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Nicholas Ayache, Alain Damasio, Yuval Noah Harari, Cathy O'Neil, and Nicolas Revel. Nouvelle enquête sur l'intelligence artificielle, Champs Actuel. Flammarion, June 2020. [bibtex-key = ayache:hal-03111667] [bibtex-entry]

Xavier Pennec, Stephan Sommer, and Tom Fletcher. Riemannian Geometric Statistics in Medical Image Analysis. Academic Press, 2020. [bibtex-key = pennec:hal-02341896] [bibtex-entry]

Dajiang Zhu, Jingwen Yan, Heng Huang, Li Shen, Paul M. Thompson, Carl-Fredrik Westin, Xavier Pennec, Sarang Joshi, Mads Nielsen, Tom Fletcher, Stanley Durrleman, and Stefan Sommer. Multimodal Brain Image Analysis and Mathematical Foundations of Computational Anatomy, volume 11846 of Lecture Notes in Computer Science (LNCS). Springer, October 2019. Keyword(s): Approximation methods, Artificial intelligence, Biomedical imaging, Statistical models, Principal component analysis, Neural networks, Machine learning, Imaging genetics, Image segmentation, Image registration, Image reconstruction, Image processing, Image fusion, Statistics of surfaces, Computational anatomy. [bibtex-key = zhu:hal-02341877] [bibtex-entry]

Math in the Black Forest: Workshop on New Directions in Shape Analysis, November 2018. Published by the authors. Note: 27 pages, 4 figures. [bibtex-key = bauer:hal-01923588] [bibtex-entry]

Jorge M. Cardoso, Tal Arbel, Enzo Ferrante, Xavier Pennec, Dalca Adrian V., Sarah Parisot, Sarang Joshi, Nematollah K. Batmanghelich, Aristeidis Sotiras, Mads Nielsen, Mert Sabuncu, Fletcher Tom, Li Shen, Stanley Durrleman, and Stefan Sommer. Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics, volume 10551 of Lecture Notes in Computer Science. September 2017. Keyword(s): Data mining, Face recognition, Feature selection, Geometry, Image analysis, Image processing, Image reconstruction, Learning systems, Medical images, Medical imaging, Neural networks, Pattern recognition, Signal processing, Computer vision, Cluster analysis, Clustering algorithms, Artificial intelligence, Bayesian networks, Classification. [bibtex-key = cardoso:hal-01597839] [bibtex-entry]

Mihaela Pop, Maxime Sermesant, Pierre-Marc Jodoin, Alain Lalande, Xiahai Zhuang, Guang Yang, Alistair Young, and Olivier Bernard, editors. Statistical Atlases and Computational Models of the Heart. ACDC and MMWHS Challenges, France, 2017. Springer. [bibtex-key = pop:hal-01800814] [bibtex-entry]

Nicholas Ayache. Des images médicales au patient numérique, Leçons inaugurales du Collège de France. Collège de France / Fayard, March 2015. [bibtex-key = ayache:hal-01170613] [bibtex-entry]

Nikos Paragios, Jim Duncan, and Nicholas Ayache. Handbook of Biomedical Imaging: Methodologies and Clinical Research. Springer, 2015. [bibtex-key = paragios:inria-00616178] [bibtex-entry]

Oscar Camara, Tommaso Mansi, Mihaela Pop, Kawal Rhode, Maxime Sermesant, and Alistair Young, editors. Statistical Atlases and Computational Models of the Heart - Imaging and Modelling Challenges, volume 8896 of Lecture Notes in Computer Science, Boston, United States, 2015. Springer. [bibtex-key = camara:hal-01244233] [bibtex-entry]

Stanley Durrleman, Thomas P. Fletcher, Guido Gerig, Marc Niethammer, and Xavier Pennec, editors. Spatio-temporal Image Analysis for Longitudinal and Time-Series Image Data, volume 8682 of Lecture notes in computer science, Cambridge, United States, January 2015. Springer International Publishing. [bibtex-key = durrleman:hal-01114150] [bibtex-entry]

Pennec, Xavier, Joshi, Sarang, Nielsen, Mads, Fletcher, Thomas P., Durrleman, Stanley, Sommer, and Stefan, editors. Proceedings of the fifth international workshop on Mathematical Foundations of Computational Anatomy (MFCA 2015), Munich, Germany, August 2015. [bibtex-key = pennec:hal-01203812] [bibtex-entry]

Bjoern H. Menze, Georg Langs, Le Lu, Albert Montillo, Zhuowen Tu, and Antonio Criminisi. Medical Computer Vision: Recognition techniques and applications in medical imaging. Proceedings of the MICCAI 2012 Workshop on Medical Computer Vision (MCV 2012), volume 7766 of Lecture Notes in Computer Science. Springer, February 2013. [bibtex-key = menze:hal-00912655] [bibtex-entry]

Xavier Pennec, Sarang Joshi, Mads Nielsen, Thomas P. Fletcher, Stanley Durrleman, and Stefan Sommer. Proceedings of the Fourth International Workshop on Mathematical Foundations of Computational Anatomy - Geometrical and Statistical Methods for Biological Shape Variability Modeling (MFCA 2013), Nagoya, Japan. Inria, August 2013. [bibtex-key = pennec:hal-00873631] [bibtex-entry]

Bjoern Menze, Mauricio Reyes, Andras Jakab, Elisabeth Gerstner, Justin Kirby, and Keyvan Farahani, editors. Proceedings of the MICCAI Challenge on Multimodal Brain Tumor Image Segmentation (BRATS) 2013, Nagoya, Japan, September 2013. MICCAI. [bibtex-key = menze:hal-00912934] [bibtex-entry]

Xavier Pennec, Sarang Joshi, and Mads Nielsen, editors. Proceedings of the Third International Workshop on Mathematical Foundations of Computational Anatomy - Geometrical and Statistical Methods for Modelling Biological Shape Variability, Toronto, Canada, September 2011. [bibtex-key = Pennec:MFCAProcs:11] [bibtex-entry]

Oscar Camara, M. Pop, Kawal Rhode, Maxime Sermesant, Nic Smith, and Alistair A. Young, editors. Statistical Atlases and Computational Models of the Heart, First International Workshop, STACOM 2010, and Cardiac Electrophysiological Simulation Challenge, CESC 2010, volume 6364 of LNCS, 2010. Springer. Note: Held in Conjunction with MICCAI 2010, Beijing, China, September 20, 2010. ISBN: 978-3-642-15834-6. [bibtex-key = STACOM:2010] [bibtex-entry]

Bjoern H. Menze, Georg Langs, Zhuowen Tu, and Antonio Criminisi, editors. Medical Computer Vision: Recognition techniques and applications in medical imaging -- MICCAI-MCV 2010, volume 6533 of LNCS, Beijing, China, December 2010. Springer. [bibtex-key = miccai-mcv:2010] [bibtex-entry]

Nicholas Ayache, Hervé Delingette, and Maxime Sermesant, editors. Functional Imaging and Modeling of the Heart - FIMH 2009, volume 5528 of LNCS, Nice, France, June 2009. Springer. Note: 537 pages. [bibtex-key = FIMH:2009] [bibtex-entry]

Xavier Pennec and Sarang Joshi, editors. Proceedings of the Second International Workshop on Mathematical Foundations of Computational Anatomy - Geometrical and Statistical Methods for Modelling Biological Shape Variability, New York, USA, September 2008. [bibtex-key = Pennec:MFCAProcs:08] [bibtex-entry]

Nicholas Ayache, Sébastien Ourselin, and Anthony Maeder, editors. Medical Image Computing and Computer-Assisted Intervention - MICCAI 2007 - Part I, volume 4791 of LNCS, Brisbane, Australia, October 2007. Springer. Note: 1001 pages. [bibtex-key = miccai:i:2007] [bibtex-entry]

Nicholas Ayache, Sébastien Ourselin, and Anthony Maeder, editors. Medical Image Computing and Computer-Assisted Intervention - MICCAI 2007 - Part II, volume 4792 of LNCS, Brisbane, Australia, October 2007. Springer. Note: 977 pages. [bibtex-key = miccai:ii:2007] [bibtex-entry]

Hervé Delingette and Alejandro Frangi, editors. Proceedings of the MICCAI Workshop - From Statistical Atlases to Personalized Models: Understanding Complex Diseases in Populations and Individuals, 2006. [bibtex-key = Delingette:MICCAIworkshop:06] [bibtex-entry]

Xavier Pennec and Sarang Joshi, editors. Proceedings of the First International Workshop on Mathematical Foundations of Computational Anatomy - Geometrical and Statistical Methods for Modelling Biological Shape Variability, Copenhagen, Denmark, October 2006. [bibtex-key = Pennec:MFCAProcs:06] [bibtex-entry]

N. Ayache, editor. Computational Models for the Human Body, Handbook of Numerical Analysis (Ph. Ciarlet series editor). Elsevier, 2004. Note: 670 pages. [bibtex-key = Ayache:book:2003] [bibtex-entry]

N. Ayache and H. Delingette, editors. Proceedings of the International Symposium on Surgery Simulation and Soft Tissue Modeling, volume 2673 of Lecture Notes in Computer Science, Juan-les-Pins, France, June 2003. Springer. [bibtex-key = IS4TM:03] [bibtex-entry]

B. Marfart, H. Delingette, and G. Subsol, editors. Three Dimensional Imaging in PaleoAnthropology and Prehistoric Archeology, Liege, Belgium, 2002. BAR International Series 1049. [bibtex-key = Delingette:Paleo:02] [bibtex-entry]

M.G. Linguraru and I. Moisil. Stiinta Sistemelor si a Calculatoarelor. Consoft, 2001. [bibtex-key = Linguraru:Book:01] [bibtex-entry]

J.L. Dugelay and G. Subsol, editors. Traitement du Signal - numéro spécial Réalité Virtuelle, volume 16(1), 1999. [bibtex-key = Dugelay:ts:99] [bibtex-entry]

G. Subsol, editor. International Scientific Workshop on Virtual Reality and Prototyping, Laval (France), June 1999. Note: Version électronique : https://www-sop.inria.fr/epidaure/GT-RV/JT-GT-RV7. [bibtex-key = Subsol99.1] [bibtex-entry]

E. Cuchet and G. Subsol, editors. Model-Based 3D Image Analysis, IIT, Mumbai (Inde), 1998. IEEE Computer Society. [bibtex-key = MB3IA98] [bibtex-entry]

J. L. Dugelay, G. Eude, and G. Subsol, editors. 6èmes Journées de Travail du GT Réalité Virtuelle, Issy-les-Moulineaux (France), 1998. [bibtex-key = JTGTRV6.98] [bibtex-entry]

O. Balet, R. Caubet, J.-P. Jessel, and G. Subsol, editors. Journées Nationales Réalité Virtuelle. IRIT, Toulouse (France), October 1996. [bibtex-key = JTGTRV5.96] [bibtex-entry]

N. Ayache, editor. First international conference on computer vision, virtual reality and robotics in medicine, CVRMed'95, volume 905 of Lecture Notes in Computer Science, Nice, France, April 1995. Springer. [bibtex-key = CVRMed95] [bibtex-entry]

O. Monga and R. Horaud. Vision par ordinateur, outils fondamentaux. Editions Hermes (Traité des Nouvelles Technologies, série Informatique), Août 1993. [bibtex-key = monhor93] [bibtex-entry]

J. Lévy Véhel. Etat de l'Art en Géométrie Fractale. SGDN, 1992. [bibtex-key = levy92d] [bibtex-entry]

N. Ayache. Artificial Vision for Mobile robots - Stereo-vision and Multisensor Perception. MIT-Press, 1991. Note: 342 pages. [bibtex-key = ayache91] [bibtex-entry]

Nicholas Ayache. Vision Stéréoscopique et Perception Multisensorielle: Application à la robotique mobile. Inter-Editions (MASSON), 1989. Note: 314 pages, in French. [bibtex-key = ayache-book89] [bibtex-entry]

Gaëtan Desrues. Personalised 3D electromechanical models of the heart for cardiac resynchronisation therapy planning in heart failure patients. Theses, Université Côte d'Azur, March 2023. Keyword(s): Patient-specific simulation, Digital twin, ECG, CRT, Cardiac electrophysiology, Biomechanics, Finite element method, Artificial intelligence, Simulation personnalisée, Jumeau numérique, ECG, CRT, Électrophysiologie cardiaque, Biomécanique, Méthode des éléments finis, Intelligence artificielle. [bibtex-key = desrues:tel-04220830] [bibtex-entry]

Yann Fraboni. Reliability and robustness of federated learning in practical applications. Theses, Université Côte d'Azur, May 2023. Keyword(s): Federated learning, Heterogeneous data, Privacy, Distributed optimization, Bias, Apprentissage fédéré, Données hétérogènes, Protection des données, Optimisation distribuée, Biais. [bibtex-key = fraboni:tel-04141520] [bibtex-entry]

Dimitri Hamzaoui. AI-based diagnosis of prostate cancer from multiparametric MRI. Theses, Université Côte d'Azur, June 2023. Keyword(s): Machine learning, Prostate-cancer, Inter-expert variability, Segmentation, Consensus, Medical imaging, Artificial intelligence, Apprentissage profond, Prostate-cancer, Variabilité inter-expert, Segmentation, Consensus, Imagerie médicale, Intelligence artificielle. [bibtex-key = hamzaoui:tel-04166332] [bibtex-entry]

Etrit Haxholli. Scalable and flexible density estimation for complex data distributions. Theses, Université Côte d'Azur, October 2023. Keyword(s): Density estimation, Normalizing flows, Diffusion models, Extreme value theorie, Tail modelling, Loss function distributions, Peaks-over-threshold, Cross-tail-estimation, Estimation de la densité, Flux de normalisation, Modèles de diffusion, Théorie des valeurs extrêmes, Modélisation de la queue, Distributions de la fonction de perte, Pics-au-dessus-du-seuil, Estimation de la queue croisée. [bibtex-key = haxholli:tel-04416188] [bibtex-entry]

Victoriya Kashtanova. Learning cardiac electrophysiology dynamics with PDE-based physiological constraints for data-driven personalised predictions. Theses, Université Côte d'Azur, June 2023. Keyword(s): Physics-based learning, Deep learning, Cardiac electrophysiology, Model personalisation, PDE, Simulations, Apprentissage basé sur la physique, Apprentissage profond, Electrophysiologie cardiaque, Personnalisation de modèle, EDP, Simulations. [bibtex-key = kashtanova:tel-04176798] [bibtex-entry]

Elodie Maignant. Barycentric embeddings for geometric manifold learning : with application to shapes and graphs. Theses, Université Côte d'Azur, December 2023. Keyword(s): Geometric learning, Riemannian and barycentric geometry, Manifold learning, Quotient manifolds, Kendall shape spaces, Statistical graph analysis, Apprentissage géométrique, Géométrie riemannienne et barycentrique, Apprentissage de variétés, Variétés quotient, Espaces de formes de Kendall, Analyse statistique de graphes. [bibtex-key = maignant:tel-04452790] [bibtex-entry]

Morten Akhoj Pedersen. Riemannian and sub-riemannian methods for dimension reduction. Theses, Université Côte d'Azur ; Kobenhavns universitet, November 2023. Keyword(s): Geometrisk statistik, Differentialgeometry, Riemannsk geometri, Sub-Riemannsk geometri, Matematisk statistik, Maskinlaering, Geometric statistics, Sub-riemannian geometry, Mathematical statistics, Differential geometry, Géometrie riemannienne, Machine learning, Statistiques géométriques, Géometrie sous-riemannienne, Statistique mathématique, Géométrie différentielle, Géometrie riemannienne, Apprentissage automatique. [bibtex-key = pedersen:tel-04391602] [bibtex-entry]

Santiago Smith Silva Rincon. Federated Learning of Biomedical Data in Multicentric Imaging Studies. Theses, UCA, Inria, July 2023. Keyword(s): federated learning, healthcare, data protection, GDPR, CCPA, medical imaging, data harmonization, meta-analysis, mega-analysis, Fed-BioMed, Bayesian optimization, random effect models, FedComBat, apprentissage fédéré, santé, protection des données, RGPD, CCPA, imagerie médicale, harmonisation des données, méta-analyse, méganalyse, Fed-BioMed, optimisation bayésienne, modèles à effets aléatoires, FedComBat. [bibtex-key = silvarincon:tel-04417044] [bibtex-entry]

Paul Tourniaire. AI-based selection of imaging and biological markers predictive of therapy response in lung cancer. Theses, Université Côte d'Azur, June 2023. Keyword(s): Digital pathology, Multiple instance learning, Mixed supervision, Deep learning, Survival analysis, Lung cancer, Immunotherapy, Histopathologie numérique, Apprentissage multi-instance, Supervision mélangée, Apprentissage profond, Analyse de survie, Cancer du poumon, Immunothérapie. [bibtex-key = tourniaire:tel-04189450] [bibtex-entry]

Yingyu Yang. Automatic analysis of cardiac function with artificial intelligence : multimodal approach for portable echocardiographic devices. Theses, Université Côte d'Azur, December 2023. Keyword(s): Cardiac function analysis, Deep learning, Echocardiography segmentation, Echocardiography motion tracking, Electrocardiogram decomposition, Multi-modal learning, Deep learning with uncertainty, Analyse de la fonction cardiaque, Apprentissage profond, Segmentation de l'échocardiographie, Suivi du mouvement en échocardiographie, Décomposition de l'électrocardiogramme, Apprentissage multimodal, Apprentissage profond avec incertitude. [bibtex-key = yang:tel-04422777] [bibtex-entry]

Hind Dadoun. AI-based analysis of abdominal ultrasound images to support medical diagnosis. Theses, Université Côte d'Azur, December 2022. Keyword(s): Ultrasound imaging, Bayesian learning, Object detection, Self-supervised learning, Semi-supervised learning, Natural language processing, Imagerie ultrasonore, Apprentissage bayésien, Détection d'objets, Apprentissage auto-supervisé, Apprentissage semi-supervisé, Traitement du langage naturel. [bibtex-key = dadoun:tel-03984539] [bibtex-entry]

Florent Jousse. Statistical modeling of face morphology for dermatology and plastic surgery. Theses, Université Côte d'Azur, September 2022. Keyword(s): Statistical shape modeling, Shape registration, Face modeling, Geodesic kernel, Disentangled learning, Partial least squares, Modélisation statistique de forme, Recalage de formes, Modélisation du visage, Noyau géodésique, Démêlage de représentations, Moindres carrés partiels. [bibtex-key = jousse:tel-03890672] [bibtex-entry]

Buntheng Ly. Deep learning on large clinical databases for image-based predictions of cardiac arrhythmias. Theses, Université Côte d'Azur, December 2022. Keyword(s): Cardiac arrhythmia, Artificial intelligence, Explainable learning, Cardiac imaging, Multi-modality, Arythmie cardiaque, Intelligence artificielle, Modèle explicable, Imagerie cardiaque, Multi-modalité. [bibtex-key = ly:tel-04088542] [bibtex-entry]

Yann Thanwerdas. Riemannian and stratified geometries on covariance and correlation matrices. Theses, Université Côte d'Azur, May 2022. Keyword(s): Riemannian geometry, Covariance matrices, Correlation matrices, Families of metrics, Geodesics, Stratified spaces, Géométrie riemannienne, Matrices de covariance, Matrices de corrélation, Familles de métriques, Géodésiques, Espaces stratifiés. [bibtex-key = thanwerdas:tel-03698752] [bibtex-entry]

Clément Abi Nader. Modelling and simulating the progression of Alzheimer's disease through the analysis of multi-modal neuroimages and clinical data. Theses, Université Côte d'Azur, June 2021. Keyword(s): Alzheimer's disease, Clinical trials, Magnetic resonance imaging, Positron emission tomography, Machine learning, Gaussian processes, Variational autoencoder, Dynamical systems, Maladie d'Alzheimer, Essais cliniques, Imagerie par résonance magnétique, Tomographie par émission de positons, Apprentissage automatique, Processus gaussiens, Auto-encodeur variationnel, Systèmes dynamiques. [bibtex-key = abinader:tel-03377153] [bibtex-entry]

Luigi Antelmi. Statistical learning on heterogeneous medical data with bayesian latent variable models : application to neuroimaging dementia studies. Theses, Université Côte d'Azur, July 2021. Keyword(s): Alzheimer's disease, Neuro-imaging, Magnetic resonance imaging, Positron emission tomography, Variational autoencoder, Multi-task learning, High dimensional data, Maladie d'Alzheimer, Neuro-imagerie, Imagerie par résonnance magnétique, Tomographie par émission de positrons, Auto-encodeur variationnel, Apprentissage multi-tâche, Données de haute dimension, Données multimodales. [bibtex-key = antelmi:tel-03474169] [bibtex-entry]

Benoît Audelan. Probabilistic segmentation modelling and deep learning-based lung cancer screening. Theses, Université Côte d'Azur, July 2021. Keyword(s): Medical imaging, Image segmentation, Artificial intelligence, Machine learning, Deep learning, Lung cancer, Imagerie médicale, Segmentation d'images, Intelligence artificielle, Apprentissage artificiel, Apprentissage profond, Cancer du poumon. [bibtex-key = audelan:tel-03406789] [bibtex-entry]

Tania Bacoyannis. Deep probabilistic generative model for the inverse problem of electrocardiography. Theses, Université Côte d'Azur, December 2021. Keyword(s): Cardiac activation, Computational modelling, Data processing, Deep learning, Electrocardiography, Generative model, Inverse problem, Activation cardiaque, Apprentissage profond, Électrocardiographique, Modélisation numérique, Modèle génératif, Problème inverse, Traitement de données. [bibtex-key = bacoyannis:tel-03621337] [bibtex-entry]

Jaume Banus. Heart & Brain. Linking cardiovascular pathologies and neurodegeneration with a combined biophysical and statistical methodology. Theses, Université Côte d'Azur, May 2021. Keyword(s): Medical imaging, Cardiovascular modelling, Neurodegeneration, Lumped models, Machine learning, Variational autoencoder, Gaussian process, Personalisation, Imagerie médicale, Modélisation cardiovasculaire, Neurodégénérescence, Modèles regroupés, Apprentissage automatique, Autoencodeur variationnel, Processus Gaussien, Personnalisation. [bibtex-key = banus:tel-03242796] [bibtex-entry]

Nicolas Guigui. Computational methods for statistical estimation on Riemannian manifolds and application to the study of the cardiac deformations. Theses, Université Côte d'Azur, November 2021. Keyword(s): Differential geometry, Computational anatomy, Geometric statistics, Géométrie différentielle, Anatomie computationnelle, Statistiques géométriques. [bibtex-key = guigui:tel-03563980] [bibtex-entry]

Zihao Wang. Deep generative learning for medical data processing, analysis and modeling : application to cochlea CT imaging. Theses, Université Côte d'Azur, September 2021. Keyword(s): Generative learning, Bayesian learning, Stochastic flow, Deep learing, Apprentissage génératif, Apprentissage bayésien, Flux stochastique, Apprentissage profond. [bibtex-key = wang:tel-03827231] [bibtex-entry]

Nicolas Cedilnik. Image-based Personalised Models of Cardiac Electrophysiology for Ventricular Tachycardia Therapy Planning. Theses, Université Côte d'Azur, December 2020. Keyword(s): Ventricular tachycardia, Model personalisation, Cardiac electrophysiology, Computed tomography, Tachycardie ventriculaire, Personnalisation de modèles, Électrophysiologie cardiaque, Imagerie tomodensitométrique. [bibtex-key = cedilnik:tel-03147908] [bibtex-entry]

Julian Krebs. Robust medical image registration and motion modeling based on machine learning. Theses, Université Côte d'Azur, June 2020. Keyword(s): Medical Image Registration, Motion Modeling, Machine Learning, Varitiaonal Autoencoder, Sudden Cardiac Death Risk, Recalage d'images médicales, Modélisation du mouvement, Apprentissage profond. [bibtex-key = krebs:tel-02954033] [bibtex-entry]

Marco Lorenzi. Modelling pathological processes from heterogeneous and high-dimensional biomedical data. Habilitation à diriger des recherches, UCA, January 2020. Keyword(s): statistical learning, medical imaging, brain, machine learning, Alzheimer's disease, federated learning, genetics, apprentissage statistique, imageie medicale, cerveau, apprentissage par ordinateurs, maladie d'Alzheimer, apprentissge féderé genetics. [bibtex-key = lorenzi:tel-03150585] [bibtex-entry]

Wen Wei. Learning brain alterations in multiple sclerosis from multimodal neuroimaging data. Theses, Université Côte d'Azur, June 2020. Keyword(s): Multiple Sclerosis, PET Imaging, MR Imaging, Brain Alterations, Deep Learning, Convolutional Neural Networks (CNN), Generative Adversarial Network (GAN), Image Synthesis, Missing MRI Sequences, Missing Modalities, Sclérose en Plaques, TEP, IRM, Altérations cérébrales, Apprentissage en profondeur, Réseau de Neurones Convolutifs (CNN), Réseaux Antagonistes Génératifs (GAN), Synthèse d'images, Séquences IRM Manquantes, Modalités Manquantes. [bibtex-key = wei:tel-02862395] [bibtex-entry]

Shuman Jia. Population-based models of shape, structure, and deformation in atrial fibrillation. Theses, COMUE Université Côte d'Azur (2015 - 2019), December 2019. Keyword(s): Cardiac image analysis, Atrial fibrillation, Segmentation, Fat, Statistical shape analysis, Parallel transport, Analyse d'images cardiaques, Fibrillation auriculaire, Segmentation, Graisse, Analyse statistique des formes, Transport parallèle. [bibtex-key = jia:tel-02428638] [bibtex-entry]

Pawel Mlynarski. Deep learning for segmentation of brain tumors and organs at risk in radiotherapy planning. Theses, COMUE Université Côte d'Azur (2015 - 2019), November 2019. Keyword(s): Convolutional Neural Networks, Semi-supervised learning, MRI, Radiotherapy, Brain tumor, Organs at risk, Réseau neuronal convolutif, Apprentissage semi-supervisé, IRM, Radiothérapie, Tumeur cérébrale, Organes à risque. [bibtex-key = mlynarski:tel-02358374] [bibtex-entry]

Raphaël Sivera. Modeling and measuring the brain morphological evolution using structural MRI in the context of neurodegenerative diseases. Theses, COMUE Université Côte d'Azur (2015 - 2019), November 2019. Keyword(s): Morphometry, Aging, Alzheimer's disease, MRI, Longitudinal models, Multivariate statistical analysis, Morphométrie, Vieillissement, Maladie d'Alzheimer, IRM, Modèles longitudinaux, Statistiques multivariées. [bibtex-key = sivera:tel-02389924] [bibtex-entry]

Qiao Zheng. Deep learning for robust segmentation and explainable analysis of 3d and dynamic cardiac images. Theses, COMUE Université Côte d'Azur (2015 - 2019), March 2019. Keyword(s): Deep learning, Cardiac segmentation, Cardiac analysis, Cine MRI, Apprentissage profond, Segmentation cardiaque, Analyse cardiaque, Ciné-IRM. [bibtex-key = zheng:tel-02083415] [bibtex-entry]

Pamela Moceri. From normal right ventricle to pathology : shape and function analysis with different loading conditions using imaging and modelling. Theses, COMUE Université Côte d'Azur (2015 - 2019), January 2018. Keyword(s): Right ventricle, Medical imaging, Echocardiography, Strain imaging, Fonction ventriculaire droite, Imagerie médicale, Échocardiographie, Modélisation. [bibtex-key = moceri:tel-01781331] [bibtex-entry]

Thomas Demarcy. Segmentation and study of anatomical variability of the cochlea from medical images. Theses, COMUE Université Côte d'Azur (2015 - 2019), July 2017. Keyword(s): Cochlea, Segmentation, Shape model, Shape variability, Cochlée, Segmentation, Modèle de forme, Variabilité anatomique. [bibtex-key = demarcy:tel-01609910] [bibtex-entry]

Loïc Devilliers. Consistency of statistics in infinite dimensional quotient spaces. Theses, COMUE Université Côte d'Azur (2015 - 2019), November 2017. Keyword(s): Frechet mean, Quotient space, Template estimation, Moyenne de Fréchet, Espace quotient, Estimation de template. [bibtex-key = devilliers:tel-01683607] [bibtex-entry]

Sophie Giffard-Roisin. Non-invasive personalisation of cardiac electrophysiological models from surface electrograms. Theses, COMUE Université Côte d'Azur (2015 - 2019), December 2017. Keyword(s): ECG imaging, Personalisation, Cardiac Electro-physiology Model, Machine learning, Simulated database, Inverse problem, Imagerie ECG, Personnalisation, Modèle électrophysiologique cardiaque, Apprentissage machine, Base de données simulée, Problème inverse. [bibtex-key = giffardroisin:tel-01771476] [bibtex-entry]

Roch Molléro. Robust personalisation of 3D electromechanical cardiac models. Application to heterogeneous and longitudinal clinical databases. Theses, COMUE Université Côte d'Azur (2015 - 2019), December 2017. Keyword(s): Cardiax modelling, Parameter estimation, Multifidelity methods, Prior probabilities, Modélisation cardiaque, Estimation de paramètres, Méthodes multi-échelles, Probabilités a priori. [bibtex-key = mollero:tel-01737200] [bibtex-entry]

Marc-Michel Rohé. Reduced representation of segmentation and tracking in cardiac images for group-wise longitudinal analysis. Theses, COMUE Université Côte d'Azur (2015 - 2019), July 2017. Keyword(s): Medical image analysis, Non-rigid registration, Deep learning, Statistical model reduction, Longitudinal analysis, Analyse d'images médicales, Recalage non-rigide, Apprentissage profond, Réduction statistique de modèle, Analyse longitudinale. [bibtex-key = rohe:tel-01575292] [bibtex-entry]

Mehdi Hadj-Hamou. Beyond volumetry in longitudinal deformation-based morphometry : application to sexual dimorphism during adolescence. Theses, COMUE Université Côte d'Azur (2015 - 2019), December 2016. Keyword(s): Longitudinal images, Evaluation, Volumetric methods, Non-rigid registration, Processing pipeline, Multivariate statistics, Group comparison, Sexual dimorphism, Images longitudinales, Évaluation, Méthodes pour la volumétrie, Recalage non-linéaire, Chaîne de traitement, Statistiques multivariées, Comparaison de groupe, Dimorphisme sexuel. [bibtex-key = hadjhamou:tel-01416569] [bibtex-entry]

Bishesh Khanal. Modeling and simulation of realistic longitudinal structural brain MRIs with atrophy in Alzheimer's disease. Theses, Université Nice Sophia Antipolis, July 2016. Keyword(s): Neurodegeneration, Alzheimer's disease, Biophysical modelling, Simulation of atrophy, Longitudinal MRIs simulation, Biomechanical simulation, Synthetic longitudinal images, Neurodégénérescence, Maladie d'Alzheimer, Modélisation biophysique, Simulation de l'atrophie, Simulation d'IRM longitudinale, Simulation biomécanique, Images longitudinales synthétiques. [bibtex-key = khanal:tel-01384678] [bibtex-entry]

Matthieu Lê. Brain tumor growth modeling : application to radiotherapy. Theses, Université Nice Sophia Antipolis, June 2016. Keyword(s): Medical imaging, Biophysical model, Personalization, Radiotherapy, Segmentation, Uncertainty, Imagerie médicale, Modèle biophysique, Personnalisation, Radiothérapie, Segmentation, Incertitude. [bibtex-key = le:tel-01376688] [bibtex-entry]

Nina Miolane. Geometric statistics for computational anatomy. Theses, COMUE Université Côte d'Azur (2015 - 2019), December 2016. Keyword(s): Statistics, Geometry, Medical imaging, Anatomy, Statistiques, Géométrie, Imagerie médicale, Anatomie. [bibtex-key = miolane:tel-01411886] [bibtex-entry]

Maxime Sermesant. When Cardiac Biophysics Meets Groupwise Statistics: Complementary Modelling Approaches for Patient-Specific Medicine. Habilitation à diriger des recherches, Université de Nice - Sophia Antipolis, June 2016. Keyword(s): cardiac modelling, biophysics, statistics, machine learning, modélisation cardiaque. [bibtex-key = sermesant:tel-01337145] [bibtex-entry]

Anant Suraj Vemuri. Inter-operative biopsy site relocalization in gastroscopy : application to oesophagus. Theses, Université Nice Sophia Antipolis, April 2016. Keyword(s): Gastro-intestinal endoscopy, Inter-operative relocalization, Electromagnetic tracking, Endoscopie gastro-intestinale, Relocalisation préopératoire, Suivi électromagnétique. [bibtex-key = vemuri:tel-01310047] [bibtex-entry]

Chloé Audigier. Computational modeling of radiofrequency ablation for the planning and guidance of abdominal tumor treatment. Theses, Université Nice Sophia Antipolis, October 2015. Keyword(s): RFA Modeling, Liver, Patient-Specific, Heat transfer, Cellular necrosis, Computational fluid dynamics, Computer model, Lattice Boltzmann method, Parameter estimation, Pre-clinical study, Medical imaging, Modélisation d'ARF, Foie, Personnalisation, Diffusion de la chaleur, Nécrose cellulaire, Mécanique des fluides, Modèle informatique, Méthode de Lattice Boltzmann, Estimation de paramètres, Étude préclinique, Imagerie médicale. [bibtex-key = audigier:tel-01256010] [bibtex-entry]

Thomas Benseghir. Topology Preserving Vascular Registration: Application to Percutaneous Coronary Intervention. Theses, Université de Nice-Sophia Antipolis, July 2015. Keyword(s): 3D/2D Registration, Coronary Arteries, Recalage 3D/2D, Artères Coronaires. [bibtex-key = benseghir:tel-01235141] [bibtex-entry]

Rocìo Cabrera Lozoya. Radiofrequency ablation planning for cardiac arrhythmia treatment using modeling and machine learning approaches. Theses, Université Nice Sophia Antipolis, September 2015. Keyword(s): Cardiac electrophysiology modeling, Intracardiac electrogram modeling, Machine learning, Radiofrequency ablation planning, Electroanatomical mapping, Local abnormal ventricular activities (LAVA), Modélisation de l'électrophysiologie cardiaque, Modélisation d'électrogrammes intracardiaques, Apprentissage automatique, Planification d'ablation par radiofréquence, Activités ventriculaires anormales locales LAVA. [bibtex-key = cabreralozoya:tel-01206478] [bibtex-entry]

Nicolas Cordier. Multi-atlas patch-based segmentation and synthesis of brain tumor MR images. Theses, Université Nice Sophia Antipolis, December 2015. Keyword(s): Patch-based, Multi-atlas, Glioma, Segmentation, Probabilistic generative model, Medical image simulation, Modality synthesis, Appariement de blocs de voxels, Multi-atlas, Gliome, Segmentation, Modèle génératif probabiliste, Simulation d'image médicale, Synthèse de modalité. [bibtex-key = cordier:tel-01237853] [bibtex-entry]

Vikash Gupta. Diffusion tensor imaging of the brain : towards quantitative clinical tools. Theses, Université Nice Sophia Antipolis, March 2015. Keyword(s): Clinical DTI, Super-resolution, Multimodal brain atlas, Population based statistical analysis, HIV, DTI clinique, Super-résolution, Multimodales atlas du cerveau, Analyse statistique basée sur la population, VIH. [bibtex-key = gupta:tel-01159964] [bibtex-entry]

Loïc Le Folgoc. Statistical learning for image-based personalization of cardiac models. Theses, Université Nice Sophia Antipolis, November 2015. Keyword(s): Inverse problem, Cardiac motion tracking, Non-rigid registration, Structured sparse bayesian learning, Automatic relevance determination, MCMC, Problème inverse, Suivi de mouvement cardiaque, Recalage non-rigide, Modélisation bayésienne parcimonieuse structurée, Détermination automatique, MCMC. [bibtex-key = lefolgoc:tel-01316449] [bibtex-entry]

Jan Margeta. Machine Learning for Simplifying the Use of Cardiac Image Databases. Theses, Ecole Nationale Supérieure des Mines de Paris, December 2015. [bibtex-key = margeta:tel-01243340] [bibtex-entry]

Erin Stretton. Simulation of patient-specific glioma models for therapy planning. Theses, Ecole Nationale Supérieure des Mines de Paris, November 2014. Keyword(s): Brain Tumor Modeling, Glioma Modeling, Computer Model, Medical Imaging, Patient-Specific, Ficher Kolmogorov Model, Modélisation de Tumeur Cérébrale, Patient-Spécifique, Imagerie Médicale, Modèle de Fisher Kolmogorov, Modèlisation numérique, Modélisation de Gliome. [bibtex-key = stretton:tel-01144425] [bibtex-entry]

Hugo Talbot. Interactive Patient-Specific Simulation of Cardiac Electrophysiology. Theses, Université des Sciences et Technologies de Lille, July 2014. Keyword(s): Cardiac Electrophysiology Modeling, Real-Time Simulation, Arrhythmia Modeling, Cardiac Electromechanics, Nonlinear Optimisation, Model Personalization, Endovascular Navigation, Training Simulation, Radio- Frequency Ablation Planning, SOFA Framework, Modélisation de l'Électrophysiologie Cardiaque, Simulation Temps-Réel, Modélisation d'Arythmie, Électromécanique Cardiaque, Optimisation Non-linéaire, Personnalisation de Modèle, Navigation Endovasculaire, Simulation d'Entrainement, Ablation Radio-Fréquence, Planning d'Ablation, Framework de Simulation SOFA. [bibtex-key = talbot:tel-01097201] [bibtex-entry]

Marine Breuilly. Small animal 4D SPECT imaging : assessment of respiratory motion and iodide biodistribution. Theses, Université Nice Sophia Antipolis, November 2013. Keyword(s): SPECT, Small animal, Dynamic images, Respiratory motion, Respiratory gating, 99mTc-pertechnetate biodistribution, Compartmental analysis, TEMP, Petit animal, Images dynamiques, Mouvement respiratoire, Synchronisation respiratoire, Biodistribution du 99mTc-pertechnétate, Analyse compartimentale. [bibtex-key = breuilly:tel-00908962] [bibtex-entry]

Ezequiel Geremia. Spatial random forests for brain lesions segmentation in MRIs and model-based tumor cell extrapolation. Theses, Université Nice Sophia Antipolis, January 2013. Keyword(s): MRI, Segmentation, Regression, Random forests, Multiple sclerosis, Gliomas, Cell density, IRM, Segmentation, Régression, Forêts aléatoires, Sclérose en plaques, Gliomes, Densité cellulaire. [bibtex-key = geremia:tel-00838795] [bibtex-entry]

Stephanie Marchesseau. Simulation de modèles personnalisés du coeur pour la prédiction de thérapies cardiaques. Theses, Ecole Nationale Supérieure des Mines de Paris, January 2013. Keyword(s): Cardiac modeling, Cardiac mechanics, Computer model, Medical imaging, Patient-specific, Specificity analysis, Modélisation Cardiaque, Mécanique Cardiaque, Modèle Informatique, Imagerie Médicale, Personnalisation, Etude de Spécificité. [bibtex-key = marchesseau:pastel-00820082] [bibtex-entry]

Kristin Mcleod. Reduced-order statistical models of cardiac growth, motion and blood flow : application to the tetralogy of Fallot heart. Theses, Université Nice Sophia Antipolis, November 2013. Keyword(s): Medical image analysis, Non-rigid registration, Statistical model reduction, Tetralogy of Fallot, Analyse d'images médicales, Recalage, Modèles statistiques réduits, Tétralogie de Fallot. [bibtex-key = mcleod:tel-00942556] [bibtex-entry]

Adityo Prakosa. Analysis and simulation of multimodal cardiac images to study the heart function. Theses, Université Nice Sophia Antipolis, January 2013. Keyword(s): Cardiac motion tracking, Synthetic cardiac sequences, Cardiac inverse electro-kinematic learning, Suivi de mouvement cardiaque, Simulation de séquences synthétiques d'images cardiaque, Problème inverse du couplage électro-cinématique. [bibtex-key = prakosa:tel-00837857] [bibtex-entry]

Marco Lorenzi. Deformation-based morphometry of the brain for the development of surrogate markers in Alzheimer's disease. Ph.D. Thesis, University of Nice Sophia Antipolis, December 2012. [bibtex-key = Lorenzi:PhD:12] [bibtex-entry]

Jatin Relan. Personalised Electrophysiological Models of Ventricular Tachycardia for Radio Frequency Ablation Therapy Planning. Ph.D. Thesis, Ecole Nationale Supérieure des Mines de Paris, June 2012. [bibtex-key = Relan:PhD:12] [bibtex-entry]

Christof Seiler. Trees on Geometrical Deformations to Model the Statistical Variability of Organs in Medical Images. Ph.D. Thesis, University of Nice Sophia Antipolis and University of Bern, September 2012. [bibtex-key = Seiler:PhD:12] [bibtex-entry]

Nicolas Toussaint. Curvilinear Analysis and Approximation of Cardiac DTI In-Vivo. PhD Thesis, King's College London, July 2012. [bibtex-key = Toussaint:PhD:12] [bibtex-entry]

Barbara André. Smart Atlas for Endomicroscopy Diagnosis Support: A Clinical Application of Content-Based Image Retrieval. Ph.D. Thesis, Ecole Nationale Supérieure des Mines de Paris, October 2011. [bibtex-key = Andre:PhD:11] [bibtex-entry]

François Chung. Regional appearance modeling for deformable model-based image segmentation. Ph.D. Thesis, Ecole Nationale Supérieure des Mines de Paris, January 2011. [bibtex-key = Chung:PhD:11] [bibtex-entry]

Liliane Ramus. Conception et utilisation d'atlas anatomiques pour la segmentation automatique : application à la radiothérapie des cancers ORL. Thèse de sciences, Université de Nice Sophia Antipolis, Juillet 2011. [bibtex-key = Ramus:PhD:11] [bibtex-entry]

Florence Billet. Assimilation de données images pour la personnalisation d'un modèle électromécanique du coeur. Thèse de sciences (PhD Thesis), Université Nice Sophia-Antipolis, July 2010. [bibtex-key = Billet:PhD:10] [bibtex-entry]

Stanley Durrleman. Statistical models of currents for measuring the variability of anatomical curves, surfaces and their evolution. Thèse de sciences (PhD Thesis), Université de Nice-Sophia Antipolis, March 2010. [bibtex-key = Durrleman:PhD:10] [bibtex-entry]

Romain Fernandez. Reconstruction tridimensionnelle et suivi de lignées cellulaires à partir d'images de microscopie laser : application à des tissus végétaux. Thèse de sciences, Université Montpellier 2, November 2010. [bibtex-key = fernandez:phd:2010] [bibtex-entry]

Heike Hufnagel. A probabilistic framework for point-based shape modeling in medical image analysis. PhD Thesis, University of Lübeck, July 2010. [bibtex-key = Hufnagel:PhD:2010] [bibtex-entry]

Tommaso Mansi. Image-Based Physiological and Statistical Models of the Heart, Application to Tetralogy of Fallot. Thèse de sciences (PhD Thesis), Ecole Nationale Supérieure des Mines de Paris, September 2010. [bibtex-key = Mansi:PhD:10] [bibtex-entry]

Ender Konukoglu. Modeling Glioma Growth and Personalizing Growth Models in Medical Images. PhD Thesis, Université Nice Sophia-Antipolis, February 2009. [bibtex-key = Konukoglu:PhD:2009] [bibtex-entry]

Jean-Marc Peyrat. Comparison of Cardiac Anatomy and Function: Statistics on Fibre Architecture from DT-MRI and Registration of 4D CT Images. PhD Thesis, Nice Sophia Antipolis University, November 2009. [bibtex-key = Peyrat:PhD:2009] [bibtex-entry]

Jean-Christophe Souplet. Évaluation de l'atrophie et de la charge lésionnelle sur des séquences IRM de patients atteints de sclérose en plaques. Thèse de sciences (PhD Thesis), Université de Nice -- Sophia-Antipolis, January 2009. [bibtex-key = Souplet:PhD:09] [bibtex-entry]

Jonathan Boisvert. Modèles de la variabilité géométrique du rachis scoliotique. PhD thesis, Université de Nice-Sophia Antipolis (France) and École Polytechnique de Montréal (Canada), March 2008. [bibtex-key = Boisvert:PhD:2008] [bibtex-entry]

Jimena Costa. Segmentation of Anatomical Structures of the Lower Abdomen using 3D Deformable Models. PhD Thesis, École Nationale Supérieure des Mines de Paris, March 2008. [bibtex-key = Costa:PhD:08] [bibtex-entry]

Pierre Fillard. Riemannian Processing of Tensors for Diffusion MRI and Computational Anatomy of the Brain. PhD Thesis, University of Nice-Sophia Antipolis, February 2008. [bibtex-key = Fillard:PhD:08] [bibtex-entry]

Tom Vercauteren. Image Registration and Mosaicing for Dynamic In Vivo Fibered Confocal Microscopy. PhD Thesis, École Nationale Supérieure des Mines de Paris, January 2008. [bibtex-key = Vercauteren:PhD:08] [bibtex-entry]

Arnaud Charnoz. Recalage d'organes intra-patient à partir de l'étude de leur réseau vasculaire : application au foie. PhD thesis, Université Louis Pasteur, Strasbourg, 2007. [bibtex-key = charnoz:phd:2007] [bibtex-entry]

Olivier Commowick. Création et Utilisation d'Atlas Anatomiques Numériques pour la Radiothérapie (Design and Use of Anatomical Atlases for Radiotherapy). Thèse de sciences (PhD Thesis), Université de Nice -- Sophia-Antipolis, February 2007. [bibtex-key = Commowick:PhD:07] [bibtex-entry]

Tristan Glatard. Description, deployment and optimization of medical image analysis workflows on production grids. Thèse de sciences (PhD Thesis), Université de Nice -- Sophia-Antipolis, November 2007. [bibtex-key = Glatard:PhD:07] [bibtex-entry]

Vincent Arsigny. Processing Data in Lie Groups: An Algebraic Approach. Application to Non-Linear Registration and Diffusion Tensor MRI. Thèse de sciences (PhD Thesis), École polytechnique, November 2006. Keyword(s): DT-MRI, Tensors, Riemannian geometry, Lie groups, interpolation, Log-Euclidean metrics, Polyaffine transformations, Diffeomorphisms, Non-rigid registration, Multi-affine registration, Magnetic Resonance Imaging, Bi-invariant means, Fréchet means, Statistics. [bibtex-key = Arsigny:PhD:2006] [bibtex-entry]

Olivier Clatz. Modèles biomécaniques et physio-pathologiques pour l'analyse d'images cérébrales. Thèse de sciences, École des Mines de Paris, February 2006. [bibtex-key = Clatz:these:2006] [bibtex-entry]

Hervé Delingette. Modélisation de structures déformables. Habilitation à diriger des recherches, Université Nice Sophia-Antipolis, March 2006. [bibtex-key = Delingette:HDR:2006] [bibtex-entry]

Guillaume Dugas-Phocion. Segmentation d'IRM Cérébrales Multi-Séquences et Application à la Sclérose en Plaques. Thèse de sciences, École des Mines de Paris, March 2006. [bibtex-key = dugas:these:2006] [bibtex-entry]

Grégoire Malandain. Les mesures de similarité pour le recalage des images médicales. Habilitation à diriger des recherches, Université Nice Sophia-Antipolis, March 2006. [bibtex-key = malandain:hdr:2006] [bibtex-entry]

Xavier Pennec. Statistical Computing on Manifolds for Computational Anatomy. Habilitation à diriger des recherches, Université Nice Sophia-Antipolis, December 2006. Keyword(s): Tensors, regularization, PDE, geometry, Riemannian geometry, Registration, statistics, manifolds. [bibtex-key = Pennec:HDR:2006] [bibtex-entry]

Julien Dauguet. L'imagerie post mortem tridimensionnelle cérébrale : constitution et apport pour l'analyse conjointe de données histologiques anatomo-fonctionnelles et la mise en correspondance avec l'imagerie in vivo. PhD thesis, École Centrale de Paris, June 2005. [bibtex-key = dauguet:thesis:2005] [bibtex-entry]

Céline Fouard. Extraction de paramètres morphométriques pour l'étude du réseau micro-vasculaire cérébral. Thèse de sciences, Université de Nice -- Sophia-Antipolis, January 2005. [bibtex-key = fouard:thesis:2005] [bibtex-entry]

Valérie Moreau-Villéger. Méthodes variationnelles et séquentielles pour l'étude de la contraction cardiaque. Thèse de sciences, Université de Nice Sophia-Antipolis, 2005. [bibtex-key = moreau:thesis:2005] [bibtex-entry]

Mauricio A. Reyes. Respiratory Motion Compensation in Emission Tomography. Thèse de sciences, Université de Nice Sophia-Antipolis, December 2005. [bibtex-key = reyes:phd:2005] [bibtex-entry]

Radu Stefanescu. Parallel nonlinear registration of medical images with a priori information on anatomy and pathology. Thèse de sciences, Université de Nice -- Sophia-Antipolis, March 2005. [bibtex-key = Stefanescu:PhD:05] [bibtex-entry]

Christophe Blondel. Modélisation 3D et 3D+t des artères coronaires à partir de séquences rotationnelles de projections rayons X. Thèse de sciences, Université de Nice Sophia Antipolis, mars 2004. [bibtex-key = blondel:thesis:2004] [bibtex-entry]

Pierre-Yves Bondiau. Mise en oeuvre et évaluation d'outils de fusion d'image en radiothérapie. Thèse de sciences, Université de Nice-Sophia Antipolis, November 2004. [bibtex-key = bondiau:thesis:2004] [bibtex-entry]

Guillaume Flandin. Utilisation d'informations géométriques pour l'analyse statistique des données d'IRM fonctionnelle. PhD thesis, Université de Nice-Sophia Antipolis, April 2004. [bibtex-key = flandin:thesis:2004] [bibtex-entry]

Stéphane Nicolau. Un système de réalité augmentée pour guider les opérations du foie en radiologie interventionnelle. PhD thesis, Université de Nice-Sophia Antipolis, November 2004. [bibtex-key = Nicolau:PhD:2004] [bibtex-entry]

Clément Forest. Simulation de chirurgie par coelioscopie : contributions à l'étude de la découpe volumique, au retour d'effort et à la modélisation des vaisseaux sanguins. PhD thesis, École Polytechnique, March 2003. [bibtex-key = Forest:Thesis:03] [bibtex-entry]

Sébastien Granger. Une approche statistique multi-échelle au recalage rigide de surfaces : Application à l'implantologie dentaire. Thèse de sciences, Ecole des Mines de Paris, April 2003.

Keyword(s): surface, registration, statistics, multi-scale, validation, ICP, EM, odontology, oriented points, saliency, tensor-voting, computer-guided surgery. Abstract:

The main subject of this work is the rigid registration of surfaces dedicated to VirtualScope, a per-operative guiding system designed for oral implants surgery. It is based on a purely statistical approach. We first show how to compute and maximize a likelihood, based on a model of the data noise, for the landmarks registration problem. This approach justifies the use of the ICP algorithm, and a new multi-scale variant named ICP/EM, which improves accuracy, speed and robustness. We introduce new noise models specifically designed for the registration of sampled and noised surfaces. We discuss about the theoretical prediction of the registration accuracy, and use it for guiding the data acquisition. We analyze in detail the experimental performances of the algorithm, and provide methods for setting optimally the parameters and ensuring the correctness of registration results. The resulting algorithm is perfectly suited to the VirtualScope application. The second part of this work deals with the more general problem of the statistical modelisation of sampled and noised curves and surfaces. Based on previous works on Saliency and Tensor Voting notions, it defines a vote field that represent the probability of a curve or surface element, knowing another element. We provide basic yet easy to implement examples of such a field, which can handle the surface shape, the sampling strategy and the measurement errors. We apply them successfully to the registration problem, and suggest to use them to derive Bayesian methods to virtually all other computer vision problems involving sampled and noised curves and surfaces. This work could lead to the design of a common statistical and multi-scale framework for these various methods.

[bibtex-key = granger:these:2003] [bibtex-entry]

Alain Pitiot. Segmentation automatique des structures cérébrales s'appuyant sur des connaissances explicites. Thèse de sciences, École des mines de Paris, November 2003. [bibtex-key = Pitiot:PhD:2003] [bibtex-entry]

M. Sermesant. Modèle électromécanique du coeur pour l'analyse d'image et la simulation (Electromechanical Model of the Heart for Image Analysis and Simulation). PhD thesis, Université de Nice Sophia Antipolis, May 2003. [bibtex-key = Sermesant:Thesis:03] [bibtex-entry]

Jonathan Stoeckel. Outils de classification pour l'aide au diagnostic : application à la maladie d'Alzheimer et à d'autres pathologies cérébrales. Thèse de sciences, Ecole des Mines de Paris, March 2003. [bibtex-key = stoeckel:these:2003] [bibtex-entry]

Pascal Cachier. Recalage non rigide d'images médicales volumiques - contribution aux approches iconiques et géométriques. Thèse de sciences, École Centrale des Arts et Manufactures, January 2002. Keyword(s): registration, matching, similarity measures, deformations. [bibtex-key = Cachier:These:02] [bibtex-entry]

M.G. Linguraru. Feature Detection in Mammographic Image Analysis. PhD Thesis, University of Oxford, 2002. [bibtex-key = Linguraru:PhD:02] [bibtex-entry]

Sébastien Ourselin. Recalage d'images médicales par appariement de régions - Application à la construction d'atlas histologiques 3D. Thèse de sciences, Université de Nice Sophia-Antipolis, January 2002. Keyword(s): registration, matching, similarity measures, medical images, histology, autoradiography, robust estimation. [bibtex-key = Ourselin:These:02] [bibtex-entry]

David Rey. Détection et quantification de processus évolutifs dans des images médicales tridimensionnelles : application à la sclérose en plaques. Thèse de sciences, Université de Nice Sophia-Antipolis, October 2002. Keyword(s): time analysis of images, magnetic resonance, multiple sclerosis, vector field, differential operators, statistical inference. [bibtex-key = Rey:These:02] [bibtex-entry]

Octave Migneco. Contribution à l'Analyse d'Images de la Perfusion Cérébrale : Recalage, Fusion et Traitement Statistique. Thèse de sciences, Université de Nice Sophia-Antipolis, December 2001. [bibtex-key = migneco:thesis:2001] [bibtex-entry]

Guillaume Picinbono. Modèles géométriques et physiques pour la simulation d'interventions chirurgicales. Thèse de sciences, université de Nice Sophia-Antipolis, February 2001. [bibtex-key = Picinbono:These:01] [bibtex-entry]

Sylvain Prima. Étude de la symétrie bilatérale en imagerie cérébrale volumique. Thèse de sciences, université Paris XI, Orsay, mars 2001. Keyword(s): statistics, medical images, symmetry. [bibtex-key = Prima:These:01] [bibtex-entry]

Alexis Roche. Recalage d'images médicales par inférence statistique. Thèse de sciences, Université de Nice Sophia-Antipolis, February 2001. Keyword(s): registration, matching, similarity measures, medical images, statistics, optimization, correlation ratio, mutual information. [bibtex-key = Roche:These:01] [bibtex-entry]

Karl Krissian. Traitement multi-échelle : Applications à l'imagerie médicale et à la détection tridimensionnelle de vaisseaux. Thèse de sciences, université de Nice Sophia-Antipolis, janvier 2000. [bibtex-key = phd-krissian] [bibtex-entry]

M. A. González Ballester. Morphometric Analysis of Brain Structures in MRI. PhD thesis, University of Oxford, 1999. [bibtex-key = Gonzalez:PhD:99] [bibtex-entry]

Johan Montagnat. Modéles déformables pour la segmentation et la modélisation d'images médicales 3D et 4D. Thèse de sciences, Université de Nice-Sophia Antipolis, December 1999. Keyword(s): thesis, reconstruction. [bibtex-key = montagnat:these:19991] [bibtex-entry]

L. Soler. Une nouvelle méthode de segmentation des structures anatomiques et pathologiques : application aux angioscanners 3D du foie pour la planification chirurgicale. Thèse de sciences, université de Paris XI, Orsay, November 1998. [bibtex-key = Soler:these:1998] [bibtex-entry]

S. Cotin. Modèles anatomiques déformables en temps réel : Application à la simulation de chirurgie avec retour d'effort. Thèse de sciences, Université de Nice Sophia-Antipolis, November 1997. Keyword(s): thesis, simulation. [bibtex-key = cotin_these] [bibtex-entry]

J. Declerck. Étude de la dynamique cardiaque par analyse d'images tridimensionnelles. Thèse de sciences, université Nice-Sophia Antipolis, November 1997. [bibtex-key = Declerck:these:1997] [bibtex-entry]

Márta Fidrich. Analyse multiéchelle des invariants, Application à l'imagerie médicale volumique. Thèse de sciences, université Paris XI, Orsay, 1997. [bibtex-key = Fidrich:these:1997] [bibtex-entry]

J.-P. Thirion. Mise en Correspondance Automatique d'Images Médicales Tri-Dimensionnelles. Thèse d'Habilitation à Diriger des Recherches, université de Nice, Sophia-Antipolis, France, June 1997. Keyword(s): registration, matching, deformations. [bibtex-key = thirion-habilitation] [bibtex-entry]

Pierre-Yves Bondiau. L'oeil virtuel. thèse de médecine, université de Nice Sophia-Antipolis, octobre 1996. [bibtex-key = bondiau:these:medecine:1996] [bibtex-entry]

S. Fernández-Vidal. Squelettes et outils de topologie discrète : application à l'imagerie médicale 3D. Thèse de sciences, université de Nice Sophia-Antipolis, septembre 1996. [bibtex-key = vidal:these:1996] [bibtex-entry]

Xavier Pennec. L'incertitude dans les problèmes de reconnaissance et de recalage -- Applications en imagerie médicale et biologie moléculaire. Thèse de sciences (PhD thesis), Ecole Polytechnique, Palaiseau (France), December 1996. Keyword(s): registration, matching, statistics, validation, geometry, Riemannian geometry, medical images, protein structure. [bibtex-key = Pennec:Phd:96] [bibtex-entry]

E. Bardinet. Modèles déformables contraints - applications à l'imagerie cardiaque. Thèse de sciences, université Paris IX Dauphine, December 1995. [bibtex-key = bardinet:these:1995] [bibtex-entry]

L. D. Cohen. Méthodes Variationnelles en traitement d'images. Habilitation à diriger des recherches, Ceremade-Université Paris IX Dauphine, June 1995. [bibtex-key = cohen_these] [bibtex-entry]

J. Feldmar. Recalage rigide, non-rigide et projectif d'images médicales tridimensionnelles. Thèse de sciences, École Polytechnique, December 1995. Keyword(s): registration, matching, deformations. [bibtex-key = Feldmar:these:1995] [bibtex-entry]

A. Gourdon. Applications de la Géométrie Différentielle à l'Imagerie Médicale Multidimensionelle. Thèse de sciences, Université Paris XI-Orsay, January 1995. [bibtex-key = gourdon_these] [bibtex-entry]

Gérard Subsol. Construction automatique d'atlas anatomiques à partir d'images médicales tridimensionnelles : applications à un atlas du crâne et du cerveau. Thèse de sciences, École Centrale de Paris, December 1995. [bibtex-key = subsol:these:1995] [bibtex-entry]

S. Benayoun. Calcul local du mouvement, applications à l'imagerie médicale multidimensionnelle. Thèse de sciences, Université Paris IX Dauphine, December 1994. [bibtex-key = benayoun_these] [bibtex-entry]

H. Delingette. Modélisation, Déformation et Reconnaissance d'objets tridimensionnels a l'aide de maillages simplexes. Thèse de sciences, Ecole Centrale de Paris, July 1994. Keyword(s): thesis, reconstruction, recognition. [bibtex-key = delingette_these] [bibtex-entry]

Chahab Nastar. Modèles physiques déformables et modes vibratoires pour l'analyse du mouvement non-rigide dans les images multidimensionnelles. Thèse de sciences, Ecole Nationale des Ponts et Chaussées, Juillet 1994. Keyword(s): motion tracking, deformations. [bibtex-key = NastarPhD] [bibtex-entry]

André Guéziec. Reconnaissance Automatique de Surfaces et Courbes Gauches. Application à l'Analyse d'Images Volumiques. Thèse de sciences, Université de Paris XI ORSAY, Février 1993. [bibtex-key = GueziecAndre:These93] [bibtex-entry]

O. Monga. Des images à la géométrie des objets. Mémoire d'habilitation à diriger des Recherches, Université de Paris XI (Orsay), Janvier 1993. [bibtex-key = monga93] [bibtex-entry]

I. Cohen. Modèles déformables 2-D et 3-D: Application à la segmentation dimages médicales. Thèse de sciences, Université Paris-IX Dauphine, Juin 1992. [bibtex-key = Isaac:PhD] [bibtex-entry]

G. Malandain. Filtrage, topologie et mise en correspondance d'images médicales multidimensionnelles. Thèse de sciences, Ecole Centrale de Paris, Septembre 1992. [bibtex-key = malandain92b] [bibtex-entry]

Anna Calissano, Théodore Papadopoulo, Xavier Pennec, and Samuel Deslauriers-Gauthier. Graph Alignment Exploiting the Spatial Organization Improves the Similarity of Brain Networks. Human Brain Mapping, 45(1):e26554, January 2024. [bibtex-key = calissano:hal-03910761] [bibtex-entry]

Etrit Haxholli and Marco Lorenzi. On Tail Decay Rate Estimation of Loss Function Distributions. Journal of Machine Learning Research, 25(25):1-47, February 2024. Keyword(s): Extreme Value Theory, Tail Modelling, Loss Function Distributions, Peaks-Over-Threshold, Cross-Tail-Estimation, Model Ranking. [bibtex-key = haxholli:hal-03911884] [bibtex-entry]

Justine Labory, Evariste Njomgue-Fotso, and Silvia Bottini. Benchmarking feature selection and feature extraction methods to improve the performances of machine-learning algorithms for patient classification using metabolomics biomedical data. Computational and Structural Biotechnology Journal, 23(1):1274-1287, December 2024. [bibtex-key = labory:hal-04681403] [bibtex-entry]

Riccardo Taiello, Melek Önen, Francesco Capano, Olivier Humbert, and Marco Lorenzi. Privacy preserving image registration. Medical Image Analysis, 94, May 2024. [bibtex-key = taiello:hal-04501037] [bibtex-entry]

Paul Tourniaire, Marius Ilie, Julien Mazières, Anna Vigier, François Ghiringhelli, Nicolas Piton, Jean-Christophe Sabourin, Frédéric Bibeau, Paul Hofman, Nicholas Ayache, and Hervé Delingette. WhARIO: whole-slide-image-based survival analysis for patients treated with immunotherapy. Journal of Medical Imaging, 11(03), May 2024. Keyword(s): Lung cancer LC, Whole slide image classification. [bibtex-key = tourniaire:hal-04573158] [bibtex-entry]

Zihao Wang, Yingyu Yang, Yuzhou Chen, Tingting Yuan, Maxime Sermesant, Hervé Delingette, and Ona Wu. Mutual Information Guided Diffusion for Zero-Shot Cross-Modality Medical Image Translation. IEEE Transactions on Medical Imaging, 43(8):2825-2838, March 2024. Keyword(s): Zero-shot learning, cross-modality translation, diffusion model, mutual information. [bibtex-key = wang:hal-04696849] [bibtex-entry]

Arnaud Berenbaum, Hervé Delingette, Aurélien Maire, Cécile Poret, Claire Hassen-Khodja, Stéphane Bréant, Christel Daniel, Patricia Martel, Lamiae Grimaldi, Marie Frank, Emmanuel Durand, and Florent Besson. Performance of AI-Based Automated Classifications of Whole-Body FDG PET in Clinical Practice: The CLARITI Project. Applied Sciences, 13(9):5281, May 2023. Keyword(s): FDG PET, artificial intelligence, deep learning, convolutional neural network. [bibtex-key = berenbaum:hal-04081046] [bibtex-entry]

Nina Brillat-Savarin, Carine Wu, Laurène Aupin, Camille Thoumin, Dimitri Hamzaoui, and Raphaële Renard-Penna. 3.0 T prostate MRI: Visual assessment of 2D and 3D T2-weighted imaging sequences using PI-QUAL score. European Journal of Radiology, 166:110974, September 2023. [bibtex-key = brillatsavarin:hal-04162794] [bibtex-entry]

Nicolas Cedilnik, Mihaela Pop, Josselin Duchateau, Frédéric Sacher, Pierre Jaïs, Hubert Cochet, and Maxime Sermesant. Efficient Patient-Specific Simulations of Ventricular Tachycardia Based on Computed Tomography-Defined Wall Thickness Heterogeneity. JACC: Clinical Electrophysiology, September 2023. Keyword(s): Cardiac modeling, Electrophysiology modeling, CT, Ventricular tachycardia, Medical simulation. [bibtex-key = cedilnik:hal-04255556] [bibtex-entry]

Nikos Chrisochoides, Yixun Liu, Fotis Drakopoulos, Andriy Kot, Panos Foteinos, Christos Tsolakis, Emmanuel Billias, Olivier Clatz, Nicholas Ayache, Andrey Fedorov, Alex Golby, Peter Black, and Ron Kikinis. Comparison of physics-based deformable registration methods for image-guided neurosurgery. Frontiers in Digital Health, 5, December 2023. Keyword(s): Image-guided neurosurgery, physics-based deformable registration, finite element methods (FEM), high performance computing, mesh generation. [bibtex-key = chrisochoides:hal-04334718] [bibtex-entry]

Quentin Clairon, Chloé Pasin, Irene Balelli, Rodolphe Thiébaut, and Mélanie Prague. Parameter estimation in nonlinear mixed effect models based on ordinary differential equations: An optimal control approach. Computational Statistics, September 2023. Keyword(s): Dynamic population models, Ordinary differential equations, Optimal control theory, Mechanistic models, Nonlinear mixed effects models, Clinical trial analysis. [bibtex-key = clairon:hal-03335826] [bibtex-entry]

Francesco Cremonesi, Vincent Planat, Varvara Kalokyri, Haridimos Kondylakis, Tiziana Sanavia, Victor Miguel Mateos Resinas, Babita Singh, and Silvia Uribe. The need for multimodal health data modeling: A practical approach for a federated-learning healthcare platform. Journal of Biomedical Informatics, 141:104338, May 2023. Keyword(s): Federated learning, Data model, Healthcare, Omics, Lessons learned, Medical research, Graphical. [bibtex-key = cremonesi:hal-04600442] [bibtex-entry]

Hind Dadoun, Hervé Delingette, Anne-Laure Rousseau, Eric de Kerviler, and Nicholas Ayache. Deep Clustering for Abdominal Organ Classification in US imaging. Journal of Medical Imaging, 10(3):034502, 2023. Keyword(s): ultrasound imaging, representation learning, deep clustering, semi-supervised learning. [bibtex-key = dadoun:hal-03773082] [bibtex-entry]

Yann Fraboni, Richard Vidal, Laetitia Kameni, and Marco Lorenzi. A General Theory for Federated Optimization with Asynchronous and Heterogeneous Clients Updates. Journal of Machine Learning Research, 24:1-43, March 2023. Note: Code is available https://github.com/Accenture/Labs-Federated-Learning/tree/asynchronous_FL. [bibtex-key = fraboni:hal-03720629] [bibtex-entry]

Nicolas Guigui, Nina Miolane, and Xavier Pennec. Introduction to Riemannian Geometry and Geometric Statistics: from basic theory to implementation with Geomstats. Foundations and Trends in Machine Learning, 16(3):329-493, February 2023. Keyword(s): Riemannian Geometry, Geometric Statistics, Python Library. [bibtex-key = guigui:hal-03766900] [bibtex-entry]

Dimitri Hamzaoui, Sarah Montagne, Raphaële Renard-Penna, Nicholas Ayache, and Hervé Delingette. Morphologically-Aware Consensus Computation via Heuristics-based IterATive Optimization (MACCHIatO). Journal of Machine Learning for Biomedical Imaging, 2(UNSURE 2022 Special Issue):361-389, September 2023. Keyword(s): Consensus, Distance, Heuristic, Optimization, STAPLE. [bibtex-key = hamzaoui:hal-04208018] [bibtex-entry]

Philipp Harms, Peter W. Michor, Xavier Pennec, and Stefan Sommer. Geometry of Sample Spaces. Differential Geometry and its Applications, 90:102029, October 2023. Note: 29 pages, 1 figure. [bibtex-key = harms:hal-02972385] [bibtex-entry]

Raabid Hussain, Attila Frater, Roger Calixto, Chadlia Karoui, Jan Margeta, Zihao Wang, Michel Hoen, Hervé Delingette, François Patou, Charles Raffaelli, Clair Vandersteen, and Nicolas Guevara. Anatomical Variations of the Human Cochlea Using an Image Analysis Tool. Journal of Clinical Medicine, 12(2):509, January 2023. Keyword(s): Otology, Cochlea Modeling, Medical Image Analysis, cochlear morphology, cochlear implantation, statistical analysis. [bibtex-key = hussain:hal-04388909] [bibtex-entry]

Victoriya Kashtanova, Mihaela Pop, Ibrahim Ayed, Patrick Gallinari, and Maxime Sermesant. Simultaneous data assimilation and cardiac electrophysiology model correction using differentiable physics and deep learning. Interface Focus, 13(6), December 2023. Keyword(s): Physics-based learning, Deep Learning, Cardiac electrophysiology, Simulations. [bibtex-key = kashtanova:hal-04359753] [bibtex-entry]

Fabien Lareyre, Kak Khee Yeung, Lisa Guzzi, Gilles Di Lorenzo, Arindam Chaudhuri, Christian-Alexander Behrendt, Konstantinos Spanos, and Juliette Raffort. Artificial intelligence in vascular surgical decision making. Seminars in Vascular Surgery, 36(3):448-453, September 2023. Keyword(s): Artificial intelligence, Machine learning, Vascular disease, Decision making, Precision medicine, Artificial intelligence. [bibtex-key = lareyre:hal-04361618] [bibtex-entry]

Sébastien Molière, Dimitri Hamzaoui, Anna Luzurier, Benjamin Granger, Sarah Montagne, Alexandre Allera, Malek Ezziane, Raphaële Quint, Mehdi Kalai, Nicholas Ayache, Hervé Delingette, and Raphaële Renard-Penna. Reference standard for the evaluation of automatic segmentation algorithms: Quantification of inter observer variability of manual delineation of prostate contour on MRI. Diagnostic and Interventional Imaging, August 2023. Keyword(s): Artificial intelligence Inter-reader variability Magnetic resonance imaging Prostate Segmentation. [bibtex-key = moliere:hal-04185065] [bibtex-entry]

Théodore Soulier, Olivier Colliot, Nicholas Ayache, and Benjamin Rohaut. How will tomorrow's algorithms fuse multimodal data? The example of the neuroprognosis in Intensive Care. Anaesthesia Critical Care & Pain Medicine, pp 101301, September 2023. Keyword(s): Disorders of Consciousness, Neurological Prognosis, Multimodal Data, Artificial Intelligence, Disorders of Consciousness Neurological Prognosis Multimodal Data Artificial Intelligence. [bibtex-key = soulier:hal-04227434] [bibtex-entry]

Yann Thanwerdas and Xavier Pennec. Bures-Wasserstein minimizing geodesics between covariance matrices of different ranks. SIAM Journal on Matrix Analysis and Applications, 44(3):1447-1476, September 2023. Keyword(s): Covariance matrices, PSD matrices, Bures-Wasserstein, Orbit space, Geodesics, Injection domain, 15B48, 15A63, 53B20, 53C22, 58D17, 53-08, 53A04, 54E50, 58A35. [bibtex-key = thanwerdas:hal-03647321] [bibtex-entry]

Yann Thanwerdas and Xavier Pennec. O(n)-invariant Riemannian metrics on SPD matrices. Linear Algebra and its Applications, 661:163-201, March 2023. Keyword(s): 53B20, Symmetric Positive Definite matrices, Riemannian geometry, Invariance under orthogonal transformations, Families of metrics, Log-Euclidean metric, Affine-invariant metric, Bures-Wasserstein metric, Kernel metrics. [bibtex-key = thanwerdas:hal-03338601] [bibtex-entry]

Paul Tourniaire, Marius Ilie, Paul Hofman, Nicholas Ayache, and Hervé Delingette. MS-CLAM: Mixed Supervision for the classification and localization of tumors in Whole Slide Images. Medical Image Analysis, 85:102763, 2023. Keyword(s): Digital Pathology, Mixed Supervision, Deep Learning, Camelyon16, DigestPath2019. [bibtex-key = tourniaire:hal-03972289] [bibtex-entry]

Zihao Wang, Zhifei Xu, Jiayi He, Herve Delingette, and Jun Fan. Long Short-Term Memory Neural Equalizer. IEEE Transactions on Signal and Power Integrity, 2:13-22, 2023. [bibtex-key = wang:hal-04042921] [bibtex-entry]

Marco Lorenzi, Marie Deprez, Irene Balelli, Ana L Aguila, and Andre Altmann. Integration of Multimodal Data. In Olivier Colliot, editor, Machine Learning for Brain Disorders, volume NM197 of Neuromethods, pages 573 - 597. Springer, 2023. Keyword(s): Multivariate analysis, Latent variable models, Multimodal imaging, -Omics, Imaginggenetics, Partial least squares, Canonical correlation analysis, Variational autoencoders, Sparsity, Interpretability. [bibtex-key = lorenzi:hal-04239814] [bibtex-entry]

Buntheng Ly, Mihaela Pop, Hubert Cochet, Nicolas Duchateau, Declan O'regan, and Maxime Sermesant. Outcome Prediction. In AI and Big Data in Cardiology : A Practical Guide, pages 105-133. Springer International Publishing, May 2023. [bibtex-key = ly:hal-04212068] [bibtex-entry]

Clément Abi Nader, Federica Ribaldi, Giovanni B Frisoni, Valentina Garibotto, Philippe Robert, Nicholas Ayache, and Marco Lorenzi. SimulAD: A dynamical model for personalized simulation and disease staging in Alzheimer's disease. Neurobiology of Aging, 113:73-83, May 2022. Keyword(s): Alzheimer's disease, Disease progression models, Clinical trials, Biomarkers. [bibtex-key = abinader:hal-03514292] [bibtex-entry]

Carlos Albors, Èric Lluch, Juan Francisco Gomez, Nicolas Cedilnik, Konstantinos Mountris, Tommaso Mansi, Svyatoslav Khamzin, Arsenii Dokuchaev, Olga Solovyova, Esther Pueyo, Maxime Sermesant, Rafael Sebastian, Hernán Morales, and Oscar Camara. Meshless Electrophysiological Modeling of Cardiac Resynchronization Therapy-Benchmark Analysis with Finite-Element Methods in Experimental Data. Applied Sciences, 12(13):6438, July 2022. [bibtex-key = albors:hal-03863600] [bibtex-entry]

Benoît Audelan, Dimitri Hamzaoui, Sarah Montagne, Raphaële Renard-Penna, and Hervé Delingette. Robust Bayesian fusion of continuous segmentation maps. Medical Image Analysis, 78:102398, May 2022. Keyword(s): Image segmentation, Data fusion, Consensus, Mixture. [bibtex-key = audelan:hal-03594219] [bibtex-entry]

Nicholas Ayache. La fée IA au chevet des malades. Pour la Science. Dossier, (hors série 115):18-23, May 2022. Note: The article is available at the following address: https://www.pourlascience.fr/sd/medecine/la-fee-ia-au-chevet-des-malades-23684.php. [bibtex-key = ayache:hal-03689197] [bibtex-entry]

Tania Marina Bacoyannis, Buntheng Ly, H Cochet, and Maxime Sermesant. Deep learning formulation of ECGI evaluated on clinical data. EP-Europace, 24(Supplement_1), May 2022. Keyword(s): Electrocardiography, Inverse Problem, Deep learning, Computational Modelling, Generative Model, Data Processing, Clinical Evaluation. [bibtex-key = bacoyannis:hal-03739242] [bibtex-entry]

Irene Balelli, Santiago Silva, and Marco Lorenzi. A Differentially Private Probabilistic Framework for Modeling the Variability Across Federated Datasets of Heterogeneous Multi-View Observations. Journal of Machine Learning for Biomedical Imaging, April 2022. [bibtex-key = balelli:hal-03644819] [bibtex-entry]

James Benn and Stephen Marsland. The Measurement and Analysis of Shapes. Annals of Global Analysis and Geometry, 62:47-70, April 2022. Keyword(s): Shape, Currents, Hodge theory, Sobolev diffeomorphisms, Euler Equations, Probability densities. [bibtex-key = benn:hal-03556752] [bibtex-entry]

Nathan Blanken, Jelmer Wolterink, Herve Delingette, Christoph Brune, Michel Versluis, and Guillaume Lajoinie. Super-Resolved Microbubble Localization in Single-Channel Ultrasound RF Signals Using Deep Learning. IEEE Transactions on Medical Imaging, 41(9):2532-2542, September 2022. [bibtex-key = blanken:hal-03942375] [bibtex-entry]

Hind Dadoun, Anne-Laure Rousseau, Eric de Kerviler, Jean Michel Correas, Anne-Marie Tissier, Fanny Joujou, Sylvain Bodard, Kemel Khezzane, Constance de Margerie-Mellon, Hervé Delingette, and Nicholas Ayache. Detection, Localization, and Characterization of Focal Liver Lesions in Abdominal US with Deep Learning. Radiology: Artificial Intelligence, 4(3), 2022. [bibtex-key = dadoun:hal-03583297] [bibtex-entry]

Nicolas Guigui and Xavier Pennec. Numerical Accuracy of Ladder Schemes for Parallel Transport on Manifolds. Foundations of Computational Mathematics, 22:757-790, June 2022. [bibtex-key = guigui:hal-02894783] [bibtex-entry]

Dimitri Hamzaoui, Sarah Montagne, Benjamin Granger, Alexandre Allera, Malek Ezziane, Anna Luzurier, Raphaëlle Quint, Mehdi Kalai, Nicholas Ayache, Hervé Delingette, and Raphaële Renard-Penna. Correction to: Prostate Volume Prediction on MRI: Tools, Accuracy and Variability. European Radiology, 32(7):5035-5035, 2022. Note: Correction about the name of the author Raphaële Renard-Penna. [bibtex-key = hamzaoui:hal-03888145] [bibtex-entry]

Dimitri Hamzaoui, Sarah Montagne, Benjamin Granger, Alexandre Allera, Malek Ezziane, Anna Luzurier, Raphaële Quint, Mehdi Kalai, Nicholas Ayache, Hervé Delingette, and Raphaele Renard-Penna. Prostate volume prediction on MRI: tools, accuracy and variability. European Radiology, February 2022. Note: The original publication is available at www.springerlink.com: https://link.springer.com/article/10.1007/s00330-022-08554-4. Keyword(s): Prostate, Magnetic Resonance Imaging, Volume, PSA density, Segmentation. [bibtex-key = hamzaoui:hal-03409262] [bibtex-entry]

Dimitri Hamzaoui, Sarah Montagne, Raphaele Renard-Penna, Nicholas Ayache, and Hervé Delingette. Automatic Zonal Segmentation of the Prostate from 2D and 3D T2-weighted MRI and Evaluation for Clinical Use. Journal of Medical Imaging, 9(2):024001, March 2022. Keyword(s): Prostate, Segmentation, Deep Learning, Lesion, Magnetic Resonance Imaging, Inter-rater Variability. [bibtex-key = hamzaoui:hal-03587074] [bibtex-entry]

Marius Ilie, Jonathan Benzaquen, Paul Tourniaire, Simon Heeke, Nicholas Ayache, Hervé Delingette, Elodie Long-Mira, Sandra Lassalle, Marame Hamila, Julien Fayada, Josiane Otto, Charlotte Cohen, Abel Gomez Caro, Jean Philippe Berthet, Charles Hugo Marquette, Véronique Hofman, Christophe Bontoux, and Paul Hofman. Deep learning facilitates distinguishing histologic subtypes of pulmonary neuroendocrine tumors on digital whole-slide images. Cancers, 14(7):1740, March 2022. Keyword(s): lung, neuroendocrine carcinoma, deep learning, CNN, HALO-AI. [bibtex-key = ilie:hal-03621585] [bibtex-entry]

Fabien Lareyre, Christian-Alexander Behrendt, Arindam Chaudhuri, Nicholas Ayache, Juliette Raffort, and Hervé Delingette. Big Data and Artificial Intelligence in Vascular Surgery: Time for Multidisciplinary Cross-Border Collaboration. Angiology, 73(8):697-700, September 2022. [bibtex-key = lareyre:hal-03846183] [bibtex-entry]

Jan Margeta, Raabid Hussain, Paula López Diez, Anika Morgenstern, Thomas Demarcy, Zihao Wang, Dan Gnansia, Octavio Martinez Manzanera, Clair Vandersteen, Hervé Delingette, Andreas Buechner, Thomas Lenarz, François Patou, and Nicolas Guevara. A Web-Based Automated Image Processing Research Platform for Cochlear Implantation-Related Studies. Journal of Clinical Medicine, 11(22):6640, November 2022. Keyword(s): cochlear implant, image analysis, computed tomography, machine learning, deep learning, image segmentation, 3D model, tonotopic mapping, visualization. [bibtex-key = margeta:hal-03846584] [bibtex-entry]

Mathilde Merle, Florent Collot, Julien Castelneau, Pauline Migerditichan, Mehdi Juhoor, Buntheng Ly, Valery Ozenne, Bruno Quesson, Nejib Zemzemi, Yves Coudière, Pierre Jaïs, Hubert Cochet, and Maxime Sermesant. MUSIC: Cardiac Imaging, Modelling and Visualisation Software for Diagnosis and Therapy. Applied Sciences, 12(12):6145, June 2022. Keyword(s): cardiac imaging, multimodal, electrophysiology, deep learning, biophysical modelling, inverse problems. [bibtex-key = merle:hal-03934424] [bibtex-entry]

Adele Myers, Saiteja Utpala, Shubham Talbar, Sophia Sanborn, Christian Shewmake, Claire Donnat, Johan Mathe, Umberto Lupo, Rishi Sonthalia, Xinyue Cui, Tom Szwagier, Arthur Pignet, Andri Bergsson, Soren Hauberg, Dmitriy Nielsen, Stefan Sommer, David Klindt, Erik Hermansen, Melvin Vaupel, Benjamin Dunn, Jeffrey Xiong, Noga Aharony, Itsik Pe'Er, Felix Ambellan, Martin Hanik, Esfandiar Nava-Yazdani, Christoph von Tycowicz, and Nina Miolane. ICLR 2022 Challenge for Computational Geometry & Topology: Design and Results. Proceedings of Machine Learning Research, 196:269-276, November 2022. [bibtex-key = myers:hal-03903044] [bibtex-entry]

M Nuñez-Garcia, S Finsterbach, Buntheng Ly, Marco Lorenzi, H Cochet, and Maxime Sermesant. Long-term remodelling and arrhythmogenicity after myocardial infarction using a novel image-based estimator: the Scar Maturation Score. EP-Europace, 24(Supplement_1), May 2022. [bibtex-key = nunezgarcia:hal-03909887] [bibtex-entry]

Jairo Rodrìguez-Padilla, Argyrios Petras, Julie Magat, Jason Bayer, Yann Bihan-Poudec, Dounia El Hamrani, Girish Ramlugun, Aurel Neic, Christoph Augustin, Fanny Vaillant, Marion Constantin, David Benoist, Line Pourtau, Virginie Dubes, Julien Rogier, Louis Labrousse, Olivier Bernus, Bruno Quesson, Michel Haïssaguerre, Matthias Gsell, Gernot Plank, Valéry Ozenne, and Edward Vigmond. Impact of intraventricular septal fiber orientation on cardiac electromechanical function. AJP - Heart and Circulatory Physiology, 322(6):H936-H952, June 2022. Keyword(s): diffusion tensor imaging, electromechanical models, fiber orientation, intraventricular septum, normal structural discontinuities. [bibtex-key = rodriguezpadilla:hal-03902767] [bibtex-entry]

Marius Schmidt- Mengin, Théodore Soulier, Mariem Hamzaoui, Arya Yazdan-Panah, Benedetta Bodini, Nicholas Ayache, Bruno Stankoff, and Olivier Colliot. Online hard example mining vs. fixed oversampling strategy for segmentation of new multiple sclerosis lesions from longitudinal FLAIR MRI. Frontiers in Neuroscience, 16:100405, 2022. Keyword(s): New lesions segmentation, Deep learning, Hard example mining, Multiple sclerosis, MRI. [bibtex-key = schmidtmengin:hal-03836922] [bibtex-entry]

Yann Thanwerdas and Xavier Pennec. The geometry of mixed-Euclidean metrics on symmetric positive definite matrices. Differential Geometry and its Applications, 81(101867), April 2022. Keyword(s): Symmetric Positive Definite matrices, Riemannian geometry, information geometry, families of metrics, kernel metrics, alpha-Procrustes, mixed-power-Euclidean, mixed-Euclidean, (u, v)-divergence, ($\alpha$, $\beta$)-divergence, 15B48, 53B12, 15A63, 53B20. [bibtex-key = thanwerdas:hal-03414887] [bibtex-entry]

Yann Thanwerdas and Xavier Pennec. Theoretically and computationally convenient geometries on full-rank correlation matrices. SIAM Journal on Matrix Analysis and Applications, 43(4):1851-1872, December 2022. Keyword(s): SPD matrices, Correlation matrices, Lie group, Lie group actions, Quotient-affine metric, Lie-Cholesky metrics, Poly-hyperbolic-Cholesky metrics, Euclidean-Cholesky metrics, Log-Euclidean-Cholesky metrics. [bibtex-key = thanwerdas:hal-03527072] [bibtex-entry]

Carine Wu, Sarah Montagne, Dimitri Hamzaoui, Nicholas Ayache, Hervé Delingette, and Raphaële Renard-Penna. Automatic segmentation of prostate zonal anatomy on MRI: a systematic review of the literature. Insights into Imaging, 13(1):202, December 2022. Keyword(s): Artificial intelligence, Deep learning, Magnetic resonance imaging, Prostate cancer. [bibtex-key = wu:hal-03923997] [bibtex-entry]

Nicolas Guigui and Xavier Pennec. Parallel transport, a central tool in geometric statistics for computational anatomy: Application to cardiac motion modeling. In Frank Nielsen, Arni S.R. Srinivasa Rao, and C.R. Rao, editors, Geometry and Statistics, volume 46 of Handbook of Statistics, pages 285-326. Elsevier, May 2022. Keyword(s): Parallel transport, longitudinal studies, mean trajectory, cardiac motion analysis, Schild's ladder, pole ladder, Riemannian manifolds. [bibtex-key = guigui:hal-03684811] [bibtex-entry]

Clément Abi Nader, Nicholas Ayache, Giovanni B Frisoni, Philippe Robert, and Marco Lorenzi. Simulating the outcome of amyloid treatments in Alzheimer's Disease from multi-modal imaging and clinical data. Brain Communications, February 2021. Keyword(s): Alzheimer's Disease, Clinical trials, Disease progression, Amyloid hypothesis, Mental State Examination, FAQ = Functional Assessment Questionnaire, RAVLT = Rey Auditory Verbal Learning Test, CDRSB = Clinical Dementia Rating Scale Sum of Boxes. [bibtex-key = abinader:hal-02968724] [bibtex-entry]

Tania Bacoyannis, Buntheng Ly, Nicolas Cedilnik, Hubert Cochet, and Maxime Sermesant. Deep Learning Formulation of ECGI Integrating Image & Signal Information with Data-driven Regularisation. EP-Europace, 23(Supplement_1):i55-i62, March 2021. Keyword(s): Electrocardiographic Imaging, Inverse Problem, Deep learning, Computational Modelling, Generative Model. [bibtex-key = bacoyannis:hal-03268015] [bibtex-entry]

Jaume Banus, Marco Lorenzi, Oscar Camara, and Maxime Sermesant. Biophysics-based statistical learning: Application to heart and brain interactions. Medical Image Analysis, 72, August 2021. Keyword(s): Lumped model, Cardiovascular modelling, Personalisation, White matter damage, Atrial fibrillation, Heart-Brain interaction. [bibtex-key = banus:hal-03231513] [bibtex-entry]

Paul Blanc-Durand, Simon Jégou, Salim Kanoun, Alina Berriolo-Riedinger, Caroline M Bodet-Milin, Françoise Kraeber-Bodéré, Thomas Carlier, Steven Le Gouill, René-Olivier Casasnovas, Michel Meignan, and Emmanuel Itti. Fully automatic segmentation of diffuse large B cell lymphoma lesions on 3D FDG-PET/CT for total metabolic tumour volume prediction using a convolutional neural network. European Journal of Nuclear Medicine and Molecular Imaging, pp 1362-1370, 2021. Keyword(s): Convolutional neural network, Deep learning, Lymphoma, Positron emission tomography, Segmentation, Total metabolic tumour volume, U-net. [bibtex-key = blancdurand:inserm-03006852] [bibtex-entry]

Adrià Casamitjana, Marco Lorenzi, Sebastiano Ferraris, Loïc Peter, Marc Modat, Allison Stevens, Bruce Fischl, Tom Vercauteren, and Juan Eugenio Iglesias. Robust joint registration of multiple stains and MRI for multimodal 3D histology reconstruction: Application to the Allen human brain atlas. Medical Image Analysis, October 2021. Keyword(s): nonlinear registration, 3D reconstruction, linear programming, ex vivo MRI, histology. [bibtex-key = casamitjana:hal-03374516] [bibtex-entry]

Vien Ngoc Dang, Francesco Galati, Rosa Cortese, Giuseppe Di Giacomo, Viola Marconetto, Prateek Mathur, Karim Lekadir, Marco Lorenzi, Ferran Prados, and Maria A Zuluaga. Vessel-CAPTCHA: an efficient learning framework for vessel annotation and segmentation. Medical Image Analysis, 2021. [bibtex-key = dang:hal-03220957] [bibtex-entry]

Marie Deprez, Julien Moreira, Maxime Sermesant, and Marco Lorenzi. Decoding genetic markers of multiple phenotypic layers through biologically constrained Genome-to-Phenome Bayesian Sparse Regression. Frontiers in Molecular Medicine, 2021. Keyword(s): Bayesian, Variational Dropout, Genome, Phenome, Regression, Biological constraint. [bibtex-key = deprez:hal-03477486] [bibtex-entry]

Véronique Duboc, David Pratella, Marco Milanesio, John Boudjarane, Stéphane Descombes, Véronique Paquis-Flucklinger, and Silvia Bottini. NiPTUNE: an automated pipeline for noninvasive prenatal testing in an accurate, integrative and flexible framework. Briefings in Bioinformatics, September 2021. [bibtex-key = duboc:hal-03477359] [bibtex-entry]

Nicolas Duchateau, Pamela Moceri, and Maxime Sermesant. Direction-dependent decomposition of 3D right ventricular motion: beware of approximations. Journal of The American Society of Echocardiography, 34(2):201-203, 2021. [bibtex-key = duchateau:hal-03538132] [bibtex-entry]

Sara Garbarino and Marco Lorenzi. Investigating hypotheses of neurodegeneration by learning dynamical systems of protein propagation in the brain. NeuroImage, 235:117980, July 2021. Keyword(s): Neurodegeneration, Causal model, Dynamical systems, Protein propagation, Gaussian process, Brain connectivity. [bibtex-key = garbarino:hal-03374531] [bibtex-entry]

Shuman Jia, Hubert Nivet, Josquin Harrison, Xavier Pennec, Claudia Camaioni, Pierre Jaïs, Hubert Cochet, and Maxime Sermesant. Left atrial shape is independent predictor of arrhythmia recurrence after catheter ablation for atrial fibrillation: A shape statistics study. Heart Rhythm O2, 2(6):622-632, December 2021. Keyword(s): Atrial fibrillation, Catheter ablation, CT, Left atrial shape, Recurrence, Statistical shape modeling. [bibtex-key = jia:hal-03650289] [bibtex-entry]

Julian Krebs, Hervé Delingette, Nicholas Ayache, and Tommaso Mansi. Learning a Generative Motion Model from Image Sequences based on a Latent Motion Matrix. IEEE Transactions on Medical Imaging, February 2021. Keyword(s): motion model, deformable registration, conditional variational autoencoder, gaussian process, latent variable model, motion interpolation, motion simulation, tracking. [bibtex-key = krebs:hal-03126419] [bibtex-entry]

Julian Krebs, Tommaso Mansi, Hervé Delingette, Bin Lou, Joao Lima, Susumu Tao, Luisa Ciuffo, Sanaz Norgard, Barbara Butcher, Wei Lee, Ela Chamera, Timm-Michael Dickfeld, Michael Stillabower, Joseph Marine, Robert Weiss, Gordon Tomaselli, Henry Halperin, Katherine Wu, and Hiroshi Ashikaga. CinE caRdiac magneTic resonAnce to predIct veNTricular arrhYthmia (CERTAINTY). Scientific Reports, 11(1):22683, November 2021. Keyword(s): Cardiac device therapy, Ventricular fibrillation, Ventricular tachycardia. [bibtex-key = krebs:hal-03444134] [bibtex-entry]

Georgios Lazaridis, Marco Lorenzi, Jibran Mohamed-Noriega, Soledad Aguilar-Munoa, Katsuyoshi Suzuki, Hiroki Nomoto, Sebastien Ourselin, David Garway-Heath, David Crabb, Catey Bunce, Francesca Amalfitano, Nitin Anand, Augusto Azuara-Blanco, Rupert Bourne, David Broadway, Ian Cunliffe, Jeremy Diamond, Scott Fraser, Tuan Ho, Keith Martin, Andrew Mcnaught, Anil Negi, Ameet Shah, Paul Spry, Edward White, Richard Wormald, Wen Xing, and Thierry Zeyen. OCT Signal Enhancement with Deep Learning. Ophthalmology Glaucoma, 4(3):295-304, May 2021. Keyword(s): Deep learning, Glaucoma, Image analysis, OCT, Visual fields. [bibtex-key = lazaridis:hal-03374545] [bibtex-entry]

Georgios Lazaridis, Marco Lorenzi, Sebastien Ourselin, and David Garway-Heath. Improving statistical power of glaucoma clinical trials using an ensemble of cyclical generative adversarial networks. Medical Image Analysis, 68:101906, February 2021. Keyword(s): Optical coherence tomography, Deep learning, Perceptual loss, GAN, Label fusion, Statistical power, Clinical trials, Glaucoma. [bibtex-key = lazaridis:hal-03374539] [bibtex-entry]

Alice Le Brigant, Nicolas Guigui, Sana Rebbah, and Stéphane Puechmorel. Classifying histograms of medical data using information geometry of beta distributions. IFAC-PapersOnLine, June 2021. Keyword(s): histogram analysis, clustering, medical imaging, Information geometry, classification. [bibtex-key = lebrigant:hal-02671122] [bibtex-entry]

Pamela Moceri, Nicolas Duchateau, Delphine Baudouy, Fabien Squara, Sok Sithikun Bun, Emile Ferrari, and Maxime Sermesant. Additional prognostic value of echocardiographic follow-up in pulmonary hypertension - role of 3D right ventricular area strain. European Heart Journal - Cardiovascular Imaging, 2021. Keyword(s): Pulmonary hypertension, right ventricular function, 3D echocardiography, myocardial deformation imaging. [bibtex-key = moceri:hal-03544765] [bibtex-entry]

Pamela Moceri, Nicolas Duchateau, Benjamin Sartre, Delphine Baudouy, Fabien Squara, Maxime Sermesant, and Emile Ferrari. Value of 3D right ventricular function over 2D assessment in acute pulmonary embolism. Echocardiography, 2021. Keyword(s): pulmonary embolism, right ventricular function, 3D echocardiography, speckle-tracking. [bibtex-key = moceri:hal-03544761] [bibtex-entry]

Sarah Montagne, Dimitri Hamzaoui, Alexandre Allera, Malek Ezziane, Anna Luzurier, Raphaële Quint, Mehdi Kalai, Nicholas Ayache, Hervé Delingette, and Raphaele Renard Penna. Challenge of prostate MRI segmentation on T2-weighted images: inter-observer variability and impact of prostate morphology. Insights into Imaging, 12(1), June 2021. Keyword(s): Prostate, MRI, Segmentation, Zones, Atlas. [bibtex-key = montagne:hal-03221227] [bibtex-entry]

Talia M Nir, Jean-Paul Fouche, Jintanat Ananworanich, Beau M Ances, Jasmina Boban, Bruce J Brew, Joga R Chaganti, Linda Chang, Christopher R K Ching, Lucette A Cysique, Thomas Ernst, Joshua Faskowitz, Vikash Gupta, Jaroslaw Harezlak, Jodi M Heaps-Woodruff, Charles H Hinkin, Jacqueline Hoare, John A Joska, Kalpana J Kallianpur, Taylor Kuhn, Hei y Lam, Meng Law, Christine Lebrun-Frénay, Andrew J Levine, Lydiane Mondot, Beau K Nakamoto, Bradford A Navia, Xavier Pennec, Eric C Porges, Lauren E Salminen, Cecilia M Shikuma, Wesley Surento, April D Thames, Victor Valcour, Matteo Vassallo, Adam J Woods, Paul M Thompson, Ronald A Cohen, Robert Paul, Dan J Stein, and Neda Jahanshad. Association of Immunosuppression and Viral Load With Subcortical Brain Volume in an International Sample of People Living With HIV. JAMA Network Open, 4(1):e2031190, January 2021. [bibtex-key = nir:hal-03241929] [bibtex-entry]

Maxime Sermesant, Hervé Delingette, Hubert Cochet, Pierre Jaïs, and Nicholas Ayache. Applications of artificial intelligence in cardiovascular imaging. Nature Reviews Cardiology, 18:600-609, March 2021. Keyword(s): Cardiology, Machine learning, Medical imaging. [bibtex-key = sermesant:hal-03171141] [bibtex-entry]

Maxim Stolyarchuk, Julie Ledoux, Elodie Maignant, Alain Trouvé, and Luba Tchertanov. Identification of the Primary Factors Determining the Specificity of the human VKORC1 Recognition by Thioredoxin-fold Proteins. International Journal of Molecular Sciences, 22(2):802, January 2021. Keyword(s): Trx-fold proteins, protein folding, dynamics, molecular recognition, thioldisulphide exchange, protein-protein interactions, PDI-hVKORC1 complex, 3D modelling, molecular dynamics simulation. [bibtex-key = stolyarchuk:hal-03042382] [bibtex-entry]

Zihao Wang, Thomas Demarcy, Clair Vandersteen, Dan Gnansia, Charles Raffaelli, Nicolas Guevara, and Hervé Delingette. Bayesian Logistic Shape Model Inference: application to cochlear image segmentation. Medical Image Analysis, 75:102268, October 2021. Keyword(s): Bayesian Inference, Image Segmentation, Shape Modeling. [bibtex-key = wang:hal-03372777] [bibtex-entry]

Zihao Wang, Clair Vandersteen, Thomas Demarcy, Dan Gnansia, Charles Raffaelli, Nicolas Guevara, and Hervé Delingette. Inner-ear Augmented Metal Artifact Reduction with Simulation-based 3D Generative Adversarial Networks. Computerized Medical Imaging and Graphics, 93:101990, October 2021. Keyword(s): Artifact Reduction, Deep Learning, GAN. [bibtex-key = wang:hal-03351225] [bibtex-entry]

Zhifei Xu, Zihao Wang, Yin Sun, Chulsoon Hwang, Hervé Delingette, and Jun Fan. Jitter Aware Economic PDN Optimization with a Genetic Algorithm. IEEE Transactions on Microwave Theory and Techniques, June 2021. Note: Corresponding authors: Zihao Wang; Chulsoon Hwang. Keyword(s): PDN, Jitter, PSIJ, Decoupling capacitor, Genetic algorithm, Power integrity. [bibtex-key = xu:hal-03219748] [bibtex-entry]

Kevin Zhou, Hoang Ngan Le, Khoa Luu, Hien van Nguyen, and Nicholas Ayache. Deep reinforcement learning in medical imaging: A literature review. Medical Image Analysis, 73:102193, October 2021. [bibtex-key = zhou:hal-03375000] [bibtex-entry]

Nicholas Ayache. Foreword. In Jean-François Uhl, Joaquim Jorge, Daniel Simoes Lopes, and Pedro F Campos, editors, Digital Anatomy - Applications of Virtual, Mixed and Augmented Reality, Human--Computer Interaction Series. Springer Nature, May 2021. [bibtex-key = ayache:hal-03374760] [bibtex-entry]

Xavier Pennec. Statistical analysis of organs' shapes and deformations: the Riemannian and the affine settings in computational anatomy. In Jean-François Uhl, Joaquim Jorge, Daniel Simoes Lopes, and Pedro F Campos, editors, Digital Anatomy - Applications of Virtual, Mixed and Augmented Reality, Human--Computer Interaction Series. Springer Nature, May 2021. [bibtex-key = pennec:hal-02925156] [bibtex-entry]

Benoît Audelan and Hervé Delingette. Unsupervised quality control of segmentations based on a smoothness and intensity probabilistic model. Medical Image Analysis, 68:101895, November 2020. Keyword(s): Unsupervised quality control, Image segmentation, Bayesian learning, Unsupervised quality control. [bibtex-key = audelan:hal-03044140] [bibtex-entry]

Paul Blanc-Durand, Jean-Baptiste. Schiratti, Kathryn Schutte, Paul Jehanno, Paul Herent, Frédéric Pigneur, Olivier Lucidarme, Y. Benaceur, Alexandre Sadate, Alain Luciani, Olivier Ernst, A. Rouchaud, Maud Creze, Alex Dallongeville, Nathan Banaste, Mehdi Cadi, Imad Bousaid, Nathalie Lassau, and Simon Jégou. Abdominal musculature segmentation and surface prediction from CT using deep learning for sarcopenia assessment. Diagnostic and Interventional Imaging, 101(12):789-794, December 2020. Keyword(s): Convolutional neural networks (CNN), Deep learning, Muscular body bass, Sarcopenia, Tomography, X-ray computed. [bibtex-key = blancdurand:hal-03138538] [bibtex-entry]

Emmanuel Chevallier and Nicolas Guigui. A Bi-Invariant Statistical Model Parametrized by Mean and Covariance on Rigid Motions. Entropy, 22(4):432, 2020. Keyword(s): moment-matching estimator, Euclidean groups, density estimation, wrapped distributions, rigid motions, sampling, differential of the exponential. [bibtex-key = chevallier:hal-02568245] [bibtex-entry]

James S Duncan, Michel F Insana, and Nicholas Ayache. Biomedical Imaging and Analysis In the Age of Big Data and Deep Learning. Proceedings of the IEEE, 14:3-10, January 2020. [bibtex-key = duncan:hal-02395429] [bibtex-entry]

Simon Heeke, Jonathan Benzaquen, Véronique Hofman, Elodie Long-Mira, Virginie Lespinet, Olivier Bordone, Charles-Hugo Marquette, Hervé Delingette, Marius Ilié, and Paul Hofman. Comparison of Three Sequencing Panels Used for the Assessment of Tumor Mutational Burden in NSCLC Reveals Low Comparability. Journal of Thoracic Oncology, 15(9):1535-1540, September 2020. [bibtex-key = heeke:hal-02972033] [bibtex-entry]

Nina Miolane, Nicolas Guigui, Alice Le Brigant, Johan Mathe, Benjamin Hou, Yann Thanwerdas, Stefan Heyder, Olivier Peltre, Niklas Koep, Hadi Zaatiti, Hatem Hajri, Yann Cabanes, Thomas Gerald, Paul Chauchat, Christian Shewmake, Daniel Brooks, Bernhard Kainz, Claire Donnat, Susan Holmes, and Xavier Pennec. Geomstats: A Python Package for Riemannian Geometry in Machine Learning. Journal of Machine Learning Research, 21(223):1-9, December 2020. Keyword(s): differential geometry, Riemannian geometry, statistics, machine learning, manifold. [bibtex-key = miolane:hal-02536154] [bibtex-entry]

Pawel Mlynarski, Hervé Delingette, Hamza A Alghamdi, Pierre-Yves Bondiau, and Nicholas Ayache. Anatomically consistent CNN-based segmentation of organs-at-risk in cranial radiotherapy. Journal of Medical Imaging, 7(1):1-21, February 2020. Keyword(s): segmentation, organs at risk, Convolutional Neural Networks, radiotherapy, MRI. [bibtex-key = mlynarski:hal-02181181] [bibtex-entry]

Pamela Moceri, Nicolas Duchateau, Stephane Gillon, Lolita Jaunay, Delphine Baudouy, Fabien Squara, Emile Ferrari, and Maxime Sermesant. 3D right ventricular shape and strain in congenital heart disease patients with right ventricular chronic volume loading. European Heart Journal - Cardiovascular Imaging, 2020. [bibtex-key = moceri:hal-02913107] [bibtex-entry]

Fanny Orlhac, Augustin Lecler, Julien Savatovski, Jessica Goya-Outi, Christophe Nioche, Frédérique Charbonneau, Nicholas Ayache, Frédérique Frouin, Loïc Duron, and Irène Buvat. How can we combat multicenter variability in MR radiomics? Validation of a correction procedure. European Radiology, 2020. [bibtex-key = orlhac:hal-02945627] [bibtex-entry]

Raphaël Sivera, Nicolas Capet, Valeria Manera, Roxane Fabre, Marco Lorenzi, Hervé Delingette, Xavier Pennec, Nicholas Ayache, and Philippe Robert. Voxel-based assessments of treatment effects on longitudinal brain changes in the Multidomain Alzheimer Preventive Trial cohort. Neurobiology of Aging, 94:50-59, October 2020. Keyword(s): Multidomain intervention, Clinical trial, Subjective memory complaint, Deformation-based morphometry. [bibtex-key = sivera:hal-02166357] [bibtex-entry]

Wen Wei, Emilie Poirion, Benedetta Bodini, Matteo Tonietto, Stanley Durrleman, Olivier Colliot, Bruno Stankoff, and Nicholas Ayache. Predicting PET-derived Myelin Content from Multisequence MRI for Individual Longitudinal Analysis in Multiple Sclerosis. NeuroImage, 223C(117308), December 2020. Keyword(s): Conditional GANs, Attention Mechanism, PET Imaging, Multisequence MRI, Demyelination and Remyelination, Deep Learning, Multiple Sclerosis. [bibtex-key = wei:hal-02922534] [bibtex-entry]

Qiao Zheng, Hervé Delingette, Kenneth Fung, Steffen E Petersen, and Nicholas Ayache. Pathological Cluster Identification by Unsupervised Analysis in 3,822 UK Biobank Cardiac MRIs. Frontiers in Cardiovascular Medicine, 7:164, November 2020. Keyword(s): Cluster analysis, Gaussian mixture model, Cine MRI, Cardiac pathology, Feature extraction, UK Biobank, Cardiac motion. [bibtex-key = zheng:hal-02043380] [bibtex-entry]

Nicholas Ayache. Medical Imaging in the Age of Artificial Intelligence. In Nordlinger B., Villani C., and Rus D., editors, Healthcare and Artificial Intelligence, pages 89-91. Springer International Publishing, March 2020. [bibtex-key = ayache:hal-02522507] [bibtex-entry]

Nina Miolane, Loïc Devilliers, and Xavier Pennec. Bias on estimation in quotient space and correction methods: Applications to statistics on organ shapes. In Riemannian Geometric Statistics in Medical Image Analysis, number Chap. 9, pages 343-376. Elsevier, 2020. [bibtex-key = miolane:hal-02342155] [bibtex-entry]

Xavier Pennec. Advances in Geometric Statistics for Manifold Dimension Reduction. In Handbook of Variational Methods for Nonlinear Geometric Data, pages 339-359. Springer International Publishing, April 2020. [bibtex-key = pennec:hal-02560938] [bibtex-entry]

Xavier Pennec. Manifold-valued image processing with SPD matrices. In Riemannian Geometric Statistics in Medical Image Analysis, number Chap. 3, pages 75-134. Elsevier, 2020. [bibtex-key = pennec:hal-02341958] [bibtex-entry]

Xavier Pennec and Marco Lorenzi. Beyond Riemannian geometry: The affine connection setting for transformation groups. In Riemannian Geometric Statistics in Medical Image Analysis, number Chap. 5, pages 169-229. Elsevier, 2020. [bibtex-key = pennec:hal-02342137] [bibtex-entry]

Stefan Sommer, Tom Fletcher, and Xavier Pennec. Introduction to differential and Riemannian geometry. In Riemannian Geometric Statistics in Medical Image Analysis, number Chap. 1, pages 3-37. Elsevier, 2020. [bibtex-key = sommer:hal-02341901] [bibtex-entry]

Clement Abi Nader, Nicholas Ayache, Philippe Robert, and Marco Lorenzi. Monotonic Gaussian Process for Spatio-Temporal Disease Progression Modeling in Brain Imaging Data. NeuroImage, 2019. Keyword(s): Stochastic variational inference, Clinical trials, Bayesian modeling, Alzheimer's disease, Disease progression modeling, Gaussian Process. [bibtex-key = abinader:hal-02051843] [bibtex-entry]

Luigi Antelmi, Nicholas Ayache, Philippe Robert, and Marco Lorenzi. Sparse Multi-Channel Variational Autoencoder for the Joint Analysis of Heterogeneous Data. Proceedings of Machine Learning Research, (97):302-311, 2019. [bibtex-key = antelmi:hal-02395747] [bibtex-entry]

Nicholas Ayache and Sara Colantonio. The Digital Health Revolution - Introduction to the Special Theme. ERCIM News, (118):4-5, July 2019. [bibtex-key = ayache:hal-02404520] [bibtex-entry]

Laurent Bergé, Charles Bouveyron, Marco Corneli, and Pierre Latouche. The Latent Topic Block Model for the Co-Clustering of Textual Interaction Data. Computational Statistics and Data Analysis, 137:247-270, 2019. [bibtex-key = berge:hal-01835074] [bibtex-entry]

Christian Callegari, Marco Milanesio, and Pietro Michiardi. Network level perspective in web sessions troubleshooting. International Journal of Communication Systems, 32(6):e3908, April 2019. [bibtex-key = callegari:hal-03477646] [bibtex-entry]

Paloma Compes, Emeline Tabouret, Amandine Etcheverry, Carole Colin, Romain Appay, Nicolas Cordier, Jean Mosser, Olivier Chinot, Hervé Delingette, Nadine Girard, Henry Dufour, Philippe Metellus, and Dominique Figarella-Branger. Neuro-radiological characteristics of adult diffuse grade II and III insular gliomas classified according to WHO 2016. Journal of Neuro-Oncology, 142(3):511-520, May 2019. Keyword(s): Molecular, Glioma, Neuro-radiology, Insula, Perfusion. [bibtex-key = compes:hal-02076599] [bibtex-entry]

Claire Cury, Stanley Durrleman, David Cash, Marco Lorenzi, Jennifer M Nicholas, Martina Bocchetta, John C. van Swieten, Barbara Borroni, Daniela Galimberti, Mario Masellis, Maria Carmela Tartaglia, James Rowe, Caroline Graff, Fabrizio Tagliavini, Giovanni B. Frisoni, Robert Laforce, Elizabeth Finger, Alexandre de Mendonça, Sandro Sorbi, Sébastien Ourselin, Jonathan Rohrer, Marc Modat, Christin Andersson, Silvana Archetti, Andrea Arighi, Luisa Benussi, Sandra Black, Maura Cosseddu, Marie Fallstrm, Carlos G. Ferreira, Chiara Fenoglio, Nick Fox, Morris Freedman, Giorgio Fumagalli, Stefano Gazzina, Robert Ghidoni, Marina Grisoli, Vesna Jelic, Lize Jiskoot, Ron Keren, Gemma Lombardi, Carolina Maruta, Lieke Meeter, Rick van Minkelen, Benedetta Nacmias, Linn Ijerstedt, Alessandro Padovani, Jessica Panman, Michela Pievani, Cristina Polito, Enrico Premi, Sara Prioni, Rosa Rademakers, Veronica Redaelli, Ekaterina Rogaeva, Giacomina Rossi, Martin Rossor, Elio Scarpini, David Tang-Wai, Hakan Thonberg, Pietro Tiraboschi, Ana Verdelho, and Jason Warren. Spatiotemporal analysis for detection of pre-symptomatic shape changes in neurodegenerative diseases: Initial application to the GENFI cohort. NeuroImage, 188:282-290, March 2019. Keyword(s): Clustering, Thalamus, Spatiotemporal geodesic regression, Parallel transport, Computational anatomy, Shape analysis. [bibtex-key = cury:inserm-01958916] [bibtex-entry]

Thomas Demarcy, Isabelle Pélisson, Dan Gnansia, Hervé Delingette, Nicholas Ayache, Charles Raffaelli, Clair Vandersteen, and Nicolas Guevara. Un modèle de reconstruction tridimensionnelle de la cochlée au service de l'implantation cochléaire. Cahiers de l'audition, 32(4):36-40, July 2019. [bibtex-key = demarcy:hal-02270604] [bibtex-entry]

Rubén Doste, David Soto-iglesias, Gabriel Bernardino, Alejandro Alcaine, Rafael Sebastian, Sophie Giffard-Roisin, Maxime Sermesant, Antonio Berruezo, Damian Sanchez-quintana, and Oscar Camara. A rule-based method to model myocardial fiber orientation in cardiac biventricular geometries with outflow tracts. International Journal for Numerical Methods in Biomedical Engineering, 35(4), March 2019. Keyword(s): Rule-based method, Fiber orientation, Outflow tract, Septum, Electrophysiological simulations, Outflow tract ventricular arrhythmia. [bibtex-key = doste:hal-02128531] [bibtex-entry]

Sara Garbarino, Marco Lorenzi, Neil Oxtoby, Elisabeth Vinke, Razvan Marinescu, Arman Eshaghi, M Arfan Ikram, Wiro Niessen, Olga Ciccarelli, Frederik Barkhof, Jonathan Schott, Meike Vernooij, and Daniel Alexander. Differences in topological progression profile among neurodegenerative diseases from imaging data. eLife, 8, December 2019. [bibtex-key = garbarino:hal-03374551] [bibtex-entry]

Simon Heeke, Jonathan Benzaquen, Elodie Long-Mira, Benoît Audelan, Virginie Lespinet, Olivier Bordone, Salomé Lalvée, Katia Zahaf, Michel Poudenx, Olivier Humbert, Henri Montaudié, Pierre-Michel Dugourd, Madleen Chassang, Thierry Passeron, Hervé Delingette, Charles-Hugo Marquette, Véronique Hofman, Albrecht Stenzinger, Marius Ilié, and Paul Hofman. In-House Implementation of Tumor Mutational Burden Testing to Predict Durable Clinical Benefit in Non-Small Cell Lung Cancer and Melanoma Patients. Cancers, 11, 2019. Keyword(s): tumor mutational burden, FoundationOne assay, Oncomine TML assay, lung cancer, melanoma, immunotherapy. [bibtex-key = heeke:hal-02381188] [bibtex-entry]

Simon Heeke, Hervé Delingette, Youta Fanjat, Elodie Long-Mira, Sandra Lassalle, Véronique Hofman, Jonathan Benzaquen, Charles-Hugo Marquette, Paul Hofman, and Marius Ilié. La pathologie cancéreuse pulmonaire à l'heure de l'intelligence artificielle : entre espoir, désespoir et perspectives. Annales de Pathologie, 39(2):130-136, April 2019. Keyword(s): Pathology, Histology, Lung cancer, Artificial intelligence, Convolutional neural networks, Deep learning, Pathologie Apprentissage profond, Histologie, Cancer broncho-pulmonair, Intelligence artificielle, Réseaux de neurones convolutifs, Apprentissage profond. [bibtex-key = heeke:hal-02446712] [bibtex-entry]

Paul Hofman, Nicholas Ayache, Pascal Barbry, Michel Barlaud, Audrey Bel, Philippe Blancou, Frédéric Checler, Sylvie Chevillard, Gael Cristofari, Mathilde Demory, Vincent Esnault, Claire Falandry, Eric Gilson, Olivier Guerin, Nicolas Glaichenhaus, Joël Guigay, Marius I. Ilie, Bernard Mari, Charles-Hugo Marquette, Véronique Paquis-Flucklinger, Frédéric Prate, Pierre Saintigny, Barbara Seitz-Polsky, Taycir Skhiri, Ellen van Obberghen-Schilling, Emmanuel Van Obberghen, and Laurent Yvan-Charvet. The OncoAge Consortium: Linking Aging and Oncology from Bench to Bedside and Back Again. Cancers, 11(2):1-11, February 2019. Keyword(s): education, elderly, optimization, research, well-being, aging, cancer. [bibtex-key = hofman:hal-02045442] [bibtex-entry]

Julian Krebs, Hervé Delingette, Boris Mailhé, Nicholas Ayache, and Tommaso Mansi. Learning a Probabilistic Model for Diffeomorphic Registration. IEEE Transactions on Medical Imaging, pp 2165-2176, February 2019. Keyword(s): deformable registration, deformation transport, latent variable model, probabilistic encoding, conditional variational autoencoder, deep learning. [bibtex-key = krebs:hal-01978339] [bibtex-entry]

R azvan Marinescu, Arman Eshaghi, Marco Lorenzi, Alexandra Young, Neil Oxtoby, Sara Garbarino, Sebastian Crutch, and Daniel Alexander. DIVE: A spatiotemporal progression model of brain pathology in neurodegenerative disorders. NeuroImage, 192:166-177, May 2019. [bibtex-key = marinescu:hal-03374564] [bibtex-entry]

Pawel Mlynarski, Hervé Delingette, Antonio Criminisi, and Nicholas Ayache. 3D Convolutional Neural Networks for Tumor Segmentation using Long-range 2D Context. Computerized Medical Imaging and Graphics, 73:60-72, February 2019. Keyword(s): Brain tumor, Multisequence MRI, Segmentation, 3D Convolutional Neural Networks, Ensembles of models. [bibtex-key = mlynarski:hal-01883716] [bibtex-entry]

Pawel Mlynarski, Hervé Delingette, Antonio Criminisi, and Nicholas Ayache. Deep Learning with Mixed Supervision for Brain Tumor Segmentation. Journal of Medical Imaging, July 2019. Keyword(s): Semi-supervised learning, tumor, segmentation, Convolutional Neural Networks, Convolutional N..., Semi-supervised..., MRI. [bibtex-key = mlynarski:hal-01952458] [bibtex-entry]

Roch Molléro, Xavier Pennec, Hervé Delingette, Nicholas Ayache, and Maxime Sermesant. Population-based priors in cardiac model personalisation for consistent parameter estimation in heterogeneous databases. International Journal for Numerical Methods in Biomedical Engineering, 35(2):e3158, February 2019. Keyword(s): Cardiac Electromechanical Modeling, Parameter Estimation, Personalised modeling, Parameter Selection. [bibtex-key = mollero:hal-01922719] [bibtex-entry]

Fanny Orlhac, Charles Bouveyron, and Nicholas Ayache. Radiomics: How to Make Medical Images Speak?. ERCIM News, (118):7-8, July 2019. [bibtex-key = orlhac:hal-02404530] [bibtex-entry]

Fanny Orlhac, Frédérique Frouin, Christophe Nioche, Nicholas Ayache, and Irène Buvat. Validation of A Method to Compensate Multicenter Effects Affecting CT Radiomics. Radiology, 291(1):53-59, April 2019. [bibtex-key = orlhac:hal-02401340] [bibtex-entry]

Maxime Sermesant. Improving Cardiac Arrhythmia Therapy with Medical Imaging. ERCIM News, (118):10-11, July 2019. [bibtex-key = sermesant:hal-02404534] [bibtex-entry]

Raphaël Sivera, Hervé Delingette, Marco Lorenzi, Xavier Pennec, and Nicholas Ayache. A model of brain morphological changes related to aging and Alzheimer's disease from cross-sectional assessments. NeuroImage, 198:255-270, September 2019. Keyword(s): Imaging biomarkers, Aging, Spatio-temporal model, Brain morphology, Deformations, Alzheimer's disease. [bibtex-key = sivera:hal-01948174] [bibtex-entry]

Masateru Takigawa, Josselin Duchateau, Frederic Sacher, Ruairidh Martin, Konstantinos Vlachos, Takeshi Kitamura, Maxime Sermesant, Nicolas Cedilnik, Ghassen Cheniti, Antonio Frontera, Nathaniel Thompson, Calire Martin, Grégoire Massoullié, Felix Bourier, Anna Lam, Michael Wolf, William Escande, Clémentine André, Thomas Pambrun, Arnaud Denis, Nicolas Derval, Mélèze Hocini, Michel Haïssaguerre, Hubert Cochet, and Pierre Jaïs. Are wall thickness channels defined by computed tomography predictive of isthmuses of postinfarction ventricular tachycardia?. Heart Rhythm, 16(11):1661-1668, June 2019. Keyword(s): Wall thickness, Isthmus, High-resolution mapping, Contrart-enhanced multidetector computed tomography, MUSIC, Myocardial infarction, Ventricular tachycardia. [bibtex-key = takigawa:hal-02181776] [bibtex-entry]

Wen Wei, Emilie Poirion, Benedetta Bodini, Stanley Durrleman, Nicholas Ayache, Bruno Stankoff, and Olivier Colliot. Predicting PET-derived Demyelination from Multimodal MRI using Sketcher-Refiner Adversarial Training for Multiple Sclerosis. Medical Image Analysis, 58(101546), December 2019. Keyword(s): Multimodal MRI, PET Imaging, Adversarial Training, Multiple Sclerosis. [bibtex-key = wei:hal-02276634] [bibtex-entry]

Wen Wei, Emilie Poirion, Benedetta Bodini, Stanley Durrleman, Olivier Colliot, Bruno Stankoff, and Nicholas Ayache. Fluid-attenuated inversion recovery MRI synthesis from multisequence MRI using three-dimensional fully convolutional networks for multiple sclerosis. Journal of Medical Imaging, 6(01), February 2019. Keyword(s): MR Images, FLAIR Synthesis, 3D Fully Convolutional Networks, Multiple Sclerosis, Deep Learning. [bibtex-key = wei:hal-02042526] [bibtex-entry]

Wilhelm Wimmer, Lukas Anschuetz, Stefan Weder, Franca Wagner, Hervé Delingette, and Marco Caversaccio. Human bony labyrinth dataset: Co-registered CT and micro-CT images, surface models and anatomical landmarks. Data in Brief, 27:104782, December 2019. Keyword(s): Anatomy, Cochlea, Inner ear, Morphology, Semicircular canals, Vestibule. [bibtex-key = wimmer:hal-02402404] [bibtex-entry]

Qiao Zheng, Hervé Delingette, and Nicholas Ayache. Explainable cardiac pathology classification on cine MRI with motion characterization by semi-supervised learning of apparent flow. Medical Image Analysis, 56:80-95, 2019. Keyword(s): Deep learn- ing, Cine MRI, Classifi-cation, Motion, Semi-supervised learning, Deep learn-ing, Cardiac pathology, Neural network, Apparent flow, Classifi- cation. [bibtex-key = zheng:hal-01975880] [bibtex-entry]

Martino Alessandrini, Bidisha Chakraborty, Brecht Heyde, Olivier Bernard, Mathieu de Craene, Maxime Sermesant, and Jan d'Hooge. Realistic Vendor-Specific Synthetic Ultrasound Data for Quality Assurance of 2-D Speckle Tracking Echocardiography: Simulation Pipeline and Open Access Database. IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, 65(3):411-422, March 2018. [bibtex-key = alessandrini:hal-02059841] [bibtex-entry]

Fabien Almairac, Denys Fontaine, Thomas Demarcy, Hervé Delingette, Stephanie Beuil, and Charles Raffaelli. Motor cortex neurovascular coupling: inputs from ultra--high-frequency ultrasound imaging in humans. Journal of Neurosurgery, pp 1-7, November 2018. Keyword(s): Motor cortex, Ultrasound, Imaging methodology, Clinical neurophysiology, Diagnostic technique, Cerebral blood flow, Neurovascular coupling. [bibtex-key = almairac:hal-01984498] [bibtex-entry]

Jonathan Benzaquen, Jacques Boutros, Charles Marquette, Hervé Delingette, and Paul Hofman. Lung Cancer Screening, Towards a Multidimensional Approach: Why and How?. Cancers, 10, 2018. Keyword(s): screening, lung cancer, artificial intelligence. [bibtex-key = benzaquen:hal-02045478] [bibtex-entry]

Olivier Bernard, Alain Lalande, Clement Zotti, Frederic Cervenansky, Xin Yang, Pheng-Ann Heng, Irem Cetin, Karim Lekadir, Oscar Camara, Miguel Angel Gonzalez Ballester, Gerard Sanroma, Sandy Napel, Steffen Petersen, Georgios Tziritas, Elias Grinias, Mahendra Khened, Varghese Alex Kollerathu, Ganapathy Krishnamurthi, Marc-Michel Rohé, Xavier Pennec, Maxime Sermesant, Fabian Isensee, Paul Jager, Klaus H Maier-Hein, Peter M. Full, Ivo Wolf, Sandy Engelhardt, Chrisitan Baumgartner, Lisa Koch, Jelmer Wolterink, Ivana Isgum, Yeonggul Jang, Yoonmi Hong, Jay Patravali, Shubham Jain, Olivier Humbert, and Pierre-Marc Jodoin. Deep Learning Techniques for Automatic MRI Cardiac Multi-structures Segmentation and Diagnosis: Is the Problem Solved?. IEEE Transactions on Medical Imaging, 37(11):2514-2525, May 2018. Keyword(s): MRI, Lleft and right ventricles, Cardiac segmentation and diagnosis, Myocardium, Deep learning. [bibtex-key = bernard:hal-01803621] [bibtex-entry]

Rocio Cabrera Lozoya, Benjamin Berte, Hubert Cochet, Pierre Jaïs, Nicholas Ayache, and Maxime Sermesant. Model-based Feature Augmentation for Cardiac Ablation Target Learning from Images. IEEE Transactions on Biomedical Engineering, pp 1, March 2018. Keyword(s): intracardiac electrogram modelling, cardiac elec-, Index Terms-radio-frequency ablation planning, trophysiology modelling, electroanatomical mapping. [bibtex-key = cabreralozoya:hal-01744142] [bibtex-entry]

Nicolas Cedilnik, Josselin Duchateau, Rémi Dubois, Frédéric Sacher, Pierre Jaïs, Hubert Cochet, and Maxime Sermesant. Fast Personalized Electrophysiological Models from CT Images for Ventricular Tachycardia Ablation Planning. EP-Europace, 20, November 2018. Keyword(s): Computed Tomography, Computational Modelling, Catheter Ablation, Myocardial Infarction, Sudden Cardiac Death, Electrophysiology. [bibtex-key = cedilnik:hal-01875533] [bibtex-entry]

Marco Corneli, Charles Bouveyron, Pierre Latouche, and Fabrice Rossi. The dynamic stochastic topic block model for dynamic networks with textual edges. Statistics and Computing, 2018. Keyword(s): Dynamic random graph, model based clustering, non homogeneous Poisson process, stochastic block model, topic modeling, latent Dirichlet allocation. [bibtex-key = corneli:hal-01621757] [bibtex-entry]

Nicolas Duchateau, Maxime Sermesant, Hervé Delingette, and Nicholas Ayache. Model-based generation of large databases of cardiac images: synthesis of pathological cine MR sequences from real healthy cases. IEEE Transactions on Medical Imaging, 37:755-766, 2018. Keyword(s): validation, magnetic resonance., biomechanical modeling, Image synthesis and simulation, myocardial infarct, large database for machine learning. [bibtex-key = duchateau:hal-01533788] [bibtex-entry]

Leman Feng, Pierre Alliez, Laurent Busé, Hervé Delingette, and Mathieu Desbrun. Curved Optimal Delaunay Triangulation. ACM Transactions on Graphics, 37(4):16, August 2018. Keyword(s): Bézier elements ACM Reference Format:, Mesh generation, Bézier elements, Additional Key Words and Phrases: Higher-order meshing, Optimal Delau-nay Triangulations, CCS Concepts: $\bullet$ Mathematics of computing $\rightarrow$ Mesh generation, higher order finite elements, Optimal Delaunay Triangulations, Higher-order meshing. [bibtex-key = feng:hal-01826055] [bibtex-entry]

Sebastiano Ferraris, Johannes van Der Merwe, Lennart van Der Veeken, Ferran Prados, Juan Eugenio Iglesias, Marco Lorenzi, Andrew Melbourne, Marc M Modat, Willy Gsell, Jan Deprest, and Tom Vercauteren. A magnetic resonance multi-atlas for the neonatal rabbit brain. NeuroImage, 179:187 - 198, October 2018. [bibtex-key = ferraris:hal-01843151] [bibtex-entry]

Sophie Giffard-Roisin, Hervé Delingette, Thomas Jackson, Jessica Webb, Lauren Fovargue, Jack Lee, Christopher A Rinaldi, Reza Razavi, Nicholas Ayache, and Maxime Sermesant. Transfer Learning from Simulations on a Reference Anatomy for ECGI in Personalised Cardiac Resynchronization Therapy. IEEE Transactions on Biomedical Engineering, 20, 2018. Keyword(s): Cardiac Electrophysiology, Inverse Problem of ECG, Personalisation, ECG Imaging, Index Terms-Cardiac Electrophysiology, In- verse Problem of ECG. [bibtex-key = giffardroisin:hal-01796483] [bibtex-entry]

Pietro Gori, Olivier Colliot, Linda Marrakchi Kacem, Yulia Worbe, Alexandre Routier, Cyril Poupon, Andreas Hartmann, Nicholas Ayache, and Stanley Durrleman. Double diffeomorphism: combining morphometry and structural connectivity analysis. IEEE Transactions on Medical Imaging, 37(9):2033-2043, September 2018. Keyword(s): Neural circuits, Structural connectivity, Diffeomorphisms, Multi-object, Atlas, Shape, Morphometry, Complex, Tourette. [bibtex-key = gori:hal-01709847] [bibtex-entry]

Rashed Karim, Lauren-Emma Blake, Jiro Inoue, Qian Tao, Shuman Jia, R. James James Housden, Pranav Bhagirath, Jean-Luc Duval, Marta Varela, Jonathan Behar, Loïc Cadour, Rob J van Der Geest, Hubert Cochet, Maria Drangova, Maxime Sermesant, Reza Razavi, Oleg Aslanidi, Ronak Rajani, and Kawal S. Rhode. Algorithms for left atrial wall segmentation and thickness -- Evaluation on an open-source CT and MRI image database. Medical Image Analysis, 50:36 - 53, December 2018. Keyword(s): Myocardium, Left atrial wall thickness, Left atrium, Atrial fibrillation. [bibtex-key = karim:hal-01926935] [bibtex-entry]

Marco Lorenzi, Andre Altmann, Boris Gutman, Selina Wray, Charles Arber, Derrek D Hibar, Neda J Jahanshad, Jonathan Schott, Daniel Alexander, Paul M. Thompson, and Sébastien Ourselin. Susceptibility of brain atrophy to TRIB3 in Alzheimer's disease, evidence from functional prioritization in imaging genetics. Proceedings of the National Academy of Sciences of the United States of America, 115(12):3162-3167, 2018. Keyword(s): bioinformatics, phenotype, imaging-genetics, Alzheimer's disease, genotype, GWA. [bibtex-key = lorenzi:hal-01756811] [bibtex-entry]

Kristin Mcleod, Kristin Tondel, Lilian Calvet, M Sermesant, and Xavier Pennec. Cardiac Motion Evolution Model for Analysis of Functional Changes Using Tensor Decomposition and Cross-Sectional Data. IEEE Transactions on Biomedical Engineering, 65(12):2769 - 2780, December 2018. Keyword(s): tensor decomposition, evolution modelling, Cardiac motion tracking, non-rigid image registration, spatio-temporal alignment, N-way PLS, atlas, population statistics, Tetralogy of Fallot. [bibtex-key = mcleod:hal-01736454] [bibtex-entry]

Nina Miolane, Susan Holmes, and Xavier Pennec. Topologically constrained template estimation via Morse-Smale complexes controls its statistical consistency. SIAM Journal on Applied Algebra and Geometry, 2(2):348-375, 2018. [bibtex-key = miolane:hal-01655366] [bibtex-entry]

Pamela Moceri, Nicolas Duchateau, Delphine Baudouy, Elie-Dan Schouver, Sylvie Leroy, Fabien Squara, Emile Ferrari, and Maxime Sermesant. Three-dimensional right-ventricular regional deformation and survival in pulmonary hypertension. European Heart Journal - Cardiovascular Imaging, 19:450-458, 2018. Keyword(s): pulmonary hypertension, speckle-tracking imaging, three-dimensional echocardiography. [bibtex-key = moceri:hal-01533793] [bibtex-entry]

Pamela Moceri, Maxime Sermesant, Delphine Baudouy, Emile Ferrari, and Nicolas Duchateau. Right Ventricular Function Evolution With Pregnancy in Repaired Tetralogy of Fallot. Canadian Journal of Cardiology, 34(10):1369.e9 - 1369.e11, October 2018. Keyword(s): Pregnancy, Echocardiography, Right Ventricular Function, 3D speckle-tracking imaging, Key-words: Tetralogy of Fallot. [bibtex-key = moceri:hal-01926967] [bibtex-entry]

Christophe Nioche, Fanny Orlhac, Sarah Boughdad, Sylvain Reuzé, Jessica Goya-Outi, Charlotte Robert, Claire Pellot-Barakat, Michael Soussan, Frédérique Frouin, and Irene Buvat. LIFEx: A Freeware for Radiomic Feature Calculation in Multimodality Imaging to Accelerate Advances in the Characterization of Tumor Heterogeneity. Cancer Research, 78(16):4786 - 4789, August 2018. [bibtex-key = nioche:hal-01938545] [bibtex-entry]

Fanny Orlhac, Frédérique Frouin, Christophe Nioche, Nicholas Ayache, and Irene Buvat. Validation of a method to compensate multicenter effects affecting CT radiomic features. Radiology, 2018. [bibtex-key = orlhac:hal-01953538] [bibtex-entry]

F Orlhac, P.-A Mattei, C. Bouveyron, and N Ayache. Class-specific Variable Selection in High-Dimensional Discriminant Analysis through Bayesian Sparsity. Journal of Chemometrics, pp e3097, November 2018. [bibtex-key = orlhac:hal-01811514] [bibtex-entry]

Xavier Pennec. Barycentric Subspace Analysis on Manifolds. Annals of Statistics, 46(6A):2711-2746, July 2018. Keyword(s): Manifold, Flag of subspaces, Frechet mean, Barycenter, Subspaces, Pricipal Component Analysis. [bibtex-key = pennec:hal-01343881] [bibtex-entry]

Marc-Michel Rohé, Maxime Sermesant, and Xavier Pennec. Low-Dimensional Representation of Cardiac Motion Using Barycentric Subspaces: a New Group-Wise Paradigm for Estimation, Analysis, and Reconstruction. Medical Image Analysis, 45:1-12, April 2018. Keyword(s): Cardiac motion, Low-dimensional analysis, Registration, Image synthesis. [bibtex-key = rohe:hal-01677685] [bibtex-entry]

Sergio Sanchez-Martinez, Nicolas Duchateau, Tamas Erdei, Gabor Kunszt, Svend Aakhus, Anna Degiovanni, Paolo Marino, Erberto Carluccio, Gemma Piella, Alan Fraser, and Bart Bijnens. Machine learning analysis of left ventricular function to characterize heart failure with preserved ejection fraction. Circulation: Cardiovascular Imaging, 11(4), April 2018. Keyword(s): Excercise echocardiography, Heart failure with preservec ejection fraction, Myocardial velocity, Machine learning, Non-invasive diagnostic heart failure. [bibtex-key = sanchezmartinez:hal-02282401] [bibtex-entry]

Marzia A Scelzi, Raiyan R Khan, Marco Lorenzi, Christopher Leigh, Michael D Greicius, Jonathan M. Schott, Sébastien Ourselin, and Andre Altmann. Genetic study of multimodal imaging Alzheimer's disease progression score implicates novel loci. Brain - A Journal of Neurology, 141(7):2167 - 2180, July 2018. [bibtex-key = scelzi:hal-01843380] [bibtex-entry]

Avan A Suinesiaputra, Pierre A Ablin, Xènia A Albà, Martino Alessandrini, Jack A Allen, Wenjia Bai, Serkan Cimen, Peter Claes, Brett R Cowan, Jan d'Hooge, Nicolas Duchateau, Jan Ehrhardt, Alejandro F. Frangi, Ali A Gooya, Vicente Grau, Karim Lekadir, Allen A Lu, Anirban A Mukhopadhyay, Ilkay Oksuz, Nripesh Parajuli, Xavier Pennec, Marco Pereañez, Catarina Pinto, Paolo Piras, Marc-Michel Rohé, Daniel R Rueckert, Dennis Säring, Maxime Sermesant, Kaleem Siddiqi, Mahdi Tabassian, Luciano Teresi, Sotirios A Tsaftaris, Matthias Wilms, Alistair A Young, Xingyu Zhang, and Pau Medrano-Gracia. Statistical shape modeling of the left ventricle: myocardial infarct classification challenge. IEEE Journal of Biomedical and Health Informatics, 22(3):503-515, March 2018. Keyword(s): statistical shape analysis, classification, myocardial infarct, Cardiac modeling. [bibtex-key = suinesiaputra:hal-01533805] [bibtex-entry]

Qiao Zheng, Hervé Delingette, Nicolas Duchateau, and Nicholas Ayache. 3D Consistent & Robust Segmentation of Cardiac Images by Deep Learning with Spatial Propagation. IEEE Transactions on Medical Imaging, 37:2137-2148, April 2018. Keyword(s): deep learning, spatial propagation, Cardiac segmentation, 3D consistency, neural network. [bibtex-key = zheng:hal-01753086] [bibtex-entry]

Yitian Zhou, Sophie Giffard-Roisin, Mathieu de Craene, Sorina Camarasu-Pop, Jan d'Hooge, Martino Alessandrini, Denis Friboulet, Maxime Sermesant, and Olivier Bernard. A Framework for the Generation of Realistic Synthetic Cardiac Ultrasound and Magnetic Resonance Imaging Sequences from the same Virtual Patients. IEEE Transactions on Medical Imaging, 37(3):741-754, 2018. Keyword(s): cardiac strain, Multimodal cardiac imaging, synthetic sequences, electromechanical model, motion estimation, numerical simulation. [bibtex-key = zhou:hal-01533366] [bibtex-entry]

Nicholas Ayache. L'imagerie médicale à l'heure de l'intelligence artificielle. In Cédric Villani and Bernard Nordlinger, editors, Santé et intelligence artificielle, pages 151-154. CNRS Editions, October 2018. [bibtex-key = ayache:hal-01882558] [bibtex-entry]

Charles Bouveyron. Apprentissage statistique en grande dimension et application au diagnostic oncologique par radiomique. In Cédric Villani and Bernard Nordlinger, editors, Santé et intelligence artificielle, pages 179-189. CNRS Editions, October 2018. [bibtex-key = bouveyron:hal-01884468] [bibtex-entry]

Jan L. Bruse, Elena Cervi, Kristin Mcleod, Giovanni Biglino, Maxime Sermesant, Xavier Pennec, Andrew Taylor, Silvia Schievano, and Tain-Yen Hsia. Looks Do Matter! Aortic Arch Shape After Hypoplastic Left Heart Syndrome Palliation Correlates With Cavopulmonary Outcomes. Annals of Thoracic Surgery, 103(2):645 - 654, February 2017. [bibtex-key = bruse:hal-01880221] [bibtex-entry]

Jan L. Bruse, Abbas Khushnood, Kristin Mcleod, Giovanni Biglino, Maxime Sermesant, Xavier Pennec, Andrew M. Taylor, Tain-Yen Hsia, and Silvia Schievano. How successful is successful? Aortic arch shape after successful aortic coarctation repair correlates with left ventricular function. Journal of Thoracic and Cardiovascular Surgery, 153(2):418 - 427, February 2017. [bibtex-key = bruse:hal-01387297] [bibtex-entry]

Jan L. Bruse, Maria A. Zuluaga, Abbas Khushnood, Kristin Mcleod, Hopewell N. Ntsinjana, Tain-Yen Hsia, Maxime Sermesant, Xavier Pennec, Andrew M. Taylor, and Silvia Schievano. Detecting clinically meaningful shape clusters in medical image data: metrics analysis for hierarchical clustering applied to healthy and pathological aortic arches. IEEE Transactions on Biomedical Engineering, pp 1 - 13, February 2017. [bibtex-key = bruse:hal-01421202] [bibtex-entry]

Thomas Demarcy, Clair Vandersteen, Nicolas Guevara, Charles Raffaelli, Dan Gnansia, Nicholas Ayache, and Hervé Delingette. Automated analysis of human cochlea shape variability from segmented $\mu$CT images. Computerized Medical Imaging and Graphics, 59(July 2017):1 - 12, 2017. Keyword(s): cochlear implant, human cochlea, anatomy, shape variability, modiolar axis. [bibtex-key = demarcy:hal-01528489] [bibtex-entry]

Loïc Devilliers, Stéphanie Allassonnière, Alain Trouvé, and Xavier Pennec. Inconsistency of template estimation by minimizing of the variance/pre-variance in the quotient space. Entropy, 19(6):article 288, June 2017. Keyword(s): quotient space, Fréchet mean, Hilbert space, deformable model, regularization, template estimation, inconsistency. [bibtex-key = devilliers:hal-01543616] [bibtex-entry]

Loïc Devilliers, Stéphanie Allassonnière, Alain Trouvé, and Xavier Pennec. Template estimation in computational anatomy: Fréchet means in top and quotient spaces are not consistent. SIAM Journal on Imaging Sciences, 10(3):1139-1169, August 2017. Keyword(s): Fréchet mean, Hilbert space, quotient space, Template, manifold, empirical Fréchet mean, inconsistency, group action, consistency bias. [bibtex-key = devilliers:hal-01352707] [bibtex-entry]

Sophie Giffard-Roisin, Thomas Jackson, Lauren Fovargue, Jack Lee, Hervé Delingette, Reza Razavi, Nicholas Ayache, and Maxime Sermesant. Non-Invasive Personalisation of a Cardiac Electrophysiology Model from Body Surface Potential Mapping. IEEE Transactions on Biomedical Engineering, 64(9):2206 - 2218, September 2017. Note: Selected for the TBME highlights, sept. 2017rlhttps://tbme.embs.org/2017/08/24/non-invasive-personalisation-cardiac-electrophysiology-model-body-surface-potential-mapping/. Keyword(s): ECG Imaging, Parameter estimation, In- verse Problem of ECG, Cardiac Electrophysiology, Personalisation. [bibtex-key = giffardroisin:hal-01397393] [bibtex-entry]

Pietro Gori, Olivier Colliot, Linda Marrakchi-Kacem, Yulia Worbe, Cyril Poupon, Andreas Hartmann, Nicholas Ayache, and Stanley Durrleman. A Bayesian Framework for Joint Morphometry of Surface and Curve meshes in Multi-Object Complexes. Medical Image Analysis, 35:458-474, January 2017. Keyword(s): complex, fiber bundle, morphometry, shape, Bayesian, varifolds, atlas, multi - object. [bibtex-key = gori:hal-01359423] [bibtex-entry]

Bishesh Khanal, Nicholas Ayache, and Xavier Pennec. Simulating Longitudinal Brain MRIs with known Volume Changes and Realistic Variations in Image Intensity. Frontiers in Neuroscience, 11(Article 132):18, February 2017. Keyword(s): simulated database, biomechanical simulation, Neurodegeneration, biophysical modelling, synthetic images, synthetic. [bibtex-key = khanal:hal-01348959] [bibtex-entry]

Loïc Le Folgoc, Hervé Delingette, Antonio Criminisi, and Nicholas Ayache. Sparse Bayesian registration of medical images for self-tuning of parameters and spatially adaptive parametrization of displacements. Medical Image Analysis, 36:79 - 97, February 2017. Keyword(s): Cardiac Imaging, Automatic Relevance Determination, Bayesian modelling, Sparse, Registration. [bibtex-key = lefolgoc:hal-01149544] [bibtex-entry]

Marco Lorenzi, Maurizio Filippone, Giovanni Frisoni, Daniel C Alexander, and Sébastien Ourselin. Probabilistic disease progression modeling to characterize diagnostic uncertainty: application to staging and prediction in Alzheimer's disease. NeuroImage, October 2017. [bibtex-key = lorenzi:hal-01617750] [bibtex-entry]

Alex F. Mendelson, Maria A. Zuluaga, Marco Lorenzi, Brian F. Hutton, and Sébastien Ourselin. Selection bias in the reported performances of AD classification pipelines. Neuroimage-Clinical, 14:400 - 416, 2017. Keyword(s): Alzheimer's disease, Classification, Cross validation, Selection bias, Overfitting, ADNI. [bibtex-key = mendelson:hal-01843390] [bibtex-entry]

Nina Miolane. Les maths de l'espace-temps qui décrivent et dépassent le cerveau. Interstices, February 2017. Keyword(s): anatomie cérébrale, anatomie numérique, modélisation mathématique, géométrie riemannienne, cortex visuel, neuroimagerie, image 3D, perception visuelle. [bibtex-key = miolane:hal-01503822] [bibtex-entry]

Nina Miolane, Susan Holmes, and Xavier Pennec. Template Shape Estimation: Correcting an Asymptotic Bias. SIAM Journal on Imaging Sciences, 10(2):808 - 844, 2017. Keyword(s): geometry, quotient space, manifold, template, bias, shape, consistency. [bibtex-key = miolane:hal-01350508] [bibtex-entry]

Roch Molléro, Xavier Pennec, Hervé Delingette, Alan Garny, Nicholas Ayache, and Maxime Sermesant. Multifidelity-CMA: a multifidelity approach for efficient personalisation of 3D cardiac electromechanical models. Biomechanics and Modeling in Mechanobiology, pp 1-16, September 2017. Keyword(s): Finite Element Mechanical modeling, Parameter Estimation, Reduced Model, Cardiac Electromechanical Modeling, Multi-fidelity Modeling. [bibtex-key = mollero:hal-01656008] [bibtex-entry]

Naiara Rodriguez-Florez, Jan L. Bruse, Alessandro Borghi, Herman Vercruysse, Juling Ong, Greg James, Xavier Pennec, David J. Dunaway, Owase Jeelani, and Silvia Schievano. Statistical shape modelling to aid surgical planning: associations between surgical parameters and head shapes following spring-assisted cranioplasty. International Journal of Computer Assisted Radiology and Surgery, pp 1-11, May 2017. [bibtex-key = rodriguezflorez:hal-01540631] [bibtex-entry]

Sergio Sanchez-Martinez, Nicolas Duchateau, Tamas Erdei, Alan Fraser, Bart Bijnens, and Gemma Piella. Characterization of myocardial motion patterns by unsupervised multiple kernel learning. Medical Image Analysis, 35:70-82, 2017. Keyword(s): echocardiography, pattern analysis, multiple kernel learning, Myocardial motion. [bibtex-key = sanchezmartinez:hal-01331550] [bibtex-entry]

Walther Schulze, Zhong Chen, Jatin Relan, Danila Potyagaylo, Martin W. Krueger, Rashed Karim, Manav Sohal, Anoop Shetty, Yingliang Ma, Nicholas Ayache, Maxime Sermesant, Hervé Delingette, Julian Bostock, Reza Razavi, Kawal S. Rhode, and Christopher A. Rinaldi. ECG imaging of ventricular tachycardia: evaluation against simultaneous non-contact mapping and CMR-derived grey zone. Medical and Biological Engineering and Computing, 55(6):979 - 990, June 2017. Keyword(s): Clinical validation, Non-contact mapping, ECG imaging, Ventricular tachycardia, Inverse problem of ECG. [bibtex-key = schulze:hal-01598299] [bibtex-entry]

David Soto-Iglesias, Nicolas Duchateau, Constantine Butakoff, David Andreu, Juan Fernández-Armenta, Bart Bijnens, Antonio Berruezo, Marta Sitges, and Oscar Camara. Quantitative analysis of electro-anatomical maps: application to an experimental model of LBBB/CRT. IEEE Journal of Translational Engineering in Health and Medicine, 5:1900215, 2017. Keyword(s): electro - anatomical mapping system, quantitative pattern analysis, left bundle branch block, subject - specific 2D and 3D data representation, Cardiac resynchronization therapy, lead placement. [bibtex-key = sotoiglesias:hal-01398828] [bibtex-entry]

Zhiyu Tian and Chenyang Xu. Finiteness of fundamental groups. Compositio Mathematica, 153(02):257-273, February 2017. [bibtex-key = tian:hal-01975531] [bibtex-entry]

Stéphanie Marchesseau, Simon Chatelin, and Hervé Delingette. Nonlinear Biomechanical Model of the Liver. In Yohan Payan and Jacques Ohayon, editors, Biomechanics of Living Organs. Hyperelastic Constitutive Laws for Finite Element Modeling, pages 243 - 265. Elsevier, 2017. [bibtex-key = marchesseau:hal-03040194] [bibtex-entry]

Martino Alessandrini, Brecht Heyde, Sandro Queirós, Szymon Cygan, Maria Zontak, Oudom Somphone, Olivier Bernard, Maxime Sermesant, Hervé Delingette, Daniel Barbosa, Mathieu de Craene, Matthew O'Donnell, and Jan d'Hooge. Detailed Evaluation of Five 3D Speckle Tracking Algorithms Using Synthetic Echocardiographic Recordings. IEEE Transactions on Medical Imaging, 35(8):1915-1926, 2016. [bibtex-key = alessandrini:hal-01373083] [bibtex-entry]

Chloé Audigier, Tommaso Mansi, Hervé Delingette, Saikiran Rapaka, Tiziano Passerini, Viorel Mihalef, Marie-Pierre Jolly, Raoul Pop, Michele Diana, Luc Soler, Ali Kamen, Dorin Comaniciu, and Nicholas Ayache. Comprehensive Pre-Clinical Evaluation of a Multi-physics Model of Liver Tumor Radiofrequency Ablation. International Journal of Computer Assisted Radiology and Surgery, December 2016. [bibtex-key = audigier:hal-01423321] [bibtex-entry]

Nicholas Ayache. Medical Imaging Informatics: Towards a Personalized Computational Patient. IMIA Yearbook of Medical Informatics, 25(Suppl. 1):S8-S9, 2016. [bibtex-key = ayache:hal-01320985] [bibtex-entry]

Nicholas Ayache and James Duncan. 20th anniversary of the medical image analysis journal (MedIA). Medical Image Analysis, 33:1-3, October 2016. [bibtex-key = ayache:hal-01353697] [bibtex-entry]

Jan L. Bruse, Kristin Mcleod, Giovanni Biglino, Hopewell N. Ntsinjana, Claudio Capelli, Tain-Yen Hsia, Maxime Sermesant, Xavier Pennec, Andrew M. Taylor, and Silvia Schievano. A statistical shape modelling framework to extract 3D shape biomarkers from medical imaging data: assessing arch morphology of repaired coarctation of the aorta. BMC Medical Imaging, 16(1), May 2016. [bibtex-key = bruse:hal-01335147] [bibtex-entry]

Jan Bruse, Hopewell Ntsinjana, Claudio Capelli, Giovanni Biglino, Kristin Mcleod, Maxime Sermesant, Xavier Pennec, Tain-Yen Hsia, Silvia Schievano, and Andrew Taylor. CMR-based 3D statistical shape modelling reveals left ventricular morphological differences between healthy controls and arterial switch operation survivors. Journal of Cardiovascular Magnetic Resonance, 18(S1), December 2016. [bibtex-key = bruse:hal-03063907] [bibtex-entry]

Rocìo Cabrera-Lozoya, Benjamin Berte, Hubert Cochet, Pierre Jaïs, Nicholas Ayache, and Maxime Sermesant. Image-based Biophysical Simulation of Intracardiac Abnormal Ventricular Electrograms. IEEE Transactions on Biomedical Engineering, PP(99), 2016. Keyword(s): electroanatomical mapping, intracar-diac electrogram modelling, radiofrequency ablation planning, cardiac electrophysiology modelling. [bibtex-key = cabreralozoya:hal-01313615] [bibtex-entry]

Radomir Chabiniok, Vicky Y. Wang, Myrianthi Hadjicharalambous, Liya Asner, Jack Lee, Maxime Sermesant, Ellen Kuhl, Alistair A. Young, Philippe Moireau, Martyn P. Nash, Dominique Chapelle, and David Nordsletten. Multiphysics and multiscale modelling, data-model fusion and integration of organ physiology in the clinic: ventricular cardiac mechanics. Interface Focus, 6(2), 2016. Keyword(s): translational cardiac modelling, patient-specific modelling, heart mechanics, cardiac mechanics, data-model fusion. [bibtex-key = chabiniok:hal-01277684] [bibtex-entry]

Zhong Chen, Rocìo Cabrera-Lozoya, Jatin Relan, Manav Sohal, Anoop Shetty, Rashed Karim, Hervé Delingette, Jaswinder Gill, Kawal Rhode, Nicholas Ayache, Peter Taggart, Christopher Aldo Rinaldi, Maxime Sermesant, and Reza Razavi. Biophysical modelling predicts ventricular tachycardia inducibility and circuit morphology: A combined clinical validation and computer modelling approach. Journal of Cardiovascular Electrophysiology, 27(7):851-860, 2016. Keyword(s): cardiac magnetic resonance imaging, conductivity, APD restitution, computer modelling, Ventricular tachycardia. [bibtex-key = chen:hal-01301426] [bibtex-entry]

Nicolas Cordier, Hervé Delingette, Matthieu Lê, and Nicholas Ayache. Extended Modality Propagation: Image Synthesis of Pathological Cases. IEEE Transactions on Medical Imaging, PP(99), July 2016. Keyword(s): patch-based, multi-atlas, glioma, generative model, medical image simulation, modality synthesis. [bibtex-key = cordier:hal-01343233] [bibtex-entry]

Nicolas Duchateau, Mathieu de Craene, Pascal Allain, Eric Saloux, and Maxime Sermesant. Infarct localization from myocardial deformation: Prediction and uncertainty quantification by regression from a low-dimensional space. IEEE Transactions on Medical Imaging, 35(10):2340-2352, 2016. Keyword(s): biomechanical modeling, delayed-enhancement, pattern recognition & classification, Index Terms-Myocardial infarct, dimensionality reduction, computer-aided diagnosis, ultrasound. [bibtex-key = duchateau:hal-01314767] [bibtex-entry]

Dan Gnansia, Thomas Demarcy, Clair Vandersteen, Charles Raffaelli, Nicolas Guevara, Hervé Delingette, and Nicholas Ayache. Optimal electrode diameter in relation to volume of the cochlea. European Annals of Otorhinolaryngology, Head and Neck Diseases, 133, Supplement 1:S66-S67, June 2016. Keyword(s): Cochlear implant, Electrode-array, Hearing preservation, Soft surgery, Electrode-array design, Image processing, Computed tomography, Inner ear, Anatomy. [bibtex-key = gnansia:hal-01326507] [bibtex-entry]

Pietro Gori, Olivier Colliot, Linda Marrakchi-Kacem, Yulia Worbe, Fabrizio de Vico Fallani, Mario Chavez, Cyril Poupon, Andreas Hartmann, Nicholas Ayache, and Stanley Durrleman. Parsimonious Approximation of Streamline Trajectories in White Matter Fiber Bundles. IEEE Transactions on Medical Imaging, PP(99), 2016. Keyword(s): Index Terms-Diffusion weighted imaging, Brain, Connectivity analysis, Dimensionality reduction, Registration, Tractography, Visualization. [bibtex-key = gori:hal-01346067] [bibtex-entry]

Mehdi Hadj-Hamou, Marco Lorenzi, Nicholas Ayache, and Xavier Pennec. Longitudinal Analysis of Image Time Series with Diffeomorphic Deformations: A Computational Framework Based on Stationary Velocity Fields. Frontiers in Neuroscience, 10(236):18, June 2016. Keyword(s): non-linear registration, deformation-based morphometry, longitudinal study, diffeomorphism parametrized by stationary velocity fields, statistical analysis, reproducible research. [bibtex-key = hadjhamou:hal-01329989] [bibtex-entry]

Bishesh Khanal, Marco Lorenzi, Nicholas Ayache, and Xavier Pennec. A biophysical model of brain deformation to simulate and analyze longitudinal MRIs of patients with Alzheimer's disease. NeuroImage, 134:35-52, July 2016. Keyword(s): longitudinal modeling, simulation of atrophy, longitudinal MRIs simulation, biophysical model, Alzheimer's disease. [bibtex-key = khanal:hal-01305755] [bibtex-entry]

Loïc Le Folgoc, Hervé Delingette, Antonio Criminisi, and Nicholas Ayache. Quantifying Registration Uncertainty with Sparse Bayesian Modelling. IEEE Transactions on Medical Imaging, PP(99), December 2016. Keyword(s): MCMC, Uncertainty Quantification, Registration, Sparse Bayesian Learning, Reversible Jump, Automatic Relevance Determination. [bibtex-key = lefolgoc:hal-01378844] [bibtex-entry]

Matthieu Lê, Hervé Delingette, Jayashree Kalpathy-Cramer, Elizabeth R Gerstner, Tracy Batchelor, Jan Unkelbach, and Nicholas Ayache. MRI Based Bayesian Personalization of a Tumor Growth Model. IEEE Transactions on Medical Imaging, 35(10):2329-2339, April 2016. Keyword(s): bayesian, personalization, Index Terms-tumor growth, glioblastoma, reaction-diffusion, LBM, Monte Carlo. [bibtex-key = le:hal-01324849] [bibtex-entry]

Matthieu Lê, Hervé Delingette, Jayashree Kalpathy-Cramer, Elizabeth R Gerstner, Tracy Batchelor, Jan Unkelbach, and Nicholas Ayache. Personalized Radiotherapy Planning Based on a Computational Tumor Growth Model. IEEE Transactions on Medical Imaging, pp 11, 2016. Keyword(s): Index Terms-Radiotherapy planning, computational tu-, mor growth model, personalization, uncertainty, segmentation, glioblastoma. [bibtex-key = le:hal-01403847] [bibtex-entry]

Matthieu Lê, Jan Unkelbach, Nicholas Ayache, and Hervé Delingette. Sampling Image Segmentations for Uncertainty Quantification. Medical Image Analysis, 34:42-51, December 2016. Note: Accepted for publication to the journal Elsevier Medical Image Analysis. Keyword(s): Gaussian process, brain tumor, uncertainty, radiotherapy planning, Segmentation. [bibtex-key = le:hal-01304646] [bibtex-entry]

Nerea Mangado, Mario Ceresa, Nicolas Duchateau, Hans Martin Kjer, Sergio Vera, Hector Dejea Velardo, Pavel Mistrik, Rasmus R. Paulsen, Jens Fagertun, Jérôme Noailly, Gemma Piella, and Miguel Ángel González Ballester. Automatic model generation framework for computational simulation of cochlear implantation. Annals of Biomedical Engineering, 44(8):2453-2463, 2016. [bibtex-key = mangado:hal-01314765] [bibtex-entry]

Hugo Talbot, Federico Spadoni, Christian Duriez, Maxime Sermesant, Stéphane Cotin, and Hervé Delingette. Interactive Training System for Interventional Electrocardiology Procedures. Medical Image Analysis, 8789:11-19, 2016. Keyword(s): Endovascular Navigation, Training Simulator, Interactive Simulation, Real-Time Electrophysiology. [bibtex-key = talbot:hal-01338346] [bibtex-entry]

Anant S. Vemuri, Stéphane Nicolau, Adrien Sportes, Jacques Marescaux, Luc Soler, and Nicholas Ayache. Inter-Operative Biopsy Site Relocalization in Endoluminal Surgery. IEEE Transactions on Biomedical Engineering, 63(9):1862-1873, September 2016. Keyword(s): video synchronization, Computer assisted intervention, gastro-intestinal (GI) endoscopy, biopsy relocalization, Barrett's Oesophagus, electromagnetic tracking. [bibtex-key = vemuri:hal-01230752] [bibtex-entry]

Antoine Verger, Yalcin Yagdigul, Axel van Der Gucht, Sylvain Poussier, Eric Guedj, Louis Maillard, Grégoire Malandain, Gabriela Hossu, Renaud Fay, Gilles Karcher, and Pierre-Yves Marie. Temporal epilepsy lesions may be detected by the voxel-based quantitative analysis of brain FDG-PET images using an original block-matching normalization software. Annals of Nuclear Medicine, 30(4):272-278, May 2016. Keyword(s): Block-matching algorithm, FDG-PET, Mesial temporal lobe epilepsy, Spatial normalization, Statistical parametric mapping. [bibtex-key = verger:hal-01419250] [bibtex-entry]

Seigo Yamashita, Hubert Cochet, Frédéric Sacher, Saagar Mahida, Benjamin Berte, Darren Hooks, Jean-Marc Sellal, Nora Al Jefairi, Antonio Frontera, Yuki Komatsu, Han S Lim, Sana Amraoui, Arnaud Denis, Nicolas Derval, Maxime Sermesant, François Laurent, Mélèze Hocini, Michel Haïssaguerre, Michel Montaudon, and Pierre Jais. Impact of New Technologies and Approaches for Post--Myocardial Infarction Ventricular Tachycardia Ablation During Long-Term Follow-Up. Circulation. Arrhythmia and electrophysiology, 9(7), July 2016. Keyword(s): Myocardial infarction, Infarction, Heart failure, Catheter ablation, Ventricular tachycardia. [bibtex-key = yamashita:hal-01353372] [bibtex-entry]

Seigo Yamashita, Frédéric Sacher, Saagar Mahida, Benjamin Berte, Han S Lim, Yuki Komatsu, Sana Amraoui, Arnaud Denis, Nicolas Derval, François Laurent, Maxime Sermesant, Michel Montaudon, Mélèze Hocini, Michel Haïssaguerre, Pierre Jais, and Hubert Cochet. Image Integration to Guide Catheter Ablation in Scar-Related Ventricular Tachycardia. Journal of Cardiovascular Electrophysiology, 27(6):699 - 708, June 2016. Keyword(s): Scar-related ventricular tachycardia, Ablation, CMR, MDCT, Imaging. [bibtex-key = yamashita:hal-01936715] [bibtex-entry]

Nicolas Duchateau, Gemma Piella, Alejandro Frangi, and Mathieu de Craene. Learning pathological deviations from a normal pattern of myocardial motion: Added value for CRT studies?. In Guorong Wu, Dinggang Shen, and Mert Sabuncu, editors, Machine learning and medical imaging, 1st Edition, pages 365-382. Elsevier, 2016. [bibtex-key = duchateau:hal-01352464] [bibtex-entry]

Martino Alessandrini, Mathieu de Craene, Olivier Bernard, Sophie Giffard-Roisin, Pascal Allain, Juergen Weese, Eric Saloux, Hervé Delingette, Maxime Sermesant, and Jan d'Hooge. A Pipeline for the Generation of Realistic 3D Synthetic Echocardiographic Sequences: Methodology and Open-access Database.. IEEE Transactions on Medical Imaging, 34(7):1436-1451, 2015. [bibtex-key = alessandrini:hal-01117490] [bibtex-entry]

A Amelot, E Stretton, Hervé Delingette, Nicholas Ayache, S Froelich, and E Mandonnet. Expert-validated CSF segmentation of MNI atlas enhances accuracy of virtual glioma growth patterns. Journal of Neuro-Oncology, 121(2):381-387, January 2015. [bibtex-key = amelot:hal-01081410] [bibtex-entry]

Chloé Audigier, Tommaso Mansi, Hervé Delingette, Saikiran Rapaka, Viorel Mihalef, Daniel Carnegie, Emad Boctor, Michael Choti, Ali Kamen, Nicholas Ayache, and Dorin Comaniciu. Efficient Lattice Boltzmann Solver for Patient-Specific Radiofrequency Ablation of Hepatic Tumors. IEEE Transactions on Medical Imaging, 34(issue 7):p 1576-1589, 2015. Keyword(s): Radio Frequency ablation, Patient-Specific Simulation, Lattice Boltzmann Method, Heat Transfer, Computational Fluid Dynamics, Therapy Planning. [bibtex-key = audigier:hal-01146319] [bibtex-entry]

Mariem Ben Abdallah, Jihene Malek, Ahmad Taher Azar, Philippe Montesinos, Hafedh Belmabrouk, Julio Esclarìn Monreal, and Karl Krissian. Automatic Extraction of Blood Vessels in the Retinal Vascular Tree Using Multiscale Medialness. International Journal of Biomedical Imaging, 2015:1-16, 2015. Keyword(s): Distance transform, similarity measures, contours. [bibtex-key = benabdallah:hal-02112266] [bibtex-entry]

Thomas Benseghir, Grégoire Malandain, and Régis Vaillant. A tree-topology preserving pairing for 3D/2D registration. International Journal of Computer Assisted Radiology and Surgery, 10(6):913-923, 2015. Note: Information Processing in Computer-Assisted Interventions (IPCAI) 2015 Special Issue. Keyword(s): Registration, Tree, Coronary Arteries, X-ray, Navigation, Iterative Closest Curve. [bibtex-key = benseghir:hal-01183573] [bibtex-entry]

David M. Cash, Chris Frost, Leonardo O. Iheme, Devrim Ünay, Melek Kandemir, Jurgen Fripp, Olivier Salvado, Pierrick Bourgeat, Martin Reuter, Bruce Fischl, Marco Lorenzi, Giovanni B. Frisoni, Xavier Pennec, Ronald K. Pierson, Jeffrey L. Gunter, Matthew L. Senjem, Clifford R. Jack, Nicolas Guizard, Vladimir S. Fonov, D. Louis Collins, Marc Modat, Jorge M. Cardoso, Kelvin K. Leung, Hongzhi Wang, Sandhitsu R. Das, Paul A. Yushkevich, Ian B. Malone, Nick C. Fox, Jonathan M. Schott, and Sebastien Ourselin. Assessing atrophy measurement techniques in dementia: Results from the MIRIAD atrophy challenge. NeuroImage, 123:149-164, December 2015. [bibtex-key = cash:hal-01203573] [bibtex-entry]

Hubert Cochet, Arnaud Denis, Yuki Komatsu, Amir S. Jadidi, Tassadit Aït Ali, Frédéric Sacher, Nicolas Derval, Jatin Relan, Maxime Sermesant, Olivier Corneloup, Mélèze Hocini, Michel Haïssaguerre, François Laurent, Michel Montaudon, and Pierre Jaïs. Automated Quantification of Right Ventricular Fat at Contrast-enhanced Cardiac Multidetector CT in Arrhythmogenic Right Ventricular Cardiomyopathy. Radiology, 275(3):683-91, June 2015. [bibtex-key = cochet:hal-01244219] [bibtex-entry]

Nicolas Cordier, Hervé Delingette, and Nicholas Ayache. A patch-based approach for the segmentation of pathologies: Application to glioma labelling. IEEE Transactions on Medical Imaging, 35(4):11, December 2015. Keyword(s): patch-based, multi-atlas, glioma, segmentation. [bibtex-key = cordier:hal-01241480] [bibtex-entry]

Marco Lorenzi, Nicholas Ayache, and Xavier Pennec. Regional flux analysis for discovering and quantifying anatomical changes: An application to the brain morphometry in Alzheimer's disease. NeuroImage, 115:224-234, July 2015. [bibtex-key = lorenzi:hal-01145728] [bibtex-entry]

Marco Lorenzi, Xavier Pennec, Giovanni B. Frisoni, and Nicholas Ayache. Disentangling normal aging from Alzheimer's disease in structural magnetic resonance images. Neurobiology of Aging, 36:S42-S52, January 2015. [bibtex-key = lorenzi:hal-01061017] [bibtex-entry]

Jan Margeta, Antonio Criminisi, Rocio Cabrera Lozoya, Daniel C. Lee, and Nicholas Ayache. Fine-tuned convolutional neural nets for cardiac MRI acquisition plane recognition. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, August 2015. Note: This is an electronic version of an article published inComputer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualizationon 13 August 2015, by Taylor & Francis, DOI: 10.1080/21681163.2015.1061448.Available online at: http://www.tandfonline.com/10.1080/21681163.2015.1061448. Keyword(s): Transfer learning, Fine-tuning, SSFP, Planes of acquisition, Machine learning, Cardiac magnetic resonance, Convolutional neural networks, Magnetic resonance, Cardiac imaging, Deep learning. [bibtex-key = margeta:hal-01162880] [bibtex-entry]

Kristin Mcleod, Maxime Sermesant, Philipp Beerbaum, and Xavier Pennec. Spatio-Temporal Tensor Decomposition of a Polyaffine Motion Model for a Better Analysis of Pathological Left Ventricular Dynamics. IEEE Transactions on Medical Imaging, 34(7):1562-1675, July 2015. Keyword(s): cardiac modelling, atlas, non-rigid image registration, motion tracking, population statistics, tensor decomposition, spatio-temporal alignment, Tetralogy of Fallot. [bibtex-key = mcleod:hal-01205342] [bibtex-entry]

Bjoern H Menze, Koen van Leemput, Danial Lashkari, Tammy Riklin-Raviv, Ezequiel Geremia, Esther Alberts, Philipp Gruber, Susanne Wegener, Marc-André Weber, Gabor Szekely, Nicholas Ayache, and Polina Golland. A generative probabilistic model and discriminative extensions for brain lesion segmentation -- with application to tumor and stroke. IEEE Transactions on Medical Imaging, November 2015. [bibtex-key = menze:hal-01230846] [bibtex-entry]

Nina Miolane and Xavier Pennec. Computing Bi-Invariant Pseudo-Metrics on Lie Groups for Consistent Statistics. Entropy, 17(4):1850-1881, April 2015. [bibtex-key = miolane:hal-01133922] [bibtex-entry]

Catalina Tobon-Gomez, Arjan J. Geers, Jochen Peters, Jürgen Weese, Karen Pinto, Rashed Karim, Mohammed Ammar, Abdelaziz Daoudi, Jan Margeta, Zulma Sandoval, Birgit Stender, Yefeng Zheng, Maria A Zuluaga, Julian Betancur, Nicholas Ayache, Mohammed Amine Chikh, Jean-Louis Dillenseger, Michael B. Kelm, Saïd Mahmoudi, Sébastien Ourselin, Alexander Schlaefer, Tobias Schaeffter, Reza Razavi, and Kawal S. Rhode. Benchmark for Algorithms Segmenting the Left Atrium From 3D CT and MRI Datasets. IEEE Transactions on Medical Imaging, 34(7):1460-1473, July 2015. Keyword(s): Benchmark testing, automatic segmentations, atrial fibrillation ablation guidance, anatomical regions, 3D CT datasets, Left Atrial Segmentation Challenge, left atrial surface, ground truth, image segmentation, LA appendage trunk, LASC, LA segmentation, left atrial anatomy, left atrium, Magnetic Resonance Imaging, Measurement, medical image processing, MRI datasets, multiple input data, physiological models, pulmonary vein proximal sections, region growing approach, Shape, standardisation framework, statistical analysis, statistical models, biomedical MRI, biophysical modelling, blood vessels, cardiovascular disease, cardiovascular system, Computed Tomography, computerised tomography, diseases, Educational institutions, electroanatomical mapping systems, evaluation code, fibrosis quantification. [bibtex-key = tobongomez:hal-01260607] [bibtex-entry]

Clair Vandersteen, Thomas Demarcy, Coralie Roger, Eric Fontas, Charles Raffaelli, Nicholas Ayache, Hervé Delingette, and Nicolas Guevara. Impact of the surgical experience on cochleostomy location: a comparative temporal bone study between endaural and posterior tympanotomy approaches for cochlear implantation. European Archives of Oto-Rhino-Laryngology, pp 1-7, 2015. Keyword(s): Cochlear implantation, Cochleostomy, Minimally invasive surgery, Endaural approach, Learning skills, Surgery resident, Compétences d'apprentissage, Voie endaurale, Chirurgie mini-invasive, Cochléostomie, Implantation cochléaire, Interne en chirurgie. [bibtex-key = vandersteen:hal-01238195] [bibtex-entry]

Ken C.L. Wong, Maxime Sermesant, Kawal Rhode, Matthew Ginks, C. Aldo Rinaldi, Reza Razavi, Hervé Delingette, and Nicholas Ayache. Velocity-based cardiac contractility personalization from images using derivative-free optimization. Journal of the mechanical behavior of biomedical materials, 43:35-52, March 2015. Keyword(s): parameter estimation, model personalization, derivative-free optimization, Cardiac contractility, cardiac electromechanical model. [bibtex-key = wong:hal-01095725] [bibtex-entry]

Hervé Delingette and Nicholas Ayache. Building Patient-Specific Physical and Physiological Computational Models from Medical Images. In Paragios, Nikos, Duncan, Jim, Ayache, and Nicholas, editors, Handbook of Biomedical Imaging: Methodologies and Clinical Research, pages 169-182. Springer US, 2015. [bibtex-key = delingette:hal-01250442] [bibtex-entry]

Xavier Pennec and Pierre Fillard. Statistical Computing on Non-Linear Spaces for Computational Anatomy. In Paragios, Nikos, Duncan, Jim, Ayache, and Nicholas, editors, Handbook of Biomedical Imaging: Methodologies and Clinical Research, pages 147-168. Springer, 2015. [bibtex-key = pennec:inria-00616201] [bibtex-entry]

Romain Guibert, Kristin Mcleod, Alfonso Caiazzo, Tommaso Mansi, Miguel Angel Fernández, Maxime Sermesant, Xavier Pennec, Irene Vignon-Clementel, Younes Boudjemline, and Jean-Frédéric Gerbeau. Group-wise Construction of Reduced Models for Understanding and Characterization of Pulmonary Blood Flows from Medical Images. Medical Image Analysis, 18(1):63-82, 2014. Keyword(s): Computational fluid dynamics, Pulmonary artery, Tetralogy of Fallot, Atlas construction, Proper orthogonal decomposition. [bibtex-key = guibert:hal-00874545] [bibtex-entry]

Antoine Iannessi, Pierre Yves Marcy, Olivier Clatz, Nicholas Ayache, and Pierre Fillard. Touchless User Interface for Intraoperative Image Control: Almost There. Radiographics, 34(4), July 2014. [bibtex-key = iannessi:hal-01364012] [bibtex-entry]

A Iannessi, P.-y Marcy, O Clatz, P Fillard, and N Ayache. Touchless intra-operative display for interventional radiologist. Diagnostic and Interventional Imaging, 2014. Keyword(s): User-computer interface, Gesture, CT-scan, Interventional radiology, Sterility. [bibtex-key = iannessi:hal-01364021] [bibtex-entry]

Y. Komatsu, A. Jadidi, F. Sacher, A. Denis, M. Daly, N. Derval, A. Shah, H. Lehrmann, C.-I. Park, R. Weber, T. Arentz, G. Pache, Maxime Sermesant, Nicholas Ayache, J. Relan, M. Montaudon, F. Laurent, M. Hocini, M. Haissaguerre, P. Jais, and Hubert Cochet. Relationship Between MDCT-Imaged Myocardial Fat and Ventricular Tachycardia Substrate in Arrhythmogenic Right Ventricular Cardiomyopathy. Journal of the American Heart Association, 3(4):10, 2014. [bibtex-key = komatsu:hal-01095772] [bibtex-entry]

Herve Lombaert, Leo Grady, Xavier Pennec, Nicholas Ayache, and Farida Cheriet. Spectral Log-Demons: Diffeomorphic Image Registration with Very Large Deformations. International Journal of Computer Vision, 107(3):254-271, May 2014. [bibtex-key = lombaert:hal-00979616] [bibtex-entry]

Bjoern Menze, Andras Jakab, Stefan Bauer, Jayashree Kalpathy-Cramer, Keyvan Farahani, Justin Kirby, Yuliya Burren, Nicole Porz, Johannes Slotboom, Roland Wiest, Levente Lanczi, Elisabeth Gerstner, Marc-Andre Weber, Tal Arbel, Brian Avants, Nicholas Ayache, Patricia Buendia, Louis Collins, Nicolas Cordier, Jason Corso, Antonio Criminisi, Tilak Das, Hervé Delingette, Cagatay Demiralp, Christopher Durst, Michel Dojat, Senan Doyle, Joana Festa, Florence Forbes, Ezequiel Geremia, Ben Glocker, Polina Golland, Xiaotao Guo, Andac Hamamci, Khan Iftekharuddin, Raj Jena, Nigel John, Ender Konukoglu, Danial Lashkari, Jose Antonio Mariz, Raphael Meier, Sergio Pereira, Doina Precup, S. J. Price, Tammy Riklin-Raviv, Syed Reza, Michael Ryan, Lawrence Schwartz, Hoo-Chang Shin, Jamie Shotton, Carlos Silva, Nuno Sousa, Nagesh Subbanna, Gabor Szekely, Thomas Taylor, Owen Thomas, Nicholas Tustison, Gozde Unal, Flor Vasseur, Max Wintermark, Dong Hye Ye, Liang Zhao, Binsheng Zhao, Darko Zikic, Marcel Prastawa, Mauricio Reyes, and Koen van Leemput. The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS). IEEE Transactions on Medical Imaging, 34(10):1993-2024, October 2014. [bibtex-key = menze:hal-00935640] [bibtex-entry]

Antonio Porras, Martino Alessandrini, Mathieu de Craene, Nicolas Duchateau, Marta Sitges, Bart Bijnens, Hervé Delingette, Maxime Sermesant, Jan d'Hooge, Alejandro Frangi, and Gemma Piella. Improved Myocardial Motion Estimation Combining Tissue Doppler and B-Mode Echocardiographic Images. IEEE Transactions on Medical Imaging, 33(11):2098 - 2106, June 2014. Keyword(s): Echocardiography, free form deformation (FFD), image registration, motion estimation. [bibtex-key = porras:hal-01095151] [bibtex-entry]

Adityo Prakosa, Maxime Sermesant, Pascal Allain, Nicolas Villain, Christopher Aldo Rinaldi, Kawal Rhode, Reza Razavi, Hervé Delingette, and Nicholas Ayache. Cardiac Electrophysiological Activation Pattern Estimation from Images using a Patient-Specific Database of Synthetic Image Sequences. IEEE Transactions on Biomedical Engineering, 61(2):235 - 245, 2014. [bibtex-key = prakosa:hal-00858891] [bibtex-entry]

Avan Suinesiaputra, Brett Cowan, Ahmed O. Al-Agamy, Mustafa A. Alattar, Nicholas Ayache, Ahmed S. Fahmy, Ayman M. Khalifa, Pau Medrano-Gracia, Marie-Pierre Jolly, Alan H. Kadish, Daniel C. Lee, Jan Margeta, Simon K. Warfield, and Alistair Young. A Collaborative Resource to Build Consensus for Automated Left Ventricular Segmentation of Cardiac MR Images. Medical Image Analysis, 18(1):50-62, 2014. [bibtex-key = suinesiaputra:hal-00857223] [bibtex-entry]

Yuliya Tarabalka, Guillaume Charpiat, Ludovic Brucker, and Bjoern Menze. Spatio-Temporal Video Segmentation with Shape Growth or Shrinkage Constraint. IEEE Transactions on Image Processing, 23(9):3829-3840, September 2014. [bibtex-key = tarabalka:hal-01052543] [bibtex-entry]

A. Frangi, Denis Friboulet, Nicholas Ayache, H. Delingette, T. Glatard, C. Hoogendoorn, L. Humbert, K. Lekadir, I. Larrabide, Y. Martelli, F. Peyrin, X. Planes, Maxime Sermesant, M.C. Villa-Uriol, T. Whitmarsh, and D. Atkinson. Image Based Modelling. In Peter Coveney, Vanessa Diaz, Peter Hunter, and Marco Viceconti, editors, Computational Biomedicine, pages 59 - 82. Oxford University Press, 2014. [bibtex-key = frangi:hal-01016455] [bibtex-entry]

Marco Lorenzi and Xavier Pennec. Discrete Ladders for Parallel Transport in Transformation Groups with an Affine Connection Structure. In Frank Nielsen, editor, Geometric Theory of Information, Signals and Communication Technology, pages 243-271. Springer, 2014. [bibtex-key = lorenzi:hal-00933229] [bibtex-entry]

Marine Breuilly, Grégoire Malandain, Julien Guglielmi, Robert Marsault, Thierry Pourcher, Philippe R. Franken, and Jacques Darcourt. Amplitude-based data selection for optimal retrospective reconstruction in micro-SPECT. Physics in Medicine and Biology, 58(8):2657-2674, April 2013. [bibtex-key = breuilly:hal-00799381] [bibtex-entry]

François Chung and Hervé Delingette. Regional Appearance Modeling based on the Clustering of Intensity Profiles. Computer Vision and Image Understanding, 117(6):705-717, 2013. [bibtex-key = chung:hal-00813880] [bibtex-entry]

Hubert Cochet, Y. Komatsu, F. Sacher, A. Jadidi, D. Scherr, M. Riffaud, N. Derval, A. Shah, L. Roten, P. Pascale, Jatin Relan, Maxime Sermesant, Nicholas Ayache, M. Montaudon, F. Laurent, M. Hocini, M. Haïssaguerre, and Pierre Jaïs. Integration of Merged Delayed-Enhanced Magnetic Resonance Imaging and Multi-Detector Computed Tomography for the Guidance of Ventricular Tachycardia Ablation: A Pilot Study. Journal of Cardiovascular Electrophysiology, 24(4):419-426, April 2013. [bibtex-key = cochet:hal-00813820] [bibtex-entry]

Stanley Durrleman, Xavier Pennec, Alain Trouvé, José Braga, Guido Gerig, and Nicholas Ayache. Toward a Comprehensive Framework for the Spatiotemporal Statistical Analysis of Longitudinal Shape Data. International Journal of Computer Vision, 103(1):22-59, May 2013. [bibtex-key = durrleman:hal-00813825] [bibtex-entry]

Alejandro F. Frangi, D. Rod Hose, Peter J. Hunter, Nicholas Ayache, and Dana Brooks. Guest Editorial Special Issue on Medical Imaging and Image Computing in Computational Physiology. IEEE Transactions on Medical Imaging, 32(1):1-7, January 2013. [bibtex-key = frangi:hal-01355239] [bibtex-entry]

Amir S. Jadidi, Hubert Cochet, Ashok J. Shah, Steven J. Kim, Edward Duncan, Shinsuke Miyazaki, Maxime Sermesant, Heiko Lehrmann, Matthieu Lederlin, Nick Linton, Andrei Forclaz, Isabelle Nault, Lena Rivard, Matthew Wright, Xingpeng Liu, Daniel Scherr, Stephen B. Wilton, Laurent Roten, Patrizio Pascale, Nicolas Derval, Frédéric Sacher, Sebastian Knecht, Cornelius Keyl, Mélèze Hocini, Michel Montaudon, François Laurent, Michel Haïssaguerre, and Pierre Jaïs. Inverse relationship between fractionated electrograms and atrial fibrosis in persistent atrial fibrillation: combined magnetic resonance imaging and high-density mapping. Journal of the American College of Cardiology, 62(9):802-812, 2013. [bibtex-key = jadidi:hal-00855926] [bibtex-entry]

Yuki Komatsu, Hubert Cochet, Amir Jadidi, Frédéric Sacher, Ashok Shah, Nicolas Derval, Daniel Scherr, Patrizio Pascale, Laurent Roten, Arnaud Denis, Khaled Ramoul, Shinsuke Miyazaki, Matthew Daly, Matthieu Riffaud, Maxime Sermesant, Jatin Relan, Nicholas Ayache, Steven Kim, Michel Montaudon, François Laurent, Mélèze Hocini, Michel Haïssaguerre, and Pierre Jaïs. Regional myocardial wall thinning at multidetector computed tomography correlates to arrhythmogenic substrate in postinfarction ventricular tachycardia: assessment of structural and electrical substrate. Circulation. Arrhythmia and electrophysiology, 6(2):342-350, 2013. [bibtex-key = komatsu:hal-00855932] [bibtex-entry]

Benedetta Leonardi, Andrew Taylor, Tommaso Mansi, Ingmar Voigt, Maxime Sermesant, Xavier Pennec, Nicholas Ayache, Younes Boudjemline, and Giacomo Pongiglione. Computational modelling of the right ventricle in repaired tetralogy of Fallot: can it provide insight into patient treatment?. European Heart Journal - Cardiovascular Imaging, 14(4):381-6, April 2013. [bibtex-key = leonardi:hal-00813831] [bibtex-entry]

Marco Lorenzi, Nicholas Ayache, Giovanni B. Frisoni, and Xavier Pennec. LCC-Demons: a robust and accurate symmetric diffeomorphic registration algorithm. NeuroImage, 81(1):470-483, 2013. [bibtex-key = lorenzi:hal-00819895] [bibtex-entry]

Marco Lorenzi and Xavier Pennec. Efficient Parallel Transport of Deformations in Time Series of Images: from Schild's to Pole Ladder. Journal of Mathematical Imaging and Vision, 50(1-2):5-17, October 2013. [bibtex-key = lorenzi:hal-00870489] [bibtex-entry]

Marco Lorenzi and Xavier Pennec. Geodesics, Parallel Transport & One-parameter Subgroups for Diffeomorphic Image Registration. International Journal of Computer Vision, 105(2):111-127, November 2013. [bibtex-key = lorenzi:hal-00813835] [bibtex-entry]

Stéphanie Marchesseau, Hervé Delingette, Maxime Sermesant, Rocio Cabrera Lozoya, Catalina Tobon-Gomez, Philippe Moireau, Rosa Maria Figueras I Ventura, Karim Lekadir, Alfredo Hernandez, Mireille Garreau, Erwan Donal, Christophe Leclercq, Simon G. Duckett, Kawal Rhode, Christopher Aldo Rinaldi, Alejandro F. Frangi, Reza Razavi, Dominique Chapelle, and Nicholas Ayache. Personalization of a Cardiac Electromechanical Model using Reduced Order Unscented Kalman Filtering from Regional Volumes. Medical Image Analysis, 17(7):816-829, May 2013. [bibtex-key = marchesseau:hal-00819806] [bibtex-entry]

Stéphanie Marchesseau, Hervé Delingette, Maxime Sermesant, Michel Sorine, Kawal Rhode, Simon G. Duckett, Christopher Aldo Rinaldi, Reza Razavi, and Nicholas Ayache. Preliminary Specificity Study of the Bestel-Clément-Sorine Electromechanical Model of the Heart using Parameter Calibration from Medical Images. Journal of the mechanical behavior of biomedical materials, 20:259-271, 2013. [bibtex-key = marchesseau:hal-00813849] [bibtex-entry]

Bjoern Menze, Georg Langs, Zhuowen Tu, and Antonio Criminisi. Whole-body anatomy localization via classification and regression forests. Medical Image Analysis, 17(8):1282, December 2013. [bibtex-key = menze:hal-00917886] [bibtex-entry]

Katja E. Odening, Bernd A. Jung, Corinna N. Lang, Rocio Cabrera Lozoya, David Ziupa, Marius Menza, Jatin Relan, Gerlind Franke, Stefanie Perez Feliz, Gideon Koren, Manfred Zehender, Christoph Bode, Michael Brunner, Maxime Sermesant, and Daniela Föll. Spatial Correlation of Action Potential Duration and Diastolic Dysfunction in Transgenic and Drug-induced LQT2 Rabbits. Heart Rhythm, 10(10):1533-1541, 2013. Note: Focus Issue: Sudden Cardiac Death. [bibtex-key = odening:hal-00855929] [bibtex-entry]

Xavier Pennec, Sarang Joshi, and Mads Nielsen. Mathematical Methods for Medical Imaging. International Journal of Computer Vision, 105(2):109-110, August 2013. [bibtex-key = pennec:hal-00858908] [bibtex-entry]

A. Prakosa, Maxime Sermesant, H. Delingette, S. Marchesseau, E. Saloux, Pascal Allain, N. Villain, and Nicholas Ayache. Generation of Synthetic but Visually Realistic Time Series of Cardiac Images Combining a Biophysical Model and Clinical Images. IEEE Transactions on Medical Imaging, 32(1):99-109, January 2013. [bibtex-key = prakosa:hal-00813861] [bibtex-entry]

Islem Rekik, Stéphanie Allassonnière, Olivier Clatz, Ezequiel Geremia, Erin Stretton, Hervé Delingette, and Nicholas Ayache. Tumor Growth Parameters Estimation and Source Localization From a Unique Time Point: Application to Low-grade Gliomas. Computer Vision and Image Understanding, 117(3):238-249, 2013. [bibtex-key = rekik:hal-00813881] [bibtex-entry]

Stefan Sommer, François Lauze, Mads Nielsen, and Xavier Pennec. Sparse Multi-Scale Diffeomorphic Registration: the Kernel Bundle Framework. Journal of Mathematical Imaging and Vision, 46(3):292-308, 2013. [bibtex-key = sommer:hal-00813868] [bibtex-entry]

Stefan Sommer, Mads Nielsen, Sune Darkner, and Xavier Pennec. Higher-order momentum distributions and locally affine LDDMM registration. SIAM Journal on Imaging Sciences, 6(1):341-367, February 2013. [bibtex-key = sommer:hal-00813869] [bibtex-entry]

Hugo Talbot, Stéphanie Marchesseau, Christian Duriez, Maxime Sermesant, Stéphane Cotin, and Hervé Delingette. Towards an Interactive Electromechanical Model of the Heart. Interface Focus, 3(2):4, April 2013. Keyword(s): electrophysiology cardiac mechanics training simulation interactive SOFA framework. [bibtex-key = talbot:hal-00797354] [bibtex-entry]

Catalina Tobon-Gomez, Nicolas Duchateau, Rafael Sebastian, Stéphanie Marchesseau, Oscar Camara, Erwan Donal, Mathieu de Craene, Ali Pashaei, Jatin Relan, Martin Steghofer, Pablo Lamata, Hervé Delingette, Simon G. Duckett, Mireille Garreau, Alfredo Hernandez, Kawal S. Rhode, Maxime Sermesant, Nicholas Ayache, Christophe Leclercq, Reza Razavi, Nicolas P. Smith, and Alejandro F. Frangi. Understanding the mechanisms amenable to CRT response: from pre-operative multimodal image data to patient-specific computational models. Medical and Biological Engineering and Computing, pp 1-16, 2013. [bibtex-key = tobongomez:hal-00840037] [bibtex-entry]

Catalina Tobon-Gomez, Mathieu de Craene, Kristin Mcleod, Lennart Tautz, Wenzhe Shi, Anja Hennemuth, Adityo Prakosa, Hengui Wang, Gerald Carr-White, Sergio Kapetanakis, Albert Lutz, Vernon Rasche, Tobias Schaeffter, Constantin Butakoff, Oskar Friman, Tommaso Mansi, Maxime Sermesant, Xiahai Zhuang, Sébastien Ourselin, Hans Otto Peitgen, Xavier Pennec, Reza Razavi, Daniel Rueckert, Alejandro F. Frangi, and Kawal Rhode. Benchmarking framework for myocardial tracking and deformation algorithms: an open access database. Medical Image Analysis, 17(6):632-648, 2013. [bibtex-key = tobongomez:hal-00855928] [bibtex-entry]

Nicolas Toussaint, Christian T. Stoeck, Tobias Schaeffter, Sebastian Kozerke, Maxime Sermesant, and Philip G. Batchelor. In vivo human cardiac fibre architecture estimation using shape-based diffusion tensor processing. Medical Image Analysis, 2013. Note: In press. Keyword(s): Diffusion tensor imaging. [bibtex-key = toussaint:hal-00845062] [bibtex-entry]

Jan Unkelbach, Bjoern Menze, Ender Konukoglu, Florian Dittmann, Nicholas Ayache, and Helen Shi. Radiotherapy planning for glioblastoma based on a tumor growth model: implications for spatial dose redistribution. Physics in Medicine and Biology, December 2013. [bibtex-key = unkelbach:hal-00917846] [bibtex-entry]

Jan Unkelbach, Bjoern Menze, Ender Konukoglu, Florian Dittmann, Matthieu Le, Nicholas Ayache, and Helen Shi. Radiotherapy planning for glioblastoma based on a tumor growth model: improving target volume delineation. Physics in Medicine and Biology, December 2013. [bibtex-key = unkelbach:hal-00917869] [bibtex-entry]

Irina Vidal-Migallón, Olivier Commowick, Xavier Pennec, Julien Dauguet, and Tom Vercauteren. GPU & CPU implementation of Young - Van Vliet's Recursive Gaussian Smoothing Filter. Insight Journal, pp 16, July 2013. Note: Open peer-review journal. Open code / open data. Keyword(s): GPU, OpenCL, Recursive Gaussian Smoothing. [bibtex-key = vidalmigallon:inserm-00855958] [bibtex-entry]

Jürgen Weese, Nicholas Ayache, and Nicolas P. Smith. Personalized Cardiac Modeling and Simulations in euHeart. Medical and Biological Engineering and Computing, 2013. Note: Editorial. [bibtex-key = weese:hal-00851239] [bibtex-entry]

Mathieu de Craene, Stéphanie Marchesseau, Brecht Heyde, Hang Gao, M. Alessandrini, Olivier Bernard, Gemma Piella, Antonio Porras, Lennart Tautz, Anja Hennemuth, Adityo Prakosa, Hervé Liebgott, Oudom Somphone, Pascal Allain, S. Makram Ebeid, Hervé Delingette, Maxime Sermesant, Jan d'Hooge, and Eric Saloux. 3D strain assessment in ultrasound (straus): A synthetic comparison of five tracking methodologies. IEEE Transactions on Medical Imaging, 32(9):1632 - 1646, 2013. [bibtex-key = decraene:hal-00840039] [bibtex-entry]

Ezequiel Geremia, Darko Zikic, Olivier Clatz, Bjoern H. Menze, Ben Glocker, Ender Konukoglu, Jamie Shotton, O. M. Thomas, S. J. Price, Tilak Das, Raj Jena, Nicholas Ayache, and Antonio Criminisi. Classification Forests for Semantic Segmentation of Brain Lesions in Multi-channel MRI. In Criminisi, Antonio, Shotton, and J., editors, Decision Forests for Computer Vision and Medical Image Analysis, Advances in Computer Vision and Pattern Recognition, pages 245-260. Springer London, 2013. [bibtex-key = geremia:hal-00931809] [bibtex-entry]

Kristin Mcleod, Tommaso Mansi, Maxime Sermesant, Giacomo Pongiglione, and Xavier Pennec. Statistical Shape Analysis of Surfaces in Medical Images Applied to the Tetralogy of Fallot Heart. In Frederic Cazals and Pierre Kornprobst, editors, Modeling in Computational Biology and Biomedicine, Lectures Notes in Mathematical and Computational Biology, pages 165-191. Springer, 2013. [bibtex-key = mcleod:hal-00813850] [bibtex-entry]

Barbara André, Tom Vercauteren, Anna M. Buchner, Murli Krishna, Nicholas Ayache, and Michael B. Wallace. Software for Automated Classification of probe-based Confocal Laser Endomicroscopy Videos of Colorectal Polyps. World Journal of Gastroenterology, October 2012. [bibtex-key = andre:wjg:2012] [bibtex-entry]

Barbara André, Tom Vercauteren, Anna M. Buchner, Michael B. Wallace, and Nicholas Ayache. Learning Semantic and Visual Similarity for Endomicroscopy Video Retrieval. IEEE Transactions on Medical Imaging, 31(6):1276-1288, June 2012. [bibtex-key = andre:tmi:2012] [bibtex-entry]

R. Blanc, Christof Seiler, G. Székely, L. Nolte, and Mauricio Reyes. Statistical Model Based Shape Prediction from a Combination of Direct Observations and Various Surrogates. Medical Image Analysis (MedIA), 16(6):1156-1166, 2012. [bibtex-key = BlancSeiler:MEDIA:2012] [bibtex-entry]

H. Cochet, Y. Komatsu, F. Sacher, A. Jadidi, D. Scherr, M. Riffaud, N. Derval, A. Shah, L. Roten, P. Pascale, Jatin Relan, Maxime Sermesant, Nicholas Ayache, M. Montaudon, F. Laurent, M. Hocini, M. Haïssaguerre, and P. Jaïs. Integration of Merged Delayed-Enhanced Magnetic Resonance Imaging and Multi-Detector Computed Tomography for the Guidance of Ventricular Tachycardia Ablation: A Pilot Study. Journal of Cardiovascular Electrophysiology, 2012. ISSN: 1540-8167. Keyword(s): ventricular tachycardia, MRI, computed tomography, catheter ablation, myocardial infarction, cardiomyopathy. [bibtex-key = JCE:JCE12052] [bibtex-entry]

Hervé Delingette, F. Billet, Ken C. L. Wong, Maxime Sermesant, Kawal Rhode, M. Ginks, C. Aldo Rinaldi, Reza Razavi, and Nicholas Ayache. Personalization of Cardiac Motion and Contractility From Images Using Variational Data Assimilation. Biomedical Engineering, IEEE Transactions on, 59(1):20 -24, jan. 2012. ISSN: 0018-9294. [bibtex-key = Delingette:TBME:2012] [bibtex-entry]

Stanley Durrleman, Xavier Pennec, Alain Trouvé, Nicholas Ayache, and José Braga. Comparison of the endocranial ontogenies between chimpanzees and bonobos via temporal regression and spatiotemporal registration. Journal of Human Evolution, 62(1):74 - 88, 2012. ISSN: 0047-2484. Keyword(s): Endocranium. [bibtex-key = Durrleman:JHE:12] [bibtex-entry]

B. Michael Kelm, Frederik O. Kaster, A. Henning, Marc-André Weber, P. Bachert, P. Boesiger, Fred A. Hamprecht, and Bjoern H. Menze. Using spatial prior knowledge in the spectral fitting of MRS images. NMR in Biomedicine, 25(1):1-13, 2012. HAL ID: inria-00616193. [bibtex-key = kelm:inria-00616193] [bibtex-entry]

Hervé Lombaert, Jean-Marc Peyrat, Pierre Croisille, Stanislas Rapacchi, Laurent Fanton, Farida Cheriet, Patrick Clarysse, Isabelle Magnin, Hervé Delingette, and Nicholas Ayache. Human Atlas of the Cardiac Fiber Architecture: Study on a Healthy Population. IEEE Trans. on Medical Imaging, 31(7):1436-1447, 2012. [bibtex-key = Lombaert:TMI:12] [bibtex-entry]

Stéphanie Marchesseau, Hervé Delingette, Maxime Sermesant, and Nicholas Ayache. Fast Parameter Calibration of a Cardiac Electromechanical Model from Medical Images based on the Unscented Transform. Biomechanics and Modeling in Mechanobiology, 2012. [bibtex-key = Marchesseau:BMMB:2012] [bibtex-entry]

Christophe Person, Valérie Louis-Dorr, Sylvain Poussier, Olivier Commowick, Grégoire Malandain, Louis Maillard, Didier Wolf, Nicolas Gilet, Véronique Roch, Gilles Karcher, and Pierre-Yves Marie. Voxel-based quantitative analysis of brain images from F-18 Fluorodeoxyglucose Positron Emission Tomography with a Block-Matching algorithm for spatial normalization. Clinical Nuclear Medicine, 37(3):268-273, 2012. HAL ID: hal-00651731. [bibtex-key = person:hal-00651731] [bibtex-entry]

M. Pop, Maxime Sermesant, G. Liu, Jatin Relan, Tommaso Mansi, A. Soong, Jean-Marc Peyrat, M.V. Truong, P. Fefer, Elliot R. McVeigh, Hervé Delingette, A.J. Dick, Nicholas Ayache, and G.A Wright. Construction of 3D MR image-based computer models of pathologic hearts, augmented with histology and optical fluorescence imaging to characterize action potential propagation. Medical Image Analysis, 16(2):505-523, February 2012. [bibtex-key = Pop:2012:MedIA] [bibtex-entry]

L. Ritacco, Christof Seiler, G. Farfalli, L. Nolte, Mauricio Reyes, D. Muscolo, and L. Tinao. Validity of an Automatic Measure Protocol in Distal Femur for Allograft Selection from a Three-Dimensional Virtual Bone Bank System. Cell and Tissue Banking, 2012. Note: To appear. [bibtex-key = RitaccoSeiler:CTB:2012] [bibtex-entry]

Roberta Rossi, Michela Pievani, Marco Lorenzi, Marina Boccardi, Rossella Beneduce, Stefano Bignotti, Genoveffa Borsci, Maria Cotelli, Panteleimon Giannakopoulos, Laura R. Magni, Luciana Rillosi, Sandra Rosini, Giuseppe Rossi, and Giovanni B. Frisoni. Structural brain features of borderline personality and bipolar disorders. Psychiatry Research: Neuroimaging, 12:S0925-4927, 2012. [bibtex-key = Lorenzi:PSY:2012] [bibtex-entry]

Christof Seiler, A. Gazdhar, Mauricio Reyes, L.M. Benneker, T. Geiser, K.A. Siebenrock, and B. Gantenbein-Ritter. Time-Lapse Microscopy and Classification of 2D Human Mesenchymal Stem Cells Based on Cell Shape Picks Up Myogenic from Osteogenic and Adipogenic Differentiation. Journal of Tissue Engineering and Regenerative Medicine, 2012. Note: To appear. [bibtex-key = Seiler:TERM:2012] [bibtex-entry]

Christof Seiler, Xavier Pennec, and Mauricio Reyes. Capturing the Multiscale Anatomical Shape Variability with Polyaffine Transformation Trees. Medical Image Analysis (MedIA), 16(7):1371-1384, 2012. [bibtex-key = Seiler:MEDIA:2012] [bibtex-entry]

Maxime Sermesant, R. Chabiniok, P. Chinchapatnam, Tommaso Mansi, F. Billet, P. Moireau, Jean-Marc Peyrat, Ken C. L. Wong, Jatin Relan, Kawal Rhode, M. Ginks, P. Lambiase, Hervé Delingette, M. Sorine, C. Aldo Rinaldi, D. Chapelle, Reza Razavi, and Nicholas Ayache. Patient-specific electromechanical models of the heart for the prediction of pacing acute effects in CRT: A preliminary clinical validation. Medical Image Analysis, 16(1):201-215, 2012. [bibtex-key = Sermesant:MEDIA:2012] [bibtex-entry]

Juliette Thariat, Pierre-Yves Marcy, A. Lacout, Liliane Ramus, T. Girinsky, Y. Pointreau, and Grégoire Malandain. Radiotherapy and radiology: joint efforts for modern radiation planning and practice. Diagn Interv Imaging, 93(5):342-50, May 2012.

Abstract:

With new irradiation techniques, the dose can be better matched to the contours of the tumour. The corollary is that greater precision is required. Recent intercomparison studies of treatment plans have emphasized the need to harmonise contouring practices. More of a consensus approach is based on using adaptive imaging modalities, expert group recommendations and automatic segmentation atlases, on harmonisation of dosimetric decisions through employing exhaustive nomograms for organs at risk, and on indexes for choosing optimal treatment plans. On another level, quality assurance and data pooling programmes have been set up, making use of DICOM-RT data transfer (image networks). The combination of several irradiation techniques (for example, intensity-modulated conformal radiation therapy plus CyberKnife((R)) boost and re-irradiation), making it possible to irradiate tumours better, requires the cumulative doses to be recorded by dose summation software. Real awareness has been achieved in recent years as regards improving the quality of treatment, pooling data and harmonising practices.

[bibtex-key = thariat:DII:2012] [bibtex-entry]

Juliette Thariat, Liliane Ramus, Philippe Maingon, Guillaume Odin, Vincent Gregoire, Vincent Darcourt, Nicolas Guevara, Marie-Helene Orlanducci, Serge Marcie, Gilles Poissonnet, Pierre-Yves Marcy, Alex Bozec, Olivier Dassonville, Laurent Castillo, Francois Demard, Jose Santini, and Grégoire Malandain. DENTALMAPS: Automatic Dental Delineation for Radiotherapy Planning in Head-and-neck Cancer. Int J Radiat Oncol Biol Phys, 82(5):1858-65, April 2012.

Abstract:

PURPOSE: To propose an automatic atlas-based segmentation framework of the dental structures, called Dentalmaps, and to assess its accuracy and relevance to guide dental care in the context of intensity-modulated radiotherapy. METHODS AND MATERIALS: A multi-atlas-based segmentation, less sensitive to artifacts than previously published head-and-neck segmentation methods, was used. The manual segmentations of a 21-patient database were first deformed onto the query using nonlinear registrations with the training images and then fused to estimate the consensus segmentation of the query. RESULTS: The framework was evaluated with a leave-one-out protocol. The maximum doses estimated using manual contours were considered as ground truth and compared with the maximum doses estimated using automatic contours. The dose estimation error was within 2-Gy accuracy in 75\% of cases (with a median of 0.9 Gy), whereas it was within 2-Gy accuracy in 30\% of cases only with the visual estimation method without any contour, which is the routine practice procedure. CONCLUSIONS: Dose estimates using this framework were more accurate than visual estimates without dental contour. Dentalmaps represents a useful documentation and communication tool between radiation oncologists and dentists in routine practice. Prospective multicenter assessment is underway on patients extrinsic to the database.

[bibtex-key = thariat-ramus:ijrobp:2012] [bibtex-entry]

Florian Vichot, H. Cochet, Benoit Bleuzé, Nicolas Toussaint, P. Jaïs, and Maxime Sermesant. Cardiac Interventional Guidance using Multimodal Data Processing and Visualisation: medInria as an Interoperability Platform. Midas Journal, 2012.

Keyword(s): Standards, Data Formats, Registration, Visualisation. Abstract:

medInria is a free medical imaging software developed at Inria, which aims at providing clinicians with state-of-the-art algorithms dedicated to medical image processing and visualization. Efforts have been made to simplify the user interface, while keeping high-level algorithms. In this particular article, we will concentrate on its use in preoperative preparation for cardiac interventions, and how we handle the difficulties arising from the lack of standard format for data types such as meshes or fibers, the absence of a common programming interface for data processing algorithms, notably registration, and the issues of visualisation where display conventions would be beneficial.

[bibtex-key = Vichot2012] [bibtex-entry]

François Faure, Christian Duriez, Hervé Delingette, Jérémie Allard, Benjamin Gilles, Stéphanie Marchesseau, Hugo Talbot, Hadrien Courtecuisse, Guillaume Bousquet, Igor Peterlik, and Stéphane Cotin. SOFA: A Multi-Model Framework for Interactive Physical Simulation. In Yohan Payan, editor, Soft Tissue Biomechanical Modeling for Computer Assisted Surgery. Springer, June 2012. HAL ID: hal-00681539. [bibtex-key = faure2012sofa] [bibtex-entry]

Xavier Pennec and Vincent Arsigny. Exponential Barycenters of the Canonical Cartan Connection and Invariant Means on Lie Groups. In Frederic Barbaresco, Amit Mishra, and Frank Nielsen, editors, Matrix Information Geometry, pages 123-166. Springer, May 2012. ISBN: 978-3-642-30231-2. HAL ID: hal-00699361.

Abstract:

When performing statistics on elements of sets that possess a particular geometric structure, it is desirable to respect this structure. For instance in a Lie group, it would be judicious to have a notion of a mean which is stable by the group operations (composition and inversion). Such a property is ensured for Riemannian center of mass in Lie groups endowed with a bi-invariant Riemannian metric, like compact Lie groups (e.g. rotations). However, bi-invariant Riemannian metrics do not exist for most non compact and non-commutative Lie groups. This is the case in particular for rigid-body transformations in any dimension greater than one, which form the most simple Lie group involved in biomedical image registration. In this paper, we propose to replace the Riemannian metric by an affine connection structure on the group. We show that the canonical Cartan connections of a connected Lie group provides group geodesics which are completely consistent with the composition and inversion. With such a non-metric structure, the mean cannot be defined by minimizing the variance as in Riemannian Manifolds. However, the characterization of the mean as an exponential barycenter gives us an implicit definition of the mean using a general barycentric equation. Thanks to the properties of the canonical Cartan connection, this mean is naturally bi-invariant. We show the local existence and uniqueness of the invariant mean when the dispersion of the data is small enough. We also propose an iterative fixed point algorithm and demonstrate that the convergence to the invariant mean is at least linear. In the case of rigid-body transformations, we give a simple criterion for the global existence and uniqueness of the bi-invariant mean, which happens to be the same as for rotations. We also give closed forms for the bi-invariant mean in a number of simple but instructive cases, including 2D rigid transformations. For general linear transformations, we show that the bi-invariant mean is a generalization of the (scalar) geometric mean, since the determinant of the bi-invariant mean is the geometric mean of the determinants of the data. Finally, we extend the theory to higher order moments, in particular with the covariance which can be used to define a local bi-invariant Mahalanobis distance.

[bibtex-key = pennec:MIG:2012] [bibtex-entry]

Barbara André, Tom Vercauteren, Anna M. Buchner, Michael B. Wallace, and Nicholas Ayache. A Smart Atlas for Endomicroscopy using Automated Video Retrieval. Medical Image Analysis, 15(4):460-476, August 2011.

Keyword(s): Content-Based Video Retrieval (CBVR), Endomicroscopy, Bag-of-Visual-Words (BoW), Video-mosaicing. Abstract:

To support the challenging task of early epithelial cancer diagnosis from in vivo endomicroscopy, we propose a content-based video retrieval method that uses an expert-annotated database. Motivated by the recent successes of non-medical content-based image retrieval, we first adjust the standard Bag-of-Visual-Words method to handle single endomicroscopic images. A local dense multi-scale description is proposed to keep the proper level of invariance, in our case to translations, in-plane rotations and affine transformations of the intensities. Since single images may have an insufficient field-of-view to make a robust diagnosis, we introduce a video-mosaicing technique that provides large field-of-view mosaic images. To remove outliers, retrieval is followed by a geometrical approach that captures a statistical description of the spatial relationships between the local features. Building on image retrieval, we then focus on efficient video retrieval. Our approach avoids the time-consuming parts of the video-mosaicing by relying on coarse registration results only to account for spatial overlap between images taken at different times. To evaluate the retrieval, we perform a simple nearest neighbors classification with leave-one-patient-out cross-validation. From the results of binary and multi-class classification, we show that our approach outperforms, with statistical significance, several state-of-the art methods. We obtain a binary classification accuracy of 94.2%, which is quite close to clinical expectations.

[bibtex-key = Andre:MEDIA:11] [bibtex-entry]

Nicholas Ayache, Olivier Clatz, Hervé Delingette, Grégoire Malandain, Xavier Pennec, and Maxime Sermesant. Vers un patient numérique personnalisé pour le diagnostic et la thérapie guidés par l'image. Médecine / Sciences, 27:208-213, March 2011. [bibtex-key = Ayache:MedScience:11] [bibtex-entry]

N. Ayache, H. Delingette, and M. Sermesant. Le coeur numérique personnalisé. Bulletin de l'Académie Nationale de Médecine, 195(8), November 2011. [bibtex-key = BANMayache2011] [bibtex-entry]

Caroline Brun, Natasha Leporé, Xavier Pennec, Yi-Yu Chou, Agatha Lee, Greig De Zubicaray, Katie Mcmahon, Margaret Wright, James C. Gee, and Paul Thompson. A nonconservative Lagrangian framework for statistical fluid registration-SAFIRA.. IEEE Transactions on Medical Imaging, 30(2):184-202, February 2011. Note: PMID: 20813636. [bibtex-key = Brun:TMI:2011] [bibtex-entry]

O. Camara, M. Sermesant, P. Lamata, L. Wang, M. Pop, J. Relan, M. De Craene, H. Delingette, H. Liu, S. Niederer, A. Pashaei, G. Plank, D. Romero, R. Sebastian, K.C.L. Wong, H. Zhang, N. Ayache, A.F. Frangi, P. Shi, N.P. Smith, and G.A. Wright. Inter-Model Consistency and Complementarity: Learning from ex-vivo Imaging and Electrophysiological Data towards an Integrated Understanding of Cardiac Physiology. Progress in Biophysics and Molecular Biology, 107:122-133, 2011. [bibtex-key = Camara:PBMB:2011] [bibtex-entry]

François Chung, Jérôme Schmid, Nadia Magnenat-Thalmann, and Hervé Delingette. Comparison of statistical models performance in case of segmentation using a small amount of training datasets. The Visual Computer, 27(2):141-151, February 2011. Note: 10.1007/s00371-010-0536-9. [bibtex-key = Chung:TVCJ:2011] [bibtex-entry]

Hervé Delingette, Florence Billet, Ken C.L. Wong, Maxime Sermesant, S. Rhode, Kawal, Matt Ginks, C.A. Rinaldi, Reza Razavi, and Nicholas Ayache. Personalization of Cardiac Motion and Contractility from Images using Variational Data Assimilation. IEEE Transactions on Biomedical Engineering, 2011. Note: In Press.

Abstract:

Personalization is a key aspect of biophysical models in order to impact clinical practice. In this paper, we propose a personalization method of electromechanical models of the heart from cine-MR images based on the adjoint method. After estimation of electrophysiological parameters, the cardiac motion is estimated based on a proactive electromechanical model. Then cardiac contractilities on two or three regions are estimated by minimizing the discrepancy between measured and simulation motion. Evaluation of the method on three patients with infarcted or dilated myocardium is provided.

[bibtex-key = delingette:inria-00616183] [bibtex-entry]

Stanley Durrleman, Pierre Fillard, Xavier Pennec, Alain Trouvé, and Nicholas Ayache. Registration, Atlas Estimation and Variability Analysis of White Matter Fiber Bundles Modeled as Currents. NeuroImage, 55(3):1073-1090, 2011. ISSN: 1053-8119. Keyword(s): Computational Anatomy. [bibtex-key = Durrleman:NImg:11] [bibtex-entry]

Ezequiel Geremia, Olivier Clatz, Bjoern H. Menze, Ender Konukoglu, Antonio Criminisi, and Nicholas Ayache. Spatial Decision Forests for MS Lesion Segmentation in Multi-Channel Magnetic Resonance Images. NeuroImage, 57(2):378-90, July 2011. [bibtex-key = Geremia:NeuroImage:11] [bibtex-entry]

BM Kelm, FO Kaster, A Henning, MA Weber, P Bachert, P Boesiger, FA Hamprecht, and BH Menze. Using spatial prior knowledge in the spectral fitting of MRS images. NMR in Biomedicine, [Epub ahead of print], 2011. [bibtex-key = kelm:NBM:11] [bibtex-entry]

E. Konukoglu, J. Relan, U. Cilingir, B. Menze, P. Chinchapatnam, A. Jadidi, H. Cochet, M. Hocini, H. Delingette, P. Jaïs, M. Haïssaguerre, N. Ayache, and M. Sermesant. Efficient Probabilistic Model Personalization Integrating Uncertainty on Data and Parameters: Application to Eikonal-Diffusion Models in Cardiac Electrophysiology. Progress in Biophysics and Molecular Biology, 107(1):134-146, October 2011. [bibtex-key = Konukoglu:PBMB:2011] [bibtex-entry]

Georg Langs, Bjoern H. Menze, Danial Lashkari, and Polina Golland. Detecting stable distributed patterns of brain activation using Gini contrast. NeuroImage, 56:497-507, 2011. [bibtex-key = Langs:Neuroimage:2011] [bibtex-entry]

Marco Lorenzi, Alberto Beltramello, Nicola Mercuri, Elisa Canu, Giada Zoccatelli, Francesca Pizzini, Franco Alessandrini, Maria Cotelli, Sandra Rosini, Daniela Costardi, Carlo Caltagirone, and Giovanni Frisoni. Effect of memantine on resting state default mode network activity in Alzheimer's disease. Drugs and Aging, 28(3):205-217, 2011. [bibtex-key = Lorenzi:DaA10:11] [bibtex-entry]

Tommaso Mansi, Xavier Pennec, Maxime Sermesant, Hervé Delingette, and Nicholas Ayache. iLogDemons: A Demons-Based Registration Algorithm for Tracking Incompressible Elastic Biological Tissues. International Journal of Computer Vision, 92(1):92-111, 2011. [bibtex-key = Mansi:IJCV:11] [bibtex-entry]

Tommaso Mansi, Ingmar Voigt, Benedetta Leonardi, Xavier Pennec, Stanley Durrleman, Maxime Sermesant, Hervé Delingette, Andrew M. Taylor, Younes Boudjemline, Giacomo Pongiglione, and Nicholas Ayache. A Statistical Model for Quantification and Prediction of Cardiac Remodelling: Application to Tetralogy of Fallot. IEEE Transactions on Medical Imaging, 9(30):1605-1616, September 2011. [bibtex-key = Mansi:TMI:11] [bibtex-entry]

Keelin Murphy, Bram van Ginneken, Joseph M. Reinhardt, Sven Kabus, Kai Ding, Xiang Deng, Kunlin Cao, Kaifang Du, Gary E. Christensen, Vincent Garcia, Tom Vercauteren, Nicholas Ayache, Olivier Commowick, Gregoire Malandain, Ben Glocker, Nikos Paragios, Nassir Navab, Vladlena Gorbunova, Jon Sporring, Marleen de Bruijne, Xiao Han, Mattias P. Heinrich, Julia A. Schnabel, Mark Jenkinson, Cristian Lorenz, Marc Modat, Jamie R. McClelland, Sebastien Ourselin, Sascha E.A. Muenzing, Max A. Viergever, Dante De Nigris, D. Louis Collins, Tal Arbel, Marta Peroni, Rui Li, Gregory C. Sharp, Alexander Schmidt-Richberg, Jan Ehrhardt, Rene Werner, Dirk Smeets, Dirk Loeckx, Gang Song, Nicholas Tustison, Brian Avants, James C. Gee, Marius Staring, Stefan Klein, Berend C. Stoel, Martin Urschler, Manuel Werlberger, Jef Vandemeulebroucke, Simon Rit, David Sarrut, and Josien P.W. Pluim. Evaluation of registration methods on thoracic CT: the EMPIRE10 challenge. IEEE Trans Med Imaging, 30(11):1901-20, November 2011.

Abstract:

EMPIRE10 (Evaluation of Methods for Pulmonary Image REgistration 2010) is a public platform for fair and meaningful comparison of registration algorithms which are applied to a database of intrapatient thoracic CT image pairs. Evaluation of nonrigid registration techniques is a nontrivial task. This is compounded by the fact that researchers typically test only on their own data, which varies widely. For this reason, reliable assessment and comparison of different registration algorithms has been virtually impossible in the past. In this work we present the results of the launch phase of EMPIRE10, which comprised the comprehensive evaluation and comparison of 20 individual algorithms from leading academic and industrial research groups. All algorithms are applied to the same set of 30 thoracic CT pairs. Algorithm settings and parameters are chosen by researchers expert in the configuration of their own method and the evaluation is independent, using the same criteria for all participants. All results are published on the EMPIRE10 website (http://empire10.isi.uu.nl). The challenge remains ongoing and open to new participants. Full results from 24 algorithms have been published at the time of writing. This paper details the organization of the challenge, the data and evaluation methods and the outcome of the initial launch with 20 algorithms. The gain in knowledge and future work are discussed.

[bibtex-key = murphy:itmi:2011] [bibtex-entry]

E. Pernod, M. Sermesant, E. Konukoglu, J. Relan, H. Delingette, and N. Ayache. A Multi-Front Eikonal Model of Cardiac Electrophysiology for Interactive Simulation of Radio-Frequency Ablation. Computers and Graphics, 35:431-440, 2011. [bibtex-key = Pernod:CG:2011] [bibtex-entry]

K.M Pohl, E. Konukoglu, S. Novellas, N. Ayache, A. Fedorov, I.-F. Talos, A. Golby, W.M. Wells, R. Kikinis, and P.M. Black. A New Metric for Detecting Change in Slowly Evolving Brain Tumors: Validation in Meningioma Patients. Neurosurgery, 68(1 Suppl Operative):225-33, March 2011. [bibtex-key = Pohl:Neurosurgery:11] [bibtex-entry]

M. Pop, M. Sermesant, T. Mansi, E. Crystal, S. Ghate, J. Peyrat, I. Lashevsky, Beiping Qiang, E. McVeigh, N. Ayache, and G.A. Wright. Correspondence Between Simple 3-D MRI-Based Computer Models and In-Vivo EP Measurements in Swine With Chronic Infarctions. Biomedical Engineering, IEEE Transactions on, 58(12):3483-3486, dec. 2011. ISSN: 0018-9294. [bibtex-key = Pop:TBME:2011] [bibtex-entry]

Jatin Relan, Phani Chinchapatnam, Maxime Sermesant, Kawal Rhode, Matt Ginks, Hervé Delingette, C. Aldo Rinaldi, Reza Razavi, and Nicholas Ayache. Coupled Personalization of Cardiac Electrophysiology Models for Prediction of Ischaemic Ventricular Tachycardia. Journal of the Royal Society Interface Focus, 1(3):396-407, 2011. [bibtex-key = Relan:IF:2011] [bibtex-entry]

Jatin Relan, Mihaela Pop, Hervé Delingette, Graham Wright, Nicholas Ayache, and Maxime Sermesant. Personalisation of a Cardiac Electrophysiology Model using Optical Mapping and MRI for Prediction of Changes with Pacing. IEEE Transactions on Bio-Medical Engineering, 58(12):3339-3349, 2011. [bibtex-key = Relan:TBME:11] [bibtex-entry]

Kawal Rhode and Maxime Sermesant. Modeling and Registration for Electrophysiology Procedures Based on Three-Dimensional Imaging. Current Cardiovascular Imaging Reports, 4:116-126, 2011. [bibtex-key = Sermesant:CCIR:11] [bibtex-entry]

N. Smith, A. de Vecchi, M. McCormick, D. Nordsletten, O. Camara, A.F. Frangi, H. Delingette, M. Sermesant, J. Relan, N. Ayache, M. W. Krueger, W. Schulze, R. Hose, I. Valverde, P. Beerbaum, C. Staicu, M. Siebes, J. Spaan, P. Hunter, J. Weese, H. Lehmann, D. Chapelle, and R. Razavi. euHeart: Personalized and integrated cardiac care using patient-specific cardiovascular modelling. Journal of the Royal Society Interface Focus, 1(3):349-364, 2011. ISSN: 2042-8898. [bibtex-key = Smith:IF:2011] [bibtex-entry]

C. Öhman, D. M. Espino, T. Heimann, M. Baleani, H. Delingette, and M. Viceconti. Subject-specific knee joint model: Design of an experiment to validate a multi-body finite element model. The Visual Computer, 27:153-159, 2011. [bibtex-key = Ohman:VisualComputer:11] [bibtex-entry]

T. Heimann and Hervé Delingette. Model-based segmentation. In Thomas Martin Deserno, editor, Biomedical Image Processing. Springer, 2011. ISBN: 978-3-642-15815-5. [bibtex-key = Delingette:RABIPA:10] [bibtex-entry]

B H Menze, E Stretton, E Konukoglu, and N. Ayache. Image-based modeling of tumor growth in patients with glioma.. In C S Garbe, R Rannacher, U Platt, and T Wagner, editors, Optimal control in image processing. Springer, Heidelberg/Germany, 2011. [bibtex-key = menze_11_image-based] [bibtex-entry]

M Cohen, C Lebrun, D Aufauvre, S Chanalet, C Filleau-Bertogliatti, W Camu, P Thomas, G Malandain, and P Clavelou. [Longitudinal study of health related quality of life in multiple sclerosis: correlation with MRI parameters]. Rev Neurol (Paris), 166(11):894-900, November 2010. Note: [In French].

Keyword(s): Adolescent, Adult, Atrophy, Brain, pathology, Cognition, physiology, Contrast Media, Disease Progression, Female, Gadolinium, Humans, Image Processing Computer-Assisted, Interferon Type I, therapeutic use, Longitudinal Studies, Magnetic Resonance Imaging, Male, Middle Aged, Multiple Sclerosis Chronic Progressive, pathology, Neuropsychological Tests, Quality of Life, Recombinant Proteins, Young Adult. Abstract:

INTRODUCTION: Health related quality of life (HRQOL) is often affected in multiple sclerosis (MS). Nevertheless, to our knowledge, there is no longitudinal study in the literature about the correlation between MRI parameters and HRQOL in MS patients. METHODS: We included 28 patients with clinically definite relapsing remitting MS. All patients initiated subcutaneous interferon beta-1a therapy. To assess HRQOL, we used the SEP-59 scale, the French validated translation of MSQOL-54, and the MusiQoL scale. Conventional MRI was performed every year. Lesion load (LL) and brain atrophy were automatically measured using SepINRIA, a free software developed by INRIA in Sophia Antipolis. RESULTS: The mean EDSS score was 1.7 and disease duration was 2.5 years. Our results revealed that HRQOL was significantly correlated to T1 and T2-LL with both SEP-59 and MusiQoL scales. T1-LL was better correlated with physical dimensions and T2-LL was better correlated with mental components. At 1-year follow-up, patients whose MRI showed either an increase of T1 LL or at least one gadolinium enhancing lesion had a worse HRQOL at the end of the study. Initial brain parenchymal fraction (BPF) measure was also correlated with the long-term follow-up HRQOL. EDSS scored at the end of the study had not significantly changed (1.3; P>0.05). CONCLUSION: Our study revealed pertinent clinicoradiological correlations between HRQOL and MRI parameters in our cohort.

[bibtex-key = cohen:rn:2010] [bibtex-entry]

Hervé Delingette and Maxime Sermesant. Le coeur numérique. Doc Sciences, 13:26-33, October 2010. [bibtex-key = Delingette:DocSciences:2010] [bibtex-entry]

Romain Fernandez, Pradeep Das, Vincent Mirabet, Eric Moscardi, Jan Traas, Jean-Luc Verdeil, Grégoire Malandain, and Christophe Godin. Imaging plant growth in 4-D: robust tissue reconstruction and lineaging at cell resolution. Nature Methods, 7(7):547-553, 2010.

Abstract:

Acquiring quantitative information on growing organs is an absolute requirement for a better understanding of morphogenesis in both plants and animals. However, detailed analyses of growth patterns at cellular resolution have remained elusive. To address this, we have designed a novel protocol where we image whole organs from multiple angles, and then computationally merge and segment these images to provide accurate cell identification within high-resolution 3-D reconstructions. We then extend this protocol to study growing organs in 4-D by using a temporal series of such reconstructions to automatically track cell lineages through multiple rounds of cell division during organ development. Using these methods, we carry out quantitative analyses of Arabidopsis flower development at cell resolution, and reveal differential growth patterns of key regions during the early stages of floral morphogenesis that were previously inaccessible. Lastly, using rice roots, we demonstrate that our approach is both generic and scalable.

[bibtex-key = fernandez:nm:2010] [bibtex-entry]

Damien Galanaud, Stéphane Haik, Marius George Linguraru, Jean-Philippe Ranjeva, Baptiste Faucheux, Elsa Kaphan, Nicholas Ayache, Jacques Chiras, Patrick Cozzone, Didier Dormont, and Jean-Philippe Brandel. Combined diffusion imaging and MR Spectroscopy in Human Prion Diseases. AJNR. American journal of neuroradiology, 31(7):1311-8, 2010.

Abstract:

BACKGROUND AND PURPOSE: The physiopathologic bases underlying the signal intensity changes and reduced diffusibility observed in prion diseases (TSEs) are still poorly understood. We evaluated the interest of MRS combined with DWI both as a diagnostic tool and a way to understand the mechanism underlying signal intensity and ADC changes in this setting. MATERIALS AND METHODS: We designed a prospective study of multimodal MR imaging in patients with suspected TSEs. Forty-five patients with a suspicion of TSE and 11 age-matched healthy volunteers were included. The MR imaging protocol included T1, FLAIR, and DWI sequences. MRS was performed on the cerebellum, pulvinar, right lenticular nucleus, and frontal cortex. MR images were assessed visually, and ADC values were calculated. RESULTS: Among the 45 suspected cases, 31 fulfilled the criteria for probable or definite TSEs (19 sCJDs, 3 iCJDs, 2 vCJDs, and 7 genetic TSEs); and 14 were classified as AltDs. High signals in the cortex and/or basal ganglia were observed in 26/31 patients with TSEs on FLAIR and 29/31 patients on DWI. In the basal ganglia, high DWI signals corresponded to a decreased ADC. Metabolic alterations, increased mIns, and decreased NAA were observed in all patients with TSEs. ADC values and metabolic changes were not correlated; this finding suggests that neuronal stress (vacuolization), neuronal loss, and astrogliosis do not alone explain the decrease of ADC. CONCLUSIONS: MRS combined with other MR imaging is of interest in the diagnosis of TSE and provides useful information for understanding physiopathologic processes underlying prion diseases.

[bibtex-key = galanaud:ajnr:2010] [bibtex-entry]

D. Gianni, S. McKeever, T. Yu, R. Britten, Hervé Delingette, A. Frangi, P. Hunter, and Nic Smith. Sharing and reusing cardiovascular anatomical models over the Web: a step towards the implementation of the virtual physiological human project. Philos Transact of the Royal Society A Mathematical Physical Engineering Sciences, 368:3039-3056, June 2010. [bibtex-key = Gianni:PTAMPES:10] [bibtex-entry]

Ender Konukoglu, Olivier Clatz, Pierre-Yves Bondiau, Hervé Delingette, and Nicholas Ayache. Extrapolating Glioma Invasion Margin in Brain Magnetic Resonance Images: Suggesting New Irradiation Margins. Medical Image Analysis, 14(2):111-125, 2010. [bibtex-key = Konukoglu:MEDIA:09] [bibtex-entry]

Ender Konukoglu, Olivier Clatz, Bjoern H. Menze, Marc-André Weber, Bram Stieltjes, Emmanuel Mandonnet, Hervé Delingette, and Nicholas Ayache. Image Guided Personalization of Reaction-Diffusion Type Tumor Growth Models Using Modified Anisotropic Eikonal Equations. IEEE Transactions on Medical Imaging, 29(1):77-95, 2010. [bibtex-key = Konukoglu:TMI:09] [bibtex-entry]

Marco Lorenzi, Michael Donohue, Donata Paternico, Cristina Scarpazza, Susanne Ostrowitzki, Olivier Blin, Elaine Irving, and G. Frisoni. Enrichment through biomarkers in clinical trials of Alzheimer's drugs in patients with mild cognitive impairment. Neurobiology of Aging, pp 1443-51, August 2010. Note: Special Issue on ADNI. [bibtex-key = Lorenzi:NBoA:10] [bibtex-entry]

Stéphanie Marchesseau, T. Heimann, Simon Chatelin, Rémy Willinger, and Hervé Delingette. Fast porous visco-hyperelastic soft tissue model for surgery simulation: application to liver surgery. Progress in Biophysics and Molecular Biology, 103(2-3):185-196, 2010. [bibtex-key = Marchesseau:PBMB:10] [bibtex-entry]

Markand D. Patel, Nicolas Toussaint, Geoffrey D. Charles-Edwards, Jean-Pierre Lin, and Philip G. Batchelor. Distribution and Fibre Field Similarity Mapping of the Human Anterior Commissure Fibres by Diffusion Tensor Imaging. Magnetic Resonance Materials in Physics, Biology and Medicine, February 2010. [bibtex-key = Toussaint:MAGMA:10] [bibtex-entry]

Jean-Marc Peyrat, Hervé Delingette, Maxime Sermesant, Chenyang Xu, and Nicholas Ayache. Registration of 4D Cardiac CT Sequences Under Trajectory Constraints With Multichannel Diffeomorphic Demons. IEEE Transactions on Medical Imaging, 29(7):1351-1368, July 2010. [bibtex-key = Peyrat:TMI:2010] [bibtex-entry]

Liliane Ramus, Juliette Thariat, Pierre-Yves Marcy, Yoann Pointreau, Guillaume Bera, Olivier Commowick, and Grégoire Malandain. Outils de contourage, utilisation et construction d'atlas anatomiques : exemples des cancers de la tete et du cou. Cancer radiothérapie, 14(3):206-12, 2010. Note: In French.

Abstract:

Highly conformal irradiation techniques are associated with steep gradient doses. Accuracy and reproducibility of delineation are required to avoid geometric misses and to properly report dose-volume effects on organs at risk. Guidelines of the International Commission on Radiation Units have largely contributed to high quality treatments. The ICRU endeavors to collect and evaluate the latest data and information pertinent to the problems of radiation measurement and dosimetry. There remains a need for delineation guidelines and automatic segmentation tools in routine practice. Among these tools, atlas-based segmentation has been shown to provide promising results. The methodology used for head and neck cancer patients is illustrated.

[bibtex-key = Ramus:CancerRadiother:2010] [bibtex-entry]

Tammy Riklin-Raviv, Koen Van Leemput, Bjoern H. Menze, William M. Wells, and Polina Golland. Segmentation of image ensembles via latent atlases. Medical Image Analysis, 14(5):654-65, 2010. [bibtex-key = Riklin-Raviv:MedIA:2010] [bibtex-entry]

Boon Thye Thomas Yeo, Mert Sabuncu, Tom Vercauteren, Nicholas Ayache, Bruce Fischl, and Polina Golland. Spherical Demons: Fast Diffeomorphic Landmark-Free Surface Registration. IEEE Transactions on Medical Imaging, 29(3):650-668, March 2010. Note: PMID:19709963.

Abstract:

We present the Spherical Demons algorithm for registering two spherical images. By exploiting spherical vector spline interpolation theory, we show that a large class of regularizors for the modified Demons objective function can be efficiently approximated on the sphere using iterative smoothing. Based on one parameter subgroups of diffeomorphisms, the resulting registration is diffeomorphic and fast. The Spherical Demons algorithm can also be modified to register a given spherical image to a probabilistic atlas. We demonstrate two variants of the algorithm corresponding to warping the atlas or warping the subject. Registration of a cortical surface mesh to an atlas mesh, both with more than 160k nodes requires less than 5 minutes when warping the atlas and less than 3 minutes when warping the subject on a Xeon 3.2GHz single processor machine. This is comparable to the fastest non-diffeomorphic landmarkfree surface registration algorithms. Furthermore, the accuracy of our method compares favorably to the popular FreeSurfer registration algorithm. We validate the technique in two different applications that use registration to transfer segmentation labels onto a new image: (1) parcellation of in-vivo cortical surfaces and (2) Brodmann area localization in ex-vivo cortical surfaces.

[bibtex-key = Yeo:TMI:10] [bibtex-entry]

Ender Konukoglu, Olivier Clatz, Hervé Delingette, and Nicholas Ayache. Personalization of Reaction-Diffusion Tumor Growth Models in MR Images: Application to Brain Gliomas Characterization and Radiotherapy Planning. In Thomas S. Deisboeck and Georgios Stamatakos, editors, Multiscale Cancer Modeling, Chapman & Hall/CRC Mathematical & Computational Biology. CRC Press, December 2010. [bibtex-key = Konukoglu:MCM:2010] [bibtex-entry]

Maxime Sermesant and Reza Razavi. Personalized Computational Models of the Heart for Cardiac Resynchronization Therapy. In Roy C.P. Kerckhoffs, editor, Patient-Specific Modeling of the Cardiovascular System, pages 167-182. Springer New York, 2010. ISBN: 978-1-4419-6691-9. Keyword(s): Life Sciences. [bibtex-key = Sermesant:CRTbook:2010] [bibtex-entry]

Vincent Arsigny, Olivier Commowick, Nicholas Ayache, and Xavier Pennec. A Fast and Log-Euclidean Polyaffine Framework for Locally Linear Registration. Journal of Mathematical Imaging and Vision, 33(2):222-238, 2009. [bibtex-key = Arsigny:JMIV:09] [bibtex-entry]

Éric Bardinet, Manik Bhattacharjee, Didier Dormont, Bernard Pidoux, Grégoire Malandain, Michael Schupbach, Nicholas Ayache, Philippe Cornu, Yves Agid, and Jerome Yelnik. A three-dimensional histological atlas of the human basal ganglia. II. Atlas deformation strategy and evaluation in deep brain stimulation for Parkinson disease.. Journal of Neurosurgery, 110(2):208-19, February 2009.

Keyword(s): Basal Ganglia, pathology, Brain Mapping, methods, Deep Brain Stimulation, methods, Humans, Image Interpretation Computer-Assisted, methods, Imaging Three-Dimensional, methods, Magnetic Resonance Imaging, methods, Medical Illustration, Microelectrodes, Microscopy, Parkinson Disease, pathology, Red Nucleus, pathology, Sensitivity and Specificity, Substantia Nigra, pathology, Subthalamic Nucleus, pathology. Abstract:

OBJECT: The localization of any given target in the brain has become a challenging issue because of the increased use of deep brain stimulation to treat Parkinson disease, dystonia, and nonmotor diseases (for example, Tourette syndrome, obsessive compulsive disorders, and depression). The aim of this study was to develop an automated method of adapting an atlas of the human basal ganglia to the brains of individual patients. METHODS: Magnetic resonance images of the brain specimen were obtained before extraction from the skull and histological processing. Adaptation of the atlas to individual patient anatomy was performed by reshaping the atlas MR images to the images obtained in the individual patient using a hierarchical registration applied to a region of interest centered on the basal ganglia, and then applying the reshaping matrix to the atlas surfaces. RESULTS: Results were evaluated by direct visual inspection of the structures visible on MR images and atlas anatomy, by comparison with electrophysiological intraoperative data, and with previous atlas studies in patients with Parkinson disease. The method was both robust and accurate, never failing to provide an anatomically reliable atlas to patient registration. The registration obtained did not exceed a 1-mm mismatch with the electrophysiological signatures in the region of the subthalamic nucleus. CONCLUSIONS: This registration method applied to the basal ganglia atlas forms a powerful and reliable method for determining deep brain stimulation targets within the basal ganglia of individual patients.

[bibtex-key = bardinet:jn:2009] [bibtex-entry]

Caroline Brun, Natasha Leporé, Xavier Pennec, Agatha D Lee, Marina Barysheva, Sarah K Madsen, Christina Avedissian, Yi-Yu Chou, Greig I. de Zubicaray, Katie McMahon, Margaret Wright, Arthur W. Toga, and Paul M. Thompson. Mapping the Regional Influence of Genetics on Brain Structure Variability - A Tensor-Based Morphometry Study. NeuroImage, 48(1):37-49, October 2009. [bibtex-key = Brun:NeuroImage:09] [bibtex-entry]

Jaydev P. Desai and Nicholas Ayache. Editorial: Special Issue on Medical Robotics. International Journal of Robotics Research, 28(9):1099-1100, 2009. [bibtex-key = desai:ijrr:2009] [bibtex-entry]

Stanley Durrleman, Xavier Pennec, Alain Trouvé, and Nicholas Ayache. Statistical Models on Sets of Curves and Surfaces based on Currents. Medical Image Analysis, 13(5):793-808, October 2009. [bibtex-key = Durrleman:Media:09] [bibtex-entry]

Heike Hufnagel, Jan Ehrhardt, Xavier Pennec, Nicholas Ayache, and Heinz Handels. Computation of a Probabilistic Statistical Shape Model in a Maximum-a-posteriori Framework. Methods of Information in Medicine, 48(4):314-319, 2009. [bibtex-key = Hufnagel:MIM:09] [bibtex-entry]

Arno Klein, Jesper Andersson, Babak A. Ardekani, John Ashburner, Brian Avants, Ming-Chang Chiang, Gary E. Christensen, D. Louis Collins, Pierre Hellier, Joo Hyun Song, Mark Jenkinson, Claude Lepage, Daniel Rueckert, Paul M. Thompson, Tom Vercauteren, Roger P. Woods, J. John Mann, and Ramin V. Parsey. Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration. NeuroImage, 46(3):786-802, July 2009. [bibtex-key = Klein:NeuroImage:09] [bibtex-entry]

S. Nicolau, Xavier Pennec, Luc Soler, X. Buy, A. Gangi, Nicholas Ayache, and J. Marescaux. An Augmented Reality System for Liver Thermal Ablation: Design and Evaluation on Clinical Cases. Medical Image Analysis, 13(3):494-506, June 2009. [bibtex-key = Nicolau:Media:09] [bibtex-entry]

Mihaela Pop, Maxime Sermesant, D Lepiller, M V Truong, Elliot McVeigh, Eugene Crystal, Alexander Dick, Hervé Delingette, Nicholas Ayache, and Graham Wright. Fusion of optical imaging and MRI for the evaluation and adjustment of macroscopic models of cardiac electrophysiology: A feasibility study. Medical Image Analysis, 13(2):370-80, April 2009. [bibtex-key = Pop:2009:MedIA] [bibtex-entry]

R Sims, A Isambert, V Gregoire, F Bidault, L Fresco, J Sage, J Mills, J Bourhis, D Lefkopoulos, Olivier Commowick, M Benkebil, and Grégoire Malandain. A pre-clinical assessment of an atlas-based automatic segmentation tool for the head and neck. Radiotherapy Oncology, 93(3):474-8, December 2009.

Abstract:

BACKGROUND AND PURPOSE: Accurate conformal radiotherapy treatment requires manual delineation of target volumes and organs at risk (OAR) that is both time-consuming and subject to large inter-user variability. One solution is atlas-based automatic segmentation (ABAS) where a priori information is used to delineate various organs of interest. The aim of the present study is to establish the accuracy of one such tool for the head and neck (H&N) using two different evaluation methods. MATERIALS AND METHODS: Two radiotherapy centres were provided with an ABAS tool that was used to outline the brainstem, parotids and mandible on several patients. The results were compared to manual delineations for the first centre (EM1) and reviewed/edited for the second centre (EM2), both of which were deemed as equally valid gold standards. The contours were compared in terms of their volume, sensitivity and specificity with the results being interpreted using the Dice similarity coefficient and a receiver operator characteristic (ROC) curve. RESULTS: Automatic segmentation took typically approximately 7min for each patient on a standard PC. The results indicated that the atlas contour volume was generally within +/-1SD of each gold standard apart from the parotids for EM1 and brainstem for EM2 that were over- and under-estimated, respectively (within +/-2SD). The similarity of the atlas contours with their respective gold standard was satisfactory with an average Dice coefficient for all OAR of 0.68+/-0.25 for EM1 and 0.82+/-0.13 for EM2. All data had satisfactory sensitivity and specificity resulting in a favourable position in ROC space. CONCLUSIONS: These tests have shown that the ABAS tool exhibits satisfactory sensitivity and specificity for the OAR investigated. There is, however, a systematic over-segmentation of the parotids (EM1) and under-segmentation of the brainstem (EM2) that require careful review and editing in the majority of cases. Such issues have been discussed with the software manufacturer and a revised version is due for release.

[bibtex-key = sims:ro:2009] [bibtex-entry]

Jean-Christophe Souplet, Christine Lebrun, Stéphane Chanalet, Nicholas Ayache, and Grégoire Malandain. Revue des approches de segmentation des lésions de sclérose en plaques dans les séquences conventionnelles IRM. Revue Neurologique, 165(1):7-14, 2009. Note: In french. [bibtex-key = Souplet:RevNeurol:09] [bibtex-entry]

Tom Vercauteren, Xavier Pennec, Aymeric Perchant, and Nicholas Ayache. Diffeomorphic Demons: Efficient Non-parametric Image Registration. NeuroImage, 45(1, Supp.1):S61-S72, March 2009. [bibtex-key = Vercauteren:NeuroImage:09] [bibtex-entry]

Boon Thye Thomas Yeo, Tom Vercauteren, Pierre Fillard, Jean-Marc Peyrat, Xavier Pennec, Polina Golland, Nicholas Ayache, and Olivier Clatz. DT-REFinD: Diffusion Tensor Registration with Exact Finite-Strain Differential. IEEE Transactions on Medical Imaging, 28(12):1914-1928, December 2009. Note: PMID:19556193. [bibtex-key = Yeo:TMI:09] [bibtex-entry]

Nicholas Ayache, Olivier Clatz, Hervé Delingette, Grégoire Malandain, Xavier Pennec, and Maxime Sermesant. Asclepios: a Research Project-Team at INRIA for the Analysis and Simulation of Biomedical Images. In Y. Bertot, G. Huet, J.-J. Lévy, and G. Plotkin, editors, From semantics to computer science: essays in honor of Gilles Kahn, pages 415-436. Cambridge University Press, 2009. [bibtex-key = ayache:kahn:2009] [bibtex-entry]

C. Germain-Renaud, V. Breton, P. Clarysse, B. Delhay, Y. Gaudeau, T. Glatard, E. Jannot, Y. Legré, Johan Montagnat, J.-M. Moureau, A. Osorio, Xavier Pennec, J. Schaerer, and R. Texier. Grid Analysis of Radiological Data. In Mario Cannataro, editor, Handbook of Research on Computational Grid Technologies for Life Sciences, Biomedicine, and Healthcare, pages 363-391. IGI Global, 2009. Note: IGI-Global Medical Information Science Discoveries Research Award 2009. [bibtex-key = Germain:HRCG:09] [bibtex-entry]

Tommaso Mansi, Barbara André, Michael Lynch, Maxime Sermesant, Hervé Delingette, Younes Boudjemline, and Nicholas Ayache. Virtual Pulmonary Valve Replacement Interventions with a Personalised Cardiac Electromechanical Model. In Nadia Magnenat-Thalmann, Jian J. Zhang, and David D. Feng, editors, Recent Advances in the 3D Physiological Human, pages 201-210. Springer, November 2009. ISBN: 978-1-84882-564-2. [bibtex-key = Mansi:3DPH:08] [bibtex-entry]

Jérôme Schmid, Anders Sandholm, François Chung, Daniel Thalmann, Hervé Delingette, and Nadia Magnenat-Thalmann. Musculoskeletal simulation model generation from MRI datasets and motion capture data. In Nadia Magnenat-Thalmann, Jian J. Zhang, and David D. Feng, editors, Recent Advances in the 3D Physiological Human, pages 3-19. Springer, February 2009. ISBN: 978-1-84882-564-2. [bibtex-key = Schmid:3DPH:08] [bibtex-entry]

Christof Seiler, P. Büchler, L.-P. Nolte, R. Paulsen, and Mauricio Reyes. Hierarchical Markov Random Fields Applied to Model Soft Tissue Deformations on Graphics Hardware. In J. J. Zhang N. Magnenat-Thalmann and D. D. Feng, editors, Recent Advances in the 3D Physiological Human, pages 133-148. Springer, 2009. ISBN: 978-1-84882-564-2. [bibtex-key = Seiler:3DPH:09] [bibtex-entry]

Neculai Archip, Olivier Clatz, Stephen Whalen, Simon Dimaio, Peter Black, Alexandra Golby, Ferenc Jolesz, and Simon Warfield. Compensation of geometric distortion effects on intraoperative magnetic resonance imaging for enhanced visualization in image-guided neurosurgery. Neurosurgery, 62(3 supl. 1):209-15, March 2008. [bibtex-key = Archip:Neurosurgery:08] [bibtex-entry]

Jonathan Boisvert, Farida Cheriet, Xavier Pennec, Hubert Labelle, and Nicholas Ayache. Articulated Spine Models for 3D Reconstruction from Partial Radiographic Data. IEEE Transactions on Bio-Medical Engineering, 55(11):2565-2574, November 2008. [bibtex-key = Boisvert:TBME:08] [bibtex-entry]

Jonathan Boisvert, Farida Cheriet, Xavier Pennec, Hubert Labelle, and Nicholas Ayache. Geometric Variability of the Scoliotic Spine using Statistics on Articulated Shape Models. IEEE Transactions on Medical Imaging, 27(4):557-568, 2008. [bibtex-key = Boisvert:TMI:08] [bibtex-entry]

Jonathan Boisvert, Farida Cheriet, Xavier Pennec, Hubert Labelle, and Nicholas Ayache. Principal Deformations Modes of Articulated Models for the Analysis of 3D Spine Deformities. Electronic Letters on Computer Vision and Image Analysis, 7(4):13-31, December 2008. [bibtex-key = Boisvert:ELCVIA:08] [bibtex-entry]

Pierre-Yves Bondiau, Olivier Clatz, Maxime Sermesant, Pierre-Yves Marcy, Hervé Delingette, Marc Frenay, and Nicholas Ayache. Biocomputing: numerical simulation of glioblastoma growth using diffusion tensor imaging. Physics in Medicine and Biology, 53(4):879-93, February 2008. [bibtex-key = bondiau:pmb:08] [bibtex-entry]

P. Chinchapatnam, K.S. Rhode, M. Ginks, C.A. Rinaldi, P. Lambiase, R. Razavi, S. Arridge, and M. Sermesant. Model-Based Imaging of Cardiac Apparent Conductivity and Local Conduction Velocity for Diagnosis and Planning of Therapy. IEEE Transactions on Medical Imaging, 27(11):1631-1642, 2008. [bibtex-key = TMI2008Phani] [bibtex-entry]

Olivier Commowick, Vincent Arsigny, Aurélie Isambert, Jimena Costa, Frédéric Dhermain, François Bidault, Pierre-Yves Bondiau, Nicholas Ayache, and Grégoire Malandain. An efficient locally affine framework for the smooth registration of anatomical structures. Medical Image Analysis, 12(4):427-41, August 2008.

Keyword(s): Algorithms, Brain, anatomy & histology, Diagnostic Imaging, methods, Humans, Image Processing Computer-Assisted, Radiotherapy Planning Computer-Assisted, methods, Sensitivity and Specificity. Abstract:

Intra-subject and inter-subject nonlinear registration based on dense transformations requires the setting of many parameters, mainly for regularization. This task is a major issue, as the global quality of the registration will depend on it. Setting these parameters is, however, very hard, and they may have to be tuned for each patient when processing data acquired by different centers or using different protocols. Thus, we present in this article a method to introduce more coherence in the registration by using fewer degrees of freedom than with a dense registration. This is done by registering the images only on user-defined areas, using a set of affine transformations, which are optimized together in a very efficient manner. Our framework also ensures a smooth and coherent transformation thanks to a new regularization of the affine components. Finally, we ensure an invertible transformation thanks to the Log-Euclidean polyaffine framework. This allows us to get a more robust and very efficient registration method, while obtaining good results as explained below. We performed a qualitative and quantitative evaluation of the obtained results on two applications: first on atlas-based brain segmentation, comparing our results with a dense registration algorithm. Then the second application for which our framework is particularly well suited concerns bone registration in the lower-abdomen area. We obtain in this case a better positioning of the femoral heads than with a dense registration. For both applications, we show a significant improvement in computation time, which is crucial for clinical applications.

[bibtex-key = commowick:mia:2008] [bibtex-entry]

Olivier Commowick, Vincent Grégoire, and Grégoire Malandain. Atlas-Based Delineation of Lymph Node Levels in Head and Neck Computed Tomography Images. Radiotherapy Oncology, 87(2):281-289, 2008. [bibtex-key = Commowick_RO_2008] [bibtex-entry]

H. Delingette. Triangular Springs for Modeling Nonlinear Membranes. IEEE Transactions on Visualization and Computer Graphics, 14(2), March/April 2008. [bibtex-key = delingette:tvcg:2008] [bibtex-entry]

Stanley Durrleman, Xavier Pennec, Alain Trouvé, Paul Thompson, and Nicholas Ayache. Inferring brain variability from diffeomorphic deformations of currents: an integrative approach. Medical Image Analysis, 12(5):626-637, 2008. [bibtex-key = Durrleman:Media:08] [bibtex-entry]

Tristan Glatard, Johan Montagnat, David Emsellem, and Diane Lingrand. A Service-Oriented Architecture enabling dynamic services grouping for optimizing distributed workflows execution. Future Generation Computer Systems, 7(24):720-730, July 2008. [bibtex-key = glatard-montagnat-etal:2007b] [bibtex-entry]

Tristan Glatard, Johan Montagnat, Diane Lingrand, and Xavier Pennec. Flexible and efficient workflow deployment of data-intensive applications on GRIDS with MOTEUR. International Journal of High Performance Computing Applications, 3(22):347-360, August 2008. Note: Special issue on Workflow Systems in Grid Environments. [bibtex-key = Glatard:IJHPCA:08] [bibtex-entry]

S Haik, D Galanaud, MG Linguraru, K Peoc'h, N Privat, BA Faucheux, N Ayache, JJ Hauw, D Dormont, and JP Brandel. In Vivo Detection of Thalamic Gliosis: A Pathoradiologic Demonstration in Familial Fatal Insomnia. Archives of Neurology, 65(4):545-549, April 2008.

Abstract:

BACKGROUND: Increasing evidence supports the usefulness of brain magnetic resonance imaging (MRI) for the diagnosis of human prion diseases. From the neuroradiological point of view, fatal familial insomnia is probably the most challenging to diagnose because brain lesions are mostly confined to the thalamus. OBJECTIVE: To determine whether multisequence MRI of the brain can show thalamic alterations and establish pathoradiologic correlations in a patient with familial fatal insomnia. DESIGN: Radioclinical prospective study. We describe a patient with fatal familial insomnia and normal MRI images. Because the MRI study was performed only 4 days before the patient's death, we were able to compare radiological data with the lesions observed at the neuropathologic level. Patient A 55-year-old man with familial fatal insomnia. Main Outcome Measure Magnetic resonance spectroscopy combined with the measurement of apparent diffusion coefficient of water in different brain areas. RESULTS: The neuroradiological study showed, in the thalamus but not in the other brain regions studied, an increase of apparent diffusion coefficient of water and a metabolic pattern indicating gliosis. These alterations closely correlated with neuropathologic data showing an almost pure gliosis that was restricted to the thalami. CONCLUSION: Considering fatal familial insomnia as a model of thalamic-restricted gliosis, this case demonstrates that multisequences of magnetic resonance can detect prion-induced gliosis in vivo, as confirmed by a neuropathologic examination performed only a few days after radiological examination.

[bibtex-key = haik:an:2008] [bibtex-entry]

H. Hufnagel, X. Pennec, J. Ehrhardt, N. Ayache, and H. Handels. Generation of a Statistical Shape Model with Probabilistic Point Correspondences and EM-ICP. International Journal for Computer Assisted Radiology and Surgery, 2(5):265-273, March 2008. [bibtex-key = Hufnagel:ijcars:2008] [bibtex-entry]

A Isambert, G Bonniaud, F Lavielle, G Malandain, and D Lefkopoulos. A phantom study of the accuracy of CT, MR and PET image registrations with a block matching-based algorithm. Cancer radiothérapie, 12(8):800-8, December 2008.

Keyword(s): Algorithms, Automation, Brain, pathology, Head, Humans, Magnetic Resonance Imaging, methods, Phantoms Imaging, Positron-Emission Tomography, methods, Radiotherapy Planning Computer-Assisted, methods, Software, Tomography X-Ray Computed, methods. Abstract:

PURPOSE: The aim of the present study was to quantitatively assess the performance of a block matching-based automatic registration algorithm integrated within the commercial treatment planning system designated ISOgray from Dosisoft. The accuracy of the process was evaluated by a phantom study on computed tomography (CT), magnetic resonance (MR) and positron emission tomography (PET) images. MATERIALS AND METHODS: Two phantoms were used to carry out this study: the cylindrical Jaszczak phantom and the anthropomorphic Liqui-Phil Head Phantom (the Phantom Laboratory), containing fillable spheres. External fiducial markers were used to quantify the accuracy of 41 CT/CT, MR/CT and PET/CT automatic registrations with images of the rotated and tilted phantoms. RESULTS: The study first showed that a cylindrical phantom was not adapted for the evaluation of the performance of a block matching-based registration software. Secondly, the Liqui-Phil Head Phantom study showed that the algorithm was able to perform automatic registrations of CT/CT and MR/CT images with differences of up to 40 degrees in phantom rotation and of up to 20-30 degrees for PET/CT with accuracy below the image voxel size. CONCLUSION: The study showed that the block matching-based automatic registration software under investigation was robust, reliable and yielded very satisfactory results. This phantom-based test can be integrated into a periodical quality assurance process and used for any commissioning of image registration software for radiation therapy.

[bibtex-key = isambert:cr:2008] [bibtex-entry]

Aurélie Isambert, Frédéric Dhermain, François Bidault, Olivier Commowick, Pierre-Yves Bondiau, Grégoire Malandain, and Dimitri Lefkopoulos. Evaluation of an atlas-based automatic segmentation software for the delineation of brain organs at risk in a radiation therapy clinical context. Radiotherapy Oncology, 87(1):93-9, April 2008.

Keyword(s): Algorithms, Brain Neoplasms, pathology, Female, Humans, Image Interpretation Computer-Assisted, methods, Magnetic Resonance Imaging, Male, Middle Aged, ROC Curve, Retrospective Studies, Software, Tomography X-Ray Computed. Abstract:

BACKGROUND AND PURPOSE: Conformal radiation therapy techniques require the delineation of volumes of interest, a time-consuming and operator-dependent task. In this work, we aimed to evaluate the potential interest of an atlas-based automatic segmentation software (ABAS) of brain organs at risk (OAR), when used under our clinical conditions. MATERIALS AND METHODS: Automatic and manual segmentations of the eyes, optic nerves, optic chiasm, pituitary gland, brain stem and cerebellum of 11 patients on T1-weighted magnetic resonance, 3-mm thick slice images were compared using the Dice similarity coefficient (DSC). The sensitivity and specificity of the ABAS were also computed and analysed from a radiotherapy point of view by splitting the ROC (Receiver Operating Characteristic) space into four sub-regions. RESULTS: Automatic segmentation of OAR was achieved in 7-8 min. Excellent agreement was obtained between automatic and manual delineations for organs exceeding 7 cm3: the DSC was greater than 0.8. For smaller structures, the DSC was lower than 0.41. CONCLUSIONS: These tests demonstrated that this ABAS is a robust and reliable tool for automatic delineation of large structures under clinical conditions in our daily practice, even though the small structures must continue to be delineated manually by an expert.

[bibtex-key = isambert:ro:2008] [bibtex-entry]

Emmanuel Mandonnet, Johan Pallud, Olivier Clatz, Hugues Duffau, and Laurent Capelle. Computational Modelling of the WHO Grade II Glioma Dynamics: Principles and Applications to Surgical Strategy. Neurosurgical Review, 31(3):263-9, July 2008. [bibtex-key = Mandonnet:NSR:08] [bibtex-entry]

Johan Montagnat, Tristan Glatard, Isabel Campos Plasencia, Francisco Castejon, Xavier Pennec, Giuliano Taffoni, Vladimir Voznesensky, and Claudio Vuerli. Workflow-based data parallel applications on the EGEE production grid infrastructure. Journal of Grid Computing, 6(4):369-383, December 2008. [bibtex-key = Montagnat:JGC:2008] [bibtex-entry]

D R Rutgers, P Fillard, G Paradot, M Tadie, P Lasjaunias, and D Ducreux. Diffusion tensor imaging characteristics of the corpus callosum in mild, moderate, and severe traumatic brain injury. AJNR. American journal of neuroradiology, 29(9):1730-5, October 2008.

Keyword(s): Adult, Anisotropy, Brain Concussion, diagnosis, Brain Injuries, diagnosis, Corpus Callosum, injuries, Diffuse Axonal Injury, diagnosis, Diffusion Magnetic Resonance Imaging, Female, Follow-Up Studies, Humans, Image Processing Computer-Assisted, Male, Middle Aged, Nerve Fibers, pathology, Young Adult. Abstract:

BACKGROUND AND PURPOSE: The corpus callosum is an important predilection site for traumatic axonal injury but may be unevenly affected in head trauma. We hypothesized that there were local differences in axonal injury within the corpus callosum as investigated with diffusion tensor imaging (DTI), varying among patients with differing severity of traumatic brain injury (TBI). MATERIALS AND METHODS: Ethics committee approval and informed consent were obtained. Ten control subjects (7 men, 3 women; mean age, 37 +/- 9 years) and 39 patients with TBI (27 men, 12 women; 34 +/- 12 years) were investigated, of whom 24 had mild; 9, moderate; and 6, severe TBI. Regions of interest were selected in the callosal genu, body, and splenium to calculate fractional anisotropy (FA), apparent diffusion coefficient (ADC), and the number of fibers passing through. Statistical comparison was made through analysis of variance with the Scheffe post hoc analysis. RESULTS: Compared with controls, patients with mild TBI investigated <3 months posttrauma (n = 12) had reduced FA (P < .01) and increased ADC (P < .05) in the genu, whereas patients with mild TBI investigated > or =3 months posttrauma (n = 12) showed no significant differences. Patients with moderate and severe TBI, all investigated <3 months posttrauma, had reduced FA (P < .001) and increased ADC (P < .01) in the genu compared with controls and reduced FA in the splenium (P < .001) without significant ADC change. CONCLUSION: Mild TBI is associated with DTI abnormalities in the genu <3 months posttrauma. In more severe TBI, both the genu and splenium are affected. DTI suggests a larger contribution of vasogenic edema in the genu than in the splenium in TBI.

[bibtex-key = rutgers:aajn:2008] [bibtex-entry]

D R Rutgers, F Toulgoat, J Cazejust, P Fillard, P Lasjaunias, and D Ducreux. White matter abnormalities in mild traumatic brain injury: a diffusion tensor imaging study. AJNR. American journal of neuroradiology, 29(3):514-9, March 2008.

Keyword(s): Adult, Brain, pathology, Brain Injuries, pathology, Demyelinating Diseases, pathology, Diffusion Magnetic Resonance Imaging, methods, Female, Humans, Male, Nerve Fibers Myelinated, pathology, Reproducibility of Results, Sensitivity and Specificity. Abstract:

BACKGROUND AND PURPOSE: Traumatic axonal injury is a primary brain abnormality in head trauma and is characterized by reduction of fractional anisotropy (FA) on diffusion tensor imaging (DTI). Our hypothesis was that patients with mild traumatic brain injury (TBI) have widespread brain white matter regions of reduced FA involving a variety of fiber bundles and show fiber disruption on fiber tracking in a minority of these regions. MATERIALS AND METHODS: Ethics committee approval and informed consent were obtained. Twenty-one patients with mild TBI were investigated (men:women, 12:9; mean age +/- SD, 32 +/- 9 years). In a voxel-based comparison with 11 control subjects (men:women, 8:3; mean age, 37 +/- 9 years) using z score analysis, patient regions with abnormally reduced FA were defined in brain white matter. MR imaging, DTI, and fiber tracking characteristics of these regions were described and analyzed using Pearson correlation, linear regression analysis, or the chi(2) test when appropriate. RESULTS: Patients had on average 9.1 regions with reduced FA, with a mean region volume of 525 mm(3), predominantly found in cerebral lobar white matter, cingulum, and corpus callosum. These regions mainly involved supratentorial projection fiber bundles, callosal fibers, and fronto-temporo-occipital association fiber bundles. Internal capsules and infratentorial white matter were relatively infrequently affected. Of all of the involved fiber bundles, 19.3% showed discontinuity on fiber tracking. CONCLUSION: Patients with mild TBI have multiple regions with reduced FA in various white matter locations and involving various fiber bundles. A minority of these fiber bundles show discontinuity on fiber tracking.

[bibtex-key = rutgers:aajn:2008:b] [bibtex-entry]

M Sermesant, J M Peyrat, P Chinchapatnam, F Billet, T Mansi, K Rhode, H Delingette, R Razavi, and N Ayache. Toward patient-specific myocardial models of the heart. Heart Failure Clinics, 4(3):289-301, July 2008. [bibtex-key = Sermesant:2008:Heart-Fail-Clin:18598981] [bibtex-entry]

Ender Konukoglu, Xavier Pennec, Olivier Clatz, and Nicholas Ayache. Tumor Growth Modeling in Oncological Image Analysis. In I. Bankman, editor, Handbook of Medical Image Processing and Analysis - New edition, chapter 18, pages 297-307. Academic Press, December 2008. ISBN: 13: 978-0-12-373904-9. [bibtex-key = Konukoglu:HMIP:08] [bibtex-entry]

X. Pennec. Statistical computing on manifolds: from Riemannian geometry to computational anatomy. In Frank Nielsen, editor, Emerging Trends in Visual Computing, volume 5416 of LNCS, pages 347-386. Springer, 2008. ISBN: 978-3-642-00825-2. [bibtex-key = Pennec:ETCV:08] [bibtex-entry]

Xavier Pennec, Nicholas Ayache, and Jean-Philippe Thirion. Landmark-based registration using features identified through differential geometry. In I. Bankman, editor, Handbook of Medical Image Processing and Analysis - New edition, chapter 34, pages 565-578. Academic Press, December 2008. ISBN: 13: 978-0-12-373904-9. Keyword(s): registration, matching, validation, uncertainty. [bibtex-key = Pennec:HMIP:08] [bibtex-entry]

Tom Vercauteren, Nicholas Ayache, Nicolas Savoire, Grégoire Malandain, and Aymeric Perchant. Processing of In Vivo Fibered Confocal Microscopy Video Sequences. In Jens Rittscher, Raghu Machiraju, and Stephen T. C. Wong, editors, Microscopic Image Analysis for Life Science Applications, chapter 19, pages 441-463. Artech House, 2008. [bibtex-key = Vercauteren:MIALSA:08] [bibtex-entry]

Elsa Angelini, Olivier Clatz, Emmanuel Mandonnet, Ender Konukoglu, Laurent Capelle, and Hugues Duffau. Glioma Dynamics and Computational Models: A Review of Segmentation, Registration, and In Silico Growth Algorithms and their Clinical Applications. Current Medical Imaging Reviews, 3(4):262-176, 2007. [bibtex-key = Angelini:CMIR:07] [bibtex-entry]

Neculai Archip, Olivier Clatz, Stephen Whalen, Dan Kacher, Andriy Fedorov, Andriy Kot, Nikos Chrisochoides, Ferenc Jolesz, Alexandra Golby, Peter Black, and Simon Warfield. Non-rigid alignment of preoperative MRI, fMRI, and DT-MRI with intra-operative MRI for enhanced visualization and navigation in image-guided neurosurgery. NeuroImage, 35(2):609-24, April 2007. [bibtex-key = Archip:NI:06] [bibtex-entry]

Vincent Arsigny, Pierre Fillard, Xavier Pennec, and Nicholas Ayache. Geometric Means in a Novel Vector Space Structure on Symmetric Positive-Definite Matrices. SIAM Journal on Matrix Analysis and Applications, 29(1):328-347, 2007. Keyword(s): DT-MRI, Tensors, Riemannian geometry, Lie groups, interpolation, Log-Euclidean metrics. [bibtex-key = Arsigny:Siam:07] [bibtex-entry]

M. A. Audette, H. Delingette, A. Fuchs, O. Burgert, and K. Chinzei. A topologically faithful, tissue-guided, spatially varying meshing strategy for computing patient-specific head models for endoscopic pituitary surgery simulation. Journal of Computer Aided Surgery, 12(1):43-52, January 2007. [bibtex-key = audette:cas:2007] [bibtex-entry]

Valentin Becker, Tom Vercauteren, Claus Hann von Weyern, Christian Prinz, Roland M. Schmid, and Alexander Meining. High Resolution Miniprobe-based Confocal Microscopy in Combination with Video-mosaicing. Gastrointestinal Endoscopy, 66(5):1001-1007, November 2007. [bibtex-key = Becker:GIE:07] [bibtex-entry]

Olivier Clatz, Stéphane Litrico, Hervé Delingette, Philippe Paquis, and Nicholas Ayache. Dynamic Model of Communicating Hydrocephalus for Surgery Simulation. IEEE Transactions on Bio-Medical Engineering, 54(4):755-758, April 2007. [bibtex-key = Clatz:TBME:07] [bibtex-entry]

Julien Dauguet, Thierry Delzescaux, Françoise Condé, Jean-François Mangin, Nicholas Ayache, Philippe Hantraye, and Vincent Frouin. Three-dimensional reconstruction of stained histological slices and 3D non-linear registration with in-vivo MRI for whole baboon brain. Journal of Neuroscience Methods, 164(1):191-204, 2007. [bibtex-key = Dauguet:Neuroscience:2007] [bibtex-entry]

D. Ducreux, P. Fillard, D. Facon, A. Ozanne, J.-F. Lepeintre, J. Renoux, M. Tadié, and P. Lasjaunias. Diffusion Tensor Magnetic Resonance Imaging and Fiber Tracking in Spinal Cord Lesions: Current and Future Indications. Neuroimaging Clinics of North America, 17(1):137-147, February 2007. [bibtex-key = Fillard:NCNAM:2007] [bibtex-entry]

Pierre Fillard, Vincent Arsigny, Xavier Pennec, Kiralee M. Hayashi, Paul M. Thompson, and Nicholas Ayache. Measuring Brain Variability by Extrapolating Sparse Tensor Fields Measured on Sulcal Lines. NeuroImage, 34(2):639-650, January 2007. Note: Also as INRIA Research Report 5887, April 2006. PMID: 17113311. [bibtex-key = Fillard:NeuroImage:06] [bibtex-entry]

Pierre Fillard, Xavier Pennec, Vincent Arsigny, and Nicholas Ayache. Clinical DT-MRI Estimation, Smoothing and Fiber Tracking with Log-Euclidean Metrics. IEEE Transactions on Medical Imaging, 26(11):1472-1482, November 2007. [bibtex-key = Fillard:TMI:2007] [bibtex-entry]

Marius G. Linguraru, Miguel A. González Ballester, and Nicholas Ayache. Deformable Atlases for the Segmentation of Internal Brain Nuclei in Magnetic Resonance Imaging. International Journal of Computers, Communication and Control, 2(1):26-36, 2007. [bibtex-key = Linguraru:ijccc:07] [bibtex-entry]

Marius George Linguraru, Tom Vercauteren, Mauricio Reyes Aguirre, Miguel Ángel González Ballester, and Nicholas Ayache. Segmentation Propagation from Deformable Atlases for Brain Mapping and Analysis. Brain Research Journal, 1(4):269-287, 2007. [bibtex-key = Linguraru:BRJ:07] [bibtex-entry]

Jean-Marc Peyrat, Maxime Sermesant, Xavier Pennec, Hervé Delingette, Chenyang Xu, Eliot R. McVeigh, and Nicholas Ayache. A Computational Framework for the Statistical Analysis of Cardiac Diffusion Tensors: Application to a Small Database of Canine Hearts. IEEE Transactions on Medical Imaging, 26(11):1500-1514, November 2007. [bibtex-key = Peyrat:TMI:2007] [bibtex-entry]

A. Pitiot, H. Delingette, and P.M. Thompson. Learning Shape Correspondence for n-D curves. International Journal of Computer Vision, 71(1):71-88, January 2007. [bibtex-key = pitiot:ijcv:2007] [bibtex-entry]

M Reyes, G Malandain, P M Koulibaly, M A Gonzalez-Ballester, and J Darcourt. Model-based respiratory motion compensation for emission tomography image reconstruction. Physics in Medicine and Biology, 52(12):3579-600, June 2007.

Abstract:

In emission tomography imaging, respiratory motion causes artifacts in lungs and cardiac reconstructed images, which lead to misinterpretations, imprecise diagnosis, impairing of fusion with other modalities, etc. Solutions like respiratory gating, correlated dynamic PET techniques, list-mode data based techniques and others have been tested, which lead to improvements over the spatial activity distribution in lungs lesions, but which have the disadvantages of requiring additional instrumentation or the need of discarding part of the projection data used for reconstruction. The objective of this study is to incorporate respiratory motion compensation directly into the image reconstruction process, without any additional acquisition protocol consideration. To this end, we propose an extension to the maximum likelihood expectation maximization (MLEM) algorithm that includes a respiratory motion model, which takes into account the displacements and volume deformations produced by the respiratory motion during the data acquisition process. We present results from synthetic simulations incorporating real respiratory motion as well as from phantom and patient data.

[bibtex-key = reyes:pmb:2007] [bibtex-entry]

Luc Thiberville, Sophie Moreno-Swirc, Tom Vercauteren, Eric Peltier, Charlotte Cavé, and Geneviève Bourg Heckly. In Vivo Imaging of the Bronchial Wall Microstructure Using Fibered Confocal Fluorescence Microscopy. American journal of respiratory and critical care medicine, 175(1):22-31, January 2007. Note: Chosen for the cover of the AJRCCM paper issue. PMID: 17023733. [bibtex-key = Thiberville:AJRCCM:06] [bibtex-entry]

Jérôme Yelnik, Eric Bardinet, Didier Dormont, Grégoire Malandain, Sébastien Ourselin, Dominique Tandé, Carine Karachi, Nicholas Ayache, Philippe Cornu, and Yves Agid. A three-dimensional, histological and deformable atlas of the human basal ganglia. I. Atlas construction based on immunohistochemical and MRI data. NeuroImage, 34(2):618-38, January 2007.

Abstract:

This paper describes the construction of an atlas of the human basal ganglia. The successive steps of the construction were as follows. First a postmortem specimen was subjected to a MRI acquisition prior to extraction of the brain from the skull. The brain was then cryosectioned (70 mum thickness). One section out of ten (80 sections) was Nissl-stained with cresyl violet, another series of 80 sections was immunostained for the calcium binding protein calbindin. Contours of basal ganglia nuclei including their calbindin-stained functional subdivisions, fiber bundles and ventricles (n=80 structures) were traced from histological sections and digitized. A novelty of this atlas is the MRI acquisition, which represents the core data element of the study. MRI was used for the coregistration of the atlas data and permitted, through multimodal (Nissl, calbindin, images of cryosectioning, T1 and T2 MRI) and 3D optimization, the production of anatomically and geometrically consistent 3D surfaces, which can be sliced through any desired orientation. The atlas MRI is also used for its deformation to provide accurate conformation to the MRI of living patients, thus adding information at the histological level to the patient's MRI volume. This latter aspect will be presented in a forthcoming paper.

[bibtex-key = yelnik:neuroimage:2007] [bibtex-entry]

Grégoire Malandain. Applications de la géométrie discrète en imagerie médicale. In Géométrie discrète et images numériques, Traités IC2, pages 371-379. Hermès, 2007. [bibtex-key = malandain:geometry:2007] [bibtex-entry]

Vincent Arsigny, Pierre Fillard, Xavier Pennec, and Nicholas Ayache. Log-Euclidean Metrics for Fast and Simple Calculus on Diffusion Tensors. Magnetic Resonance in Medicine, 56(2):411-421, August 2006. Keyword(s): DT-MRI, Tensors, Riemannian geometry, Lie groups, interpolation, Log-Euclidean metrics. [bibtex-key = Arsigny:MRM:06] [bibtex-entry]

C Bensa, C Bertogliati, S Chanalet, G Malandain, P Bedoucha, and C Lebrun. Early detection of cognitive impairment in relapsing-remitting multiple sclerosis: functional-anatomical correlations and longitudinal follow-up. Revue Neurologique, 162(12):1221-31, December 2006. Note: [In French].

Abstract:

Introduction. Cognitive impairment is frequent in relapsing remitting Multiple Sclerosis and is often diagnosed after disruption of occupational and social relations. METHODS: We studied at baseline a homogeneous population of 32 RRMS patients, diagnosed for less than 5 years, with spontaneous memory complaints, and 20 controls. Sixteen patients were followed for 2 years, combining physical examination, neuropsychological tests, and brain MRI. Neuropsychological tests used evaluated memory capacities, attentional capacities, executive functions, language, and visuo-constructive praxis. Lesion load on brain MRI was measured with semi-automatic segmentation procedures and manual control. RESULTS: Eighty percent of patients presented cognitive impairment, and this proportion was higher than that found in the literature. These disorders were more marked for verbal episodic memory, attention, and executive functions. Patients with brain MRI that initially fulfilled the Barkhof criteria and those with callous lesions had more memory disorders. No link between global T1 and T2 lesion loads and neuropsychological scores was found. A statistical link between posterior fossa lesions and attentional disorders was shown. In the longitudinal follow-up, patients had better performances in memory and attentional domains, and a lower number of cognitive domains with dysfunction for each patient. This improvement on neuropsychological tests, whereas EDSS levels were stable, underlined a possible test-retest effect. CONCLUSION: During the initial phase of the disease, most of the relapsing remitting patients present a mild cognitive impairment. Early detection, therapeutic propositions, and recognition of disorders are necessary.

[bibtex-key = bensa:rn:2006] [bibtex-entry]

Christophe Blondel, Grégoire Malandain, Régis Vaillant, and Nicholas Ayache. Reconstruction of Coronary Arteries from a Single Rotational X-Ray Projection Sequence. IEEE Transactions on Medical Imaging, 25(5):653-663, May 2006.

Keyword(s): Angiocardiography, Coronarography, Image Motion Analysis, Image Reconstruction, Tomography. Abstract:

Cardiovascular diseases remain the primary cause of death in developed countries. In most cases, exploration of possibly underlying coronary artery pathologies is performed using X-ray coronary angiography. Current clinical routine in coronary angiography is directly conducted in 2-D projection images from several static viewing angles. However, for diagnosis and treatment purposes, coronary artery reconstruction is highly suitable. The purpose of this study is to provide physicians with a 3-D model of coronary arteries, e.g. for absolute three-dimensional measures for lesion assessment, instead of direct projective measures deduced from the images, which are highly dependent on the viewing angle. In this article, we propose a novel method to reconstruct coronary arteries from one single rotational X-ray projection sequence. As a side result, we also obtain an estimation of the coronary artery motion. Our method consists of 3 main consecutive steps: (1) 3-D reconstruction of coronary artery centerlines, including respiratory motion compensation, (2) coronary artery 4-D motion computation, and (3) 3-D tomographic reconstruction of coronary arteries, involving compensation for respiratory and cardiac motions. We present some experiments on clinical datasets, and the feasibility of a true 3-D Quantitative Coronary Analysis is demonstrated.

[bibtex-key = blondel:tmi:2006] [bibtex-entry]

Francis Cassot, Frederic Lauwers, Céline Fouard, Steffen Prohaska, and Valerie Lauwers-Cances. A novel three-dimensional computer-assisted method for a quantitative study of microvascular networks of the human cerebral cortex. Microcirculation, 13(1):1-18, January 2006.

Abstract:

OBJECTIVE: Detailed information on microvascular network anatomy is a requirement for understanding several aspects of microcirculation, including oxygen transport, distributions of pressure, and wall shear stress in microvessels, regulation of blood flow, and interpretation of hemodynamically based functional imaging methods, but very few quantitative data on the human brain microcirculation are available. The main objective of this study is to propose a new method to analyze this microcirculation. METHODS: From thick sections of india ink-injected human brain, using confocal laser microscopy, the authors developed algorithms adapted to very large data sets to automatically extract and analyze center lines together with diameters of thousands of brain microvessels within a large cortex area. RESULTS: Direct comparison between the original data and the processed vascular skeletons demonstrated the high reliability of this method and its capability to manage a large amount of data, from which morphometry and topology of the cerebral microcirculation could be derived. CONCLUSIONS: Among the many parameters that can be analyzed by this method, the capillary size, the frequency distributions of diameters and lengths, the fractal nature of these networks, and the depth-related density of vessels are all vital features for an adequate model of cerebral microcirculation.

[bibtex-key = cassot:microcirculation:2006] [bibtex-entry]

Olivier Clatz, Emmanuel Mandonnet, Stéphane Chanalet, Christine Lebrun, Ender Konukoglu, Hervé Delingette, Nicholas Ayache, and Pierre-Yves Bondiau. Modèles Biomathématiques de Croissance Des Gliomes : Recherche en Informatique et Perspectives en Neuro-oncologie. Neurologies, 9(93):665-667, 2006. [bibtex-key = clatz:neurologies:06] [bibtex-entry]

O. Colliot, T. Mansi, N. Bernasconi, V. Naessens, D. Klironomos, and A. Bernasconi. Segmentation of focal cortical dysplasia lesions on MRI using level set evolution. NeuroImage, 32(4):1621-1630, October 2006.

Abstract:

Focal cortical dysplasia (FCD) is the most frequent malformation of cortical development in patients with medically intractable epilepsy. On MRI, FCD lesions are not easily differentiable from the normal cortex and defining their spatial extent is challenging. In this paper, we introduce a method to segment FCD lesions on T1-weighted MRI. It relies on two successive three-dimensional deformable models, whose evolutions are based on the level set framework. The first deformable model is driven by probability maps obtained from three MRI features: cortical thickness, relative intensity and gradient. These features correspond to the visual characteristics of FCD and allow discriminating lesions and normal tissues. In a second stage, the previous result is expanded towards the underlying and overlying cortical boundaries, throughout the whole cortical section. The method was quantitatively evaluated by comparison with manually traced labels in 18 patients with FCD. The automated segmentations achieved a strong agreement with the manuals labels, demonstrating the applicability of the method to assist the delineation of FCD lesions on MRI. This new approach may become a useful tool for the presurgical evaluation of patients with intractable epilepsy related to cortical dysplasia.

[bibtex-key = colliot:2006:neuroimage] [bibtex-entry]

Hervé Delingette and Nicholas Ayache. La simulation de Chirurgie Hépatique. Pour la science, 52(52):106-109, July 2006. Keyword(s): Simulation. [bibtex-key = Delingette:PLS:06] [bibtex-entry]

Hervé Delingette, Xavier Pennec, Luc Soler, Jacques Marescaux, and Nicholas Ayache. Computational Models for Image Guided, Robot-Assisted and Simulated Medical Interventions. Proceedings of the IEEE, 94(9):1678- 1688, September 2006. [bibtex-key = Delingette:IEEEProc:06] [bibtex-entry]

Denis Ducreux, Frédéric Dhermain, and Pierre Fillard. [Functional MRI in brain tumours]. Cancer radiothérapie, 10(6-7):330-3, November 2006. Note: [In French].

Keyword(s): Brain, anatomy & histology, Brain Mapping, Brain Neoplasms, pathology, Humans, Magnetic Resonance Imaging, methods, Prognosis. Abstract:

Functional MRI is a technique of imaging which is developing fast as it allows non-aggressive evaluation of brain functions. Diffusion, perfusion and activation are each used to study brain responsiveness to a given task. As a pretherapeutic routine investigation, in brain tumours, it can be helpful as an additional tool to morphological MRI in evaluating the prognosis of patients.

[bibtex-key = Ducreux:CancerRadiotherapy:06] [bibtex-entry]

Denis Ducreux, Jean-Francois Lepeintre, Pierre Fillard, C. Loureiro, Marc Tadié, and Pierre Lasjaunias. MR diffusion tensor imaging and fiber tracking in 5 spinal cord astrocytomas. AJNR. American journal of neuroradiology, 27(1):214-6, January 2006.

Keyword(s): Adult, Astrocytoma, diagnosis, Diffusion Magnetic Resonance Imaging, Female, Humans, Image Processing Computer-Assisted, Imaging Three-Dimensional, Male, Nerve Fibers, pathology, Spinal Cord, pathology, Spinal Cord Neoplasms, diagnosis. Abstract:

Spinal cord astrocytomas are rare neoplasms that can result in alteration of the spinal cord structural integrity, which can be assessed by using diffusion tensor imaging methods. Our objective was to visualize the deformation of the posterior spinal cord lemniscal and corticospinal tracts in 5 patients with low-grade astrocytomas compared with 10 healthy volunteers by using 3D fiber-tracking reconstructions.

[bibtex-key = Ducreux:AJNR:06] [bibtex-entry]

Céline Fouard, Grégoire Malandain, Steffen Prohaska, and Malte Westerhoff. Blockwise Processing Applied to Brain Microvascular Network Study. IEEE Transactions on Medical Imaging, 25(10):1319-1328, 2006.

Abstract:

The study of cerebral microvascular networks requires high-resolution images. However, to obtain statistically relevant results, a large area of the brain (several square millimeters) must be analyzed. This leads us to consider huge images, too large to be loaded and processed at once in the memory of a standard computer. To consider a large area, a compact representation of the vessels is required. The medial axis is the preferred tool for this application. To extract it, a dedicated skeletonization algorithm is proposed. Numerous approaches already exist which focus on computational efficiency. However, they all implicitly assume that the image can be completely processed in the computer memory, which is not realistic with the large images considered here. We present in this paper a skeletonization algorithm that processes data locally (in subimages) while preserving global properties (i.e., homotopy). We then show some results obtained on a mosaic of three-dimensional images acquired by confocal microscopy.

[bibtex-key = fouard:tmi:2006] [bibtex-entry]

M. Liberatore, C. Denier, Pierre Fillard, M.C. Petit-Lacour, F. Benoudiba, Pierre Lasjaunias, and Denis Ducreux. [Diffusion tensor imaging and tractography of central pontine myelinolysis]. J Neuroradiol, 33(3):189-193, June 2006. Note: [In French].

Keyword(s): Adult, Anorexia, complications, Diffusion Magnetic Resonance Imaging, Female, Humans, Myelinolysis Central Pontine, diagnosis, Pyramidal Tracts, pathology. Abstract:

OBJECTIVES: To illustrate the value of diffusion tensor imaging and tractography in the diagnosis and follow-up of central pontine myelinolysis. CASE REPORT: We report a case of central pontine myelinolysis in a 29 year old woman, also anorexic, studied using MR Diffusion Tensor Imaging (DTI) and Fibre Tracking (FT) focused on the pons, and compared with the studies of 5 normal volunteers. Tractography showed a swollen aspect of the right corticospinal fiber tract correlating with mild left lower extremity deficit at clinical evaluation. The pontine fibers were posteriorly displaced but intact. The sensory tracts were also intact. Apparent Diffusion Coefficient values were increased and Fractional Anisotropy was decreased in the lesions. Follow up imaging showed persistent abnormal ADC and FA values in the pons although the left cortico-spinal tract returned to normal, consistent with the clinical outcome. CONCLUSION: Diffusion Tensor Imaging MR and Fiber tractography are a new method to analyse white matter tracts. It can be used to prospectively evaluate the location of white matter tract lesions at the acute phase of central pontine myelinolysis and follow up.

[bibtex-key = Liberatore:JNeuroradiology:06] [bibtex-entry]

M.G. Linguraru, N. Ayache, E. Bardinet, M.A. González Ballester, D. Galanaud, S. Haïk, B.A. Faucheux, J.J. Hauw, P. Cozzone, D. Dormont, and J.P. Brandel. Differentiation of sCJD and vCJD Forms by Automated Analysis of Basal Ganglia Intensity Distribution in Multisequence MRI of the Brain - Definition and Evaluation of New MRI-based Ratios. IEEE Transactions on Medical Imaging, 25(8):1052-1067, 2006. [bibtex-key = Linguraru:TMI:2006] [bibtex-entry]

M.G. Linguraru, K. Marias, R. English, and J.M. Brady. A Biologically Inspired Algorithm for Microcalcification Cluster Detection. Medical Image Analysis, 10(6), 2006. [bibtex-key = Linguraru:MedIA:2006] [bibtex-entry]

Valérie Moreau-Villéger, Hervé Delingette, Maxime Sermesant, Hiroshi Ashikaga, Elliot McVeigh, and Nicholas Ayache. Building Maps of Local Apparent Conductivity of the Epicardium with a 2D Electrophysiological Model of the Heart. IEEE Transactions on Bio-Medical Engineering, 53(8):1457-1466, August 2006. [bibtex-key = moreau:ieeetbme06] [bibtex-entry]

Xavier Pennec. Intrinsic Statistics on Riemannian Manifolds: Basic Tools for Geometric Measurements. Journal of Mathematical Imaging and Vision, 25(1):127-154, July 2006. Note: A preliminary appeared as INRIA RR-5093, January 2004. Keyword(s): Fréchet means, Statistics, Lie groups, Riemannian geometry. [bibtex-key = Pennec:JMIV:06] [bibtex-entry]

Xavier Pennec, Pierre Fillard, and Nicholas Ayache. A Riemannian Framework for Tensor Computing. International Journal of Computer Vision, 66(1):41-66, January 2006. Note: A preliminary version appeared as INRIA Research Report 5255, July 2004.

Keyword(s): Tensors, regularization, PDE, geometry, Riemannian geometry. Abstract:

Tensors are nowadays a common source of geometric information. In this paper, we propose to endow the tensor space with an affine-invariant Riemannian metric. We demonstrate that it leads to strong theoretical properties: the cone of positive definite symmetric matrices is replaced by a regular and complete manifold without boundaries (null eigenvalues are at the infinity), the geodesic between two tensors and the mean of a set of tensors are uniquely defined, etc. We have previously shown that the Riemannian metric provides a powerful framework for generalizing statistics to manifolds. In this paper, we show that it is also possible to generalize to tensor fields many important geometric data processing algorithms such as interpolation, filtering, diffusion and restoration of missing data. For instance, most interpolation and Gaussian filtering schemes can be tackled efficiently through a weighted mean computation. Linear and anisotropic diffusion schemes can be adapted to our Riemannian framework, through partial differential evolution equations, provided that the metric of the tensor space is taken into account. For that purpose, we provide intrinsic numerical schemes to compute the gradient and Laplace-Beltrami operators. Finally, to enforce the fidelity to the data (either sparsely distributed tensors or complete tensors fields) we propose least-squares criteria based on our invariant Riemannian distance which are particularly simple and efficient to solve.

[bibtex-key = Pennec:IJCV:06] [bibtex-entry]

Alain Pitiot, Eric Bardinet, Paul M. Thompson, and Grégoire Malandain. Piecewise Affine Registration of Biological Images for Volume Reconstruction. Medical Image Analysis, 10(3):465-483, June 2006.

Keyword(s): registration, clustering, reconstruction, histology, MRI. Abstract:

This manuscript tackles the reconstruction of 3D volumes via mono-modal registration of series of 2D biological images (histological sections, autoradiographs, cryosections, etc.). The process of acquiring these images typically induces composite transformations that we model as a number of rigid or affine local transformations embedded in an elastic one. We propose a registration approach closely derived from this model. Given a pair of input images, we first compute a dense similarity field between them with a block matching algorithm. We use as a similarity measure an extension of the classical correlation coefficient that improves the consistency of the field. A hierarchical clustering algorithm then automatically partitions the field into a number of classes from which we extract independent pairs of sub-images. Our clustering algorithm relies on the Earth mover's distribution metric and is additionally guided by robust least-square estimation of the transformations associated with each cluster. Finally, the pairs of sub-images are, independently, affinely registered and a hybrid affine/non-linear interpolation scheme is used to compose the output registered image. We investigate the behavior of our approach on several batches of histological data and discuss its sensitivity to parameters and noise.

[bibtex-key = pitiot:media:2006] [bibtex-entry]

J Renoux, D Facon, P Fillard, I Huynh, P Lasjaunias, and D Ducreux. MR diffusion tensor imaging and fiber tracking in inflammatory diseases of the spinal cord. AJNR. American journal of neuroradiology, 27(9):1947-51, October 2006.

Keyword(s): Adult, Anisotropy, Diagnosis Differential, Diffusion Magnetic Resonance Imaging, Female, Humans, Image Enhancement, Image Processing Computer-Assisted, Male, Middle Aged, Multiple Sclerosis, diagnosis, Myelitis, diagnosis, Myelitis Transverse, diagnosis, Nerve Fibers, pathology, Neurologic Examination, Prospective Studies, Reference Values, Sarcoidosis, diagnosis, Spinal Cord, pathology. Abstract:

PURPOSE: Our aim was to study the fractional anisotropy (FA) variations and the fiber tracking (FT) patterns observed in patients with myelitis. MATERIAL AND METHODS: Fifteen patients with symptomatic myelitis and 11 healthy subjects were prospectively selected. We performed T2-weighted and diffusion tensor imaging on a 1.5T MR scanner. FA and apparent diffusion coefficient maps were computed in both healthy subjects and patients. In each patient, we performed FT to study pathologic aspects on this imaging method. FA data were analyzed by using z-scores. RESULTS: For the healthy subjects, averaged FA values ranged from 0.745 to 0.751. All abnormal areas seen on T2-weighted imaging had a significantly decreased FA value. In 9 patients (60%), FA maps showed decreased FA areas, whereas T2-weighted imaging findings were normal. These areas matched the neurologic deficit in 33%. Eighty percent of patients had multiple decreased FA areas. Five patients (33%) had increased FA values in normal T2-weighted areas. CONCLUSION: We observed specific FA and FT pattern variations in patients with myelitis.

[bibtex-key = renoux:aajn:2006] [bibtex-entry]

Gilles Scarella, Olivier Clatz, Stéphane Lanteri, Grégory Beaume, Steve Oudot, Jean-Philippe Pons, Serge Piperno, Patrick Joly, and Joe Wiart. Realistic numerical modelling of human head tissue exposure to electromagnetic waves from cellular phones. Comptes Rendus de l'Académie des Sciences - Physics, 7(5):501-508, June 2006.

Abstract:

The ever-rising diffusion of cellular phones has brought about an increased concern for the possible consequences of electromagnetic radiation on human health. Possible thermal effects have been investigated, via experimentation or simulation, by several research projects in the last decade. Concerning numerical modeling, the power absorption in a user's head is generally computed using discretized models built from clinical MRI data. The vast majority of such numerical studies have been conducted using Finite Differences Time Domain methods, although strong limitations of their accuracy are due to heterogeneity, poor definition of the detailed structures of head tissues (staircasing effects), etc. In order to propose numerical modeling using Finite Element or Discontinuous Galerkin Time Domain methods, reliable automated tools for the unstructured discretization of human heads are also needed. Results presented in this article aim at filling the gap between human head MRI images and the accurate numerical modeling of wave propagation in biological tissues and its thermal effects.

[bibtex-key = Scarella:CRAS:06] [bibtex-entry]

Maxime Sermesant, Hervé Delingette, and Nicholas Ayache. An Electromechanical Model of the Heart for Image Analysis and Simulation. IEEE Transactions on Medical Imaging, 25(5):612-625, 2006. [bibtex-key = Sermesant:TMI:06] [bibtex-entry]

Maxime Sermesant, Philippe Moireau, Oscar Camara, Jacques Sainte-Marie, Rado Andriantsimiavona, Robert Cimrman, Derek L. Hill, Dominique Chapelle, and Reza Razavi. Cardiac function estimation from MRI using a heart model and data assimilation: Advances and difficulties. Medical Image Analysis, 10(4):642-656, 2006. [bibtex-key = Sermesant:MEDIA:06] [bibtex-entry]

Arjan W Simonetti, Vedat A Elezi, Regine Farion, Gregoire Malandain, Christoph Segebarth, Chantal Remy, and Emmanuel L Barbier. A low temperature embedding and section registration strategy for 3D image reconstruction of the rat brain from autoradiographic sections. Journal of Neuroscience Methods, 158(2):242-50, December 2006.

Abstract:

In studies on animal models of human brain pathologies, three-dimensional reconstruction from histological sections is particularly useful when assessing the morphologic, functional and biochemical changes induced by pathology. It allows assessing lesion heterogeneity in planes different from the cutting plane and allows correlating the histology with images obtained in vivo, such as by means of magnetic resonance imaging. To create a 3D volume from autoradiographic sections with minimal distortion, both cryosectioning as well as section registration need to be optimal. This paper describes a strategy whereby four external fiducial markers are positioned outside the rat brain with the use of a low temperature brain embedding procedure. The fiducial markers proposed here can be rapidly added to any frozen tissue block with no impact on the subsequent histological operations. Since embedding is performed at a low temperature, no tissue degradation occurs due to sample heating. The markers enable robust and almost error free registration, even in the presence of missing sections and poor image quality. Furthermore, the markers may be used to partially correct for global distortions.

[bibtex-key = simonetti:jnm:2006] [bibtex-entry]

Tom Vercauteren, Aymeric Perchant, Grégoire Malandain, Xavier Pennec, and Nicholas Ayache. Robust Mosaicing with Correction of Motion Distortions and Tissue Deformation for In Vivo Fibered Microscopy. Medical Image Analysis, 10(5):673-692, October 2006. Note: Annual Medical Image Analysis (MedIA) Best Paper Award 2006. PMID: 16887375. [bibtex-key = Vercauteren:Media:06] [bibtex-entry]

Vincent Arsigny, Xavier Pennec, and Nicholas Ayache. Polyrigid and Polyaffine Transformations: a Novel Geometrical Tool to Deal with Non-Rigid Deformations - Application to the registration of histological slices. Medical Image Analysis, 9(6):507-523, December 2005. Keyword(s): Non-rigid registration, Histological slices, Polyaffine transformations, Ordinary differential equations. [bibtex-key = arsigny:media:05] [bibtex-entry]

J.-D. Boissonnat, R. Chaine, P. Frey, G. Malandain, S. Salmon, E. Saltel, and M. Thiriet. From arteriographies to computational flow in saccular aneurisms: the INRIA experience. Medical Image Analysis, 9(2):133-143, April 2005.

Keyword(s): 3D reconstruction, Aneurism, Finite element method, Mesh adaptation, Pulsatile flow. Abstract:

Saccular aneurisms illustrate usefulness and possible techniques of image-based modeling of flow in diseased vessels. Aneurism flow is investigated in order to estimate the rupture risk, assuming that the pressure is the major factor and that high-pressure zones are correlated to within-wall strong-stress concentrations. Computational flow is also aimed at providing additional arguments for the treatment strategy. Angiographies of aneurismal vessels of large and medium size are processed to provide three-dimensional reconstruction of the vessel region of interest. Different reconstruction techniques are used for a side and a terminal aneurisms. Reconstruction techniques may lead to different geometries especially with poor input data. The associated facetisation is improved to get a computation-adapted surface triangulation, after a treatment of vessel ends and mesh adaptation. Once the volumic mesh is obtained, the pulsatile flow of an incompressible Newtonian blood is computed using in vivo non-invasive flowmetry and the finite element method. High pressure zones are observed in the aneurism cavity. The pressure magnitude in the aneurism, the location and the size of high pressure zones depend mainly on the aneurism implantation on the vessel wall and its orientation with respect to the blood flux in the upstream vessel. The stronger the blood impacts on the aneurismal wall the higher the pressure. The state of the aneurism neck, where a high-pressure zone can occur, and the location of the aneurism, with an easy access or not, give arguments for the choice between coiling and surgical clipping. Mesh size and 3D reconstruction procedure affect the numerical results. Helpful qualitative data are provided rather than accurate quantitative results in the context of multimodeling.

[bibtex-key = boissonnat:media:2005] [bibtex-entry]

Pierre-Yves Bondiau, Gregoire Malandain, Stephane Chanalet, Pierre-Yves Marcy, Jean-Louis Habrand, Francois Fauchon, Philippe Paquis, Adel Courdi, Olivier Commowick, Isabelle Rutten, and Nicholas Ayache. Atlas-based automatic segmentation of MR images: validation study on the brainstem in radiotherapy context. Int J Radiat Oncol Biol Phys, 61(1):289-98, January 2005.

Keyword(s): Algorithms, Anatomical Atlas, methods, Brain Neoplasms, pathology, Brain Stem, anatomy & histology, Humans, Image Interpretation Computer-Assisted, methods, Magnetic Resonance Imaging, methods, Medical Illustration, Observer Variation, Reproducibility of Results, Sensitivity and Specificity. Abstract:

PURPOSE: Brain tumor radiotherapy requires the volume measurements and the localization of several individual brain structures. Any tool that can assist the physician to perform the delineation would then be of great help. Among segmentation methods, those that are atlas-based are appealing because they are able to segment several structures simultaneously, while preserving the anatomy topology. This study aims to evaluate such a method in a clinical context. METHODS AND MATERIALS: The brain atlas is made of two three-dimensional (3D) volumes: the first is an artificial 3D magnetic resonance imaging (MRI); the second consists of the segmented structures in this artificial MRI. The elastic registration of the artificial 3D MRI against a patient 3D MRI dataset yields an elastic transformation that can be applied to the labeled image. The elastic transformation is obtained by minimizing the sum of the square differences of the image intensities and derived from the optical flow principle. This automatic delineation (AD) enables the mapping of the segmented structures onto the patient MRI. Parameters of the AD have been optimized on a set of 20 patients. Results are obtained on a series of 6 patients' MRI. A comprehensive validation of the AD has been conducted on performance of atlas-based segmentation in a clinical context with volume, position, sensitivity, and specificity that are compared by a panel of seven experimented physicians for the brain tumor treatments. RESULTS: Expert interobserver volume variability ranged from 16.70 cm(3) to 41.26 cm(3). For patients, the ratio of minimal to maximal volume ranged from 48% to 70%. Median volume varied from 19.47 cm(3) to 27.66 cm(3) and volume of the brainstem calculated by AD varied from 17.75 cm(3) to 24.54 cm(3). Medians of experts ranged, respectively, for sensitivity and specificity, from 0.75 to 0.98 and from 0.85 to 0.99. Median of AD were, respectively, 0.77 and 0.97. Mean of experts ranged, respectively, from 0.78 to 0.97 and from 0.86 to 0.99. Mean of AD were, respectively, 0.76 and 0.97. CONCLUSIONS: Results demonstrate that the method is repeatable, provides a good trade-off between accuracy and robustness, and leads to reproducible segmentation and labeling. These results can be improved by enriching the atlas with the rough information of tumor or by using different laws of deformation for the different structures. Qualitative results also suggest that this method can be used for automatic segmentation of other organs such as neck, thorax, abdomen, pelvis, and limbs.

[bibtex-key = bondiau:ijrobp:2005] [bibtex-entry]

Olivier Clatz, Hervé Delingette, Ion-Florin Talos, Alexandra J. Golby, Ron Kikinis, Ferenc Jolesz, Nicholas Ayache, and Simon Warfield. Robust Non-Rigid Registration to Capture Brain Shift from Intra-Operative MRI. IEEE Transactions on Medical Imaging, 24(11):1417-1427, Nov. 2005.

Keyword(s): Non-rigid registration, intra-operative magnetic resonance imaging, finite element model, brain shift. Abstract:

We present a new algorithm to register 3D pre-operative Magnetic Resonance (MR) images to intra-operative MR images of the brain which have undergone brain shift. This algorithm relies on a robust estimation of the deformation from a sparse noisy set of measured displacements. We propose a new framework to co mpute the displacement field in an iterative process, allowing the solution to gradually move from an approximation formulation (minimizing the sum of a re gularization term and a data error term) to an interpolation formulation (least square minimization of the data error term). An outlier rejection step is i ntroduced in this gradual registration process using a weighted least trimmed squares approach, aiming at improving the robustness of the algorithm. We use a patient-specific model discretized with the finite element method (FEM) in order to ensure a realistic mechanical behavior of the brain tissue. To meet the clinical time constraint, we parallelized the slowest step of the algorithm so that we can perform a full 3D image registration in 35 seconds ( including the image update time) on a heterogeneous cluster of 15 PCs. The algorithm has been tested on six cases of brain tumor resection, presenting a brain shift of up to 14 mm. The results show a good ability to recover la rge displacements, and a limited decrease of accuracy near the tumor resection cavity.

[bibtex-key = clatz_2:TMI:2005] [bibtex-entry]

Olivier Clatz, Maxime Sermesant, Pierre-Yves Bondiau, Hervé Delingette, Simon K. Warfield, Grégoire Malandain, and Nicholas Ayache. Realistic Simulation of the 3D Growth of Brain Tumors in MR Images Coupling Diffusion with Mass Effect. IEEE Transactions on Medical Imaging, 24(10):1334-1346, October 2005.

Keyword(s): Tumor, brain, growth, model, simulation. Abstract:

We propose a new model to simulate the 3D growth of glioblastomas multiforma (GBMs), the most aggressive glial tumors. The GBM speed of growth depends on the invaded tissue: faster in white than in gray matter, it is stopped by the dura or the ventricles. These different structures are introduced into the model using an atlas matching technique. The atlas includes both the segmentations of anatomical structures and diffusion information in white matter fibers. We use the finite element method (FEM) to simulate the invasion of the GBM in the brain parenchyma and its mechanical interaction with the invaded structures (mass effect). Depending on the considered tissue, the former effect is modeled with a reaction-diffusion or a Gompertz equation, while the latter is based on a linear elastic brain constitutive equation. In addition, we propose a new coupling equation taking into account the mechanical influence of the tumor cells on the invaded tissues. The tumor growth simulation is assessed by comparing the extit{in-silico} GBM growth with the real growth observed on two magnetic resonance images (MRIs) of a patient acquired with six months difference. Results show the feasibility of this new conceptual approach and justifies its further validation.

[bibtex-key = clatz_1:TMI:2005] [bibtex-entry]

H. Delingette and N. Ayache. Hepatic Surgery Simulation. Communications of the ACM, 48(2):31-36, February 2005. [bibtex-key = Delingette:cacm:2005] [bibtex-entry]

D. Ducreux, I. Huynh, P. Fillard, J. Renoux, M.C. Petit-Lacour, K. Marsot-Dupuch, and P. Lasjaunias. Brain MR Diffusion Tensor Imaging and Fibre Tracking to Differentiate Between Two Diffuse Axonal Injuries. Neuroradiology, 47(8):604-608, August 2005. [bibtex-key = Ducreux:Neuroradiology:05] [bibtex-entry]

D. Facon, A. Ozanne, P. Fillard, J.-F. Lepeintre, C. Tournoux-Facon, and D. Ducreux. MR Diffusion Tensor Imaging and Fiber Tracking in Spinal Cord Compression. AJNR. American journal of neuroradiology, 26:1587-1594, 2005. [bibtex-key = Facon:AJNR:05] [bibtex-entry]

C. Forest, H. Delingette, and N. Ayache. Removing Tetrahedra from manifold tetrahedralisation : application to real-time surgical simulation. Medical Image Analysis, 9(2):113-122, April 2005.

Keyword(s): Surgical simulation, Topological modifications, Manifold meshes. Abstract:

This paper proposes an efficient method for removing tetrahedra from a tetrahedral mesh while keeping its manifold property. We first define precisely the notion of manifold tetrahedral mesh and stress its relevance in the context of real-time surgery simulation. We then provide a method for removing a tetrahedron that complies with the manifold definition. This removal may require in some cases the removal of neighboring tetrahedra. After providing an exhaustive description of the tetrahedron removal algorithm, its efficiency is evaluated for different mesh configurations. This algorithm is currently used in the context of real-time surgery simulation where the action of an ultrasonic lancet can be simulated by the removal of small set of tetrahedra from a tetrahedralisation.

[bibtex-key = Forest:media:2005] [bibtex-entry]

Céline Fouard and Grégoire Malandain. 3-D chamfer distances and norms in anisotropic grids. Image and Vision Computing, 23(2):143-158, February 2005.

Keyword(s): chamfer distance, anisotropic lattice, Farey triangulation. Abstract:

Chamfer distances are widely used in image analysis and many authors have investigated the computation of optimal chamfer mask coefficients. Unfortunately, these methods are not systematized: calculations have to be conducted manually for every mask size or image anisotropy. Since image acquisition (e.g. medical imaging) can lead to discrete anisotropic grids with unpredictable anisotropy value, automated calculation of chamfer mask coefficients becomes mandatory for e cient distance map computations. This article presents an automatic construction for chamfer masks of arbitrary sizes. This allows, first, to derive analytically the relative error with respect to the Euclidean distance, in any 3-D anisotropic lattice, and second, to compute optimal chamfer coefficients. In addition, the resulting chamfer map verifies discrete norm conditions.

[bibtex-key = fouard:ivc:2005] [bibtex-entry]

C. Germain, V. Breton, P. Clarysse, Y. Gaudeau, T. Glatard, E. Jeannot, Y. Legré, C. Loomis, I. Magnin, J. Montagnat, J.-M. Moureau, A. Osorio, X. Pennec, and R. Texier. Grid-Enabling Medical Image Analysis. Journal of Clinical Monitoring and Computing, 19(4-5):339-349, October 2005. [bibtex-key = Germain:JCMC:2005] [bibtex-entry]

Grégoire Malandain and Mauricio Reyes. La tomographie en mouvement. Pour la science, 338:132-137, December 2005. [bibtex-key = malandain:pls:05] [bibtex-entry]

J. Montagnat and H. Delingette. 4D Deformable Models with temporal constraints : application to 4D cardiac image segmentation. Medical Image Analysis, 9(1):87-100, February 2005. [bibtex-key = Montagnat:Media:04] [bibtex-entry]

V Muthurangu, D Atkinson, M Sermesant, M E Miquel, S Hegde, R Johnson, R Andriantsimiavona, A M Taylor, E Baker, R Tulloh, D Hill, and R S Razavi. Measurement of total pulmonary arterial compliance using invasive pressure monitoring and MR flow quantification during MR-guided cardiac catheterization. American journal of physiology. Heart and circulatory physiology, 289(3):1301-1306, September 2005.

Abstract:

Pulmonary hypertensive disease is assessed by quantification of pulmonary vascular resistance. Pulmonary total arterial compliance is also an indicator of pulmonary hypertensive disease. However, because of difficulties in measuring compliance, it is rarely used. We describe a method of measuring pulmonary arterial compliance utilizing magnetic resonance (MR) flow data and invasive pressure measurements. Seventeen patients with suspected pulmonary hypertension or congenital heart disease requiring preoperative assessment underwent MR-guided cardiac catheterization. Invasive manometry was used to measure pulmonary arterial pressure, and phase-contrast MR was used to measure flow at baseline and at 20 ppm nitric oxide (NO). Total arterial compliance was calculated using the pulse pressure method (parameter optimization of the 2-element windkessel model) and the ratio of stroke volume to pulse pressure. There was good agreement between the two estimates of compliance (r = 0.98, P 10% in response to 20 ppm NO. As a population, the increase did not reach statistical significance. There was an inverse relation between compliance and resistance (r = 0.89, P < 0.001) and between compliance and mean pulmonary arterial pressure (r = 0.72, P < 0.001). We have demonstrated the feasibility of quantifying total arterial compliance using an MR method.

[bibtex-key = Muthurangu:AJP:05] [bibtex-entry]

Stéphane Nicolau, Alain Garcia, Xavier Pennec, Luc Soler, and Nicholas Ayache. An augmented reality system to guide radio-frequency tumor ablation. Computer Animation and Virtual World (previously the Journal of Visualization and Computer Animation), 16(1):1-10, 2005. [bibtex-key = Nicolau:CAVW:05] [bibtex-entry]

Xavier Pennec. Recaler pour mieux soigner. Pour la science, 338:126-131, December 2005. [bibtex-key = Pennec:PLS:05] [bibtex-entry]

K. Rhode, M. Sermesant, D. Brogan, S. Hegde, J. Hipwell, P. Lambiase, E. Rosenthal, C. Bucknall, S. Qureshi, J. Gill, R. Razavi, and D. Hill. A system for real-time XMR guided cardiovascular intervention. IEEE Transactions on Medical Imaging, 24(11):1428-1440, 2005. [bibtex-key = Rhode:TMI:05] [bibtex-entry]

M. Sermesant, K. Rhode, G. Sanchez-Ortiz, O. Camara, R. Andriantsimiavona, S. Hegde, D. Rueckert, P. Lambiase, C. Bucknall, E. Rosenthal, H. Delingette, D. Hill, N. Ayache, and R. Razavi. Simulation of Cardiac Pathologies using an Electromechanical Biventricular Model and XMR Interventional Imaging. Medical Image Analysis, 9(5):467-480, 2005. [bibtex-key = Sermesant:MEDIA:05] [bibtex-entry]

Radu Stefanescu, Xavier Pennec, and Nicholas Ayache. A Grid Service for the Interactive Use of a Parallel Non-Rigid Registration Algorithm of Medical Images. Methods of Information in Medicine, 44(2), 2005. Keyword(s): grid service, registration, non-rigid, parallel. [bibtex-key = Stefanescu:MIM:05] [bibtex-entry]

Xavier Pennec, Alexis Roche, Pascal Cathier, and Nicholas Ayache. Non-Rigid MR/US Registration for Tracking Brain Deformations. In R.S. Blum and Zh. Liu, editors, Multi-Sensor Image Fusion and Its Applications, volume 26 of Signal Processing and Communications, chapter 4, pages 107-143. CRC Press - Taylor and Francis, July 2005. Keyword(s): registration, matching, ultrasound, motion tracking, deformations, magnetic resonance, correlation ratio, robust estimation, multimodal. [bibtex-key = Pennec:Fusion:05] [bibtex-entry]

A. Pitiot, H. Delingette, and P.M. Thompson. Automated Image Segmentation: Issues and Applications. In Cornelius T. Leondes, editor, Medical Imaging Systems Technology, volume 3. World Scientific, 2005. [bibtex-key = pitiot:SegmentationReview:2005] [bibtex-entry]

J. Annese, A. Pitiot, I.D. Dinov, and A.W. Toga. A myelo-architectonic method for the structural classification of cortical areas. NeuroImage, 21(1):15-26, January 2004.

Keyword(s): Myelo-architecture, Cerebral cortex, Cortical areas. Abstract:

We describe an automatic and reproducible method to analyze the histological design of the cerebral cortex as applied to brain sections stained to reveal myelinated fibers. The technique provides an evaluation of the distribution of myelination across the width of the cortical mantle in accordance with a model of its curvature and its intrinsic geometry. The profile lines along which the density of staining is measured are generated from the solution of a partial differential equation (PDE) that models the intermediate layers of the cortex. Cortical profiles are classified according to significant components that emerge from wavelet analysis. Intensity profiles belonging to each distinct class are normalized and averaged to produce area-specific templates of cortical myelo-architecture.

[bibtex-key = pitiot:neuroimage:04] [bibtex-entry]

Christophe Blondel, Régis Vaillant, Grégoire Malandain, and Nicholas Ayache. 3-D tomographic reconstruction of coronary arteries using a precomputed 4-D motion field. Physics in Medicine and Biology, 49(11):2197-2208, 2004. [bibtex-key = blondel:pmb:2004] [bibtex-entry]

P.Y. Bondiau, G. Malandain, S. Chanalet, P.Y. Marcy, C. Foa, and N. Ayache. Traitement des images et radiothérapie. Cancer radiothérapie, 8(2):120-129, 2004.

Abstract:

La radioth{\'e}rapie est un domaine privil{\'e}gi{\'e} d'application des techniques de traitement des images de par l'utilisation importante de donn{\'e}es issues de l'imagerie. Celles-ci sont de plus en pleine expansion du fait de la progression des performances informatiques. Actuellement, les d{\'e}veloppements r{\'e}cents de la radioth{\'e}rapie (radioth{\'e}rapie de conformation, radioth{\'e}rapie conformationnelle avec modulation d'intensit{\'e}) procurent une place majeure {\`a} ces techniques. En effet, elles contribuent {\`a} r{\'e}pondre aux conditions de pr{\'e}cision exig{\'e}es par la radioth{\'e}rapie moderne et permettent d'envisager d'am{\'e}liorer les traitements. L'objectif de cet article est de pr{\'e}senter les diff{\'e}rentes techniques du traitement d'image utilis{\'e}es aujourd'hui en radioth{\'e}rapie (segmentation et recalage en particulier) au travers de la litt{\'e}rature.

[bibtex-key = bondiau:ct:2004] [bibtex-entry]

P. Cachier and N. Ayache. Isotropic energies, filters and splines for vectorial regularization. Journal of Mathematical Imaging and Vision, 20(3):251-265, May 2004. Keyword(s): vector field regularization, non-rigid registration, convolution filter, spline. [bibtex-key = Cachier-JMIV-2004] [bibtex-entry]

H. Delingette. Réalité Virtuelle et Médecine. Centraliens, 552:17-18, February 2004. [bibtex-key = Delingette:Centraliens:04] [bibtex-entry]

Miguel Angel González Ballester, Xavier Pennec, Marius George Linguraru, and Nicholas Ayache. Generalized Image Models and Their Application as Statistical Models of Images. Medical Image Analysis, 8(3):361-369, September 2004. [bibtex-key = Gonzalez:MedIA:04] [bibtex-entry]

Isabelle Klein, Jessica Dubois, Jean-François Mangin, Ferath Kherif, Guillaume Flandin, Jean-Baptiste Poline, Michel Denis, Stephen M. Kosslyn, and Denis LeBihan. Retinotopic organization of visual mental images as revealed by functional magnetic resonance imaging. Cognitive Brain Research, 22(1):26-31, December 2004.

Abstract:

In this study, we used event-related functional magnetic resonance imaging to investigate whether visual mental images retinotopically activate early visual cortex. Six participants were instructed to visualize or view horizontally or vertically oriented flashing bow-tie shaped stimuli. When compared to baseline, imagery globally activated Area V1. When the activation evoked by the stimuli at the different orientations was directly compared, distinct spatial activation patterns were obtained for each orientation in most participants. Not only was the topography of the activation patterns from imagery similar to the topography obtained with a corresponding visual perception task, but it closely matched the individual cortical representation of either the horizontal or the vertical visual field meridians. These findings strongly support that visual imagery and perception share low-level anatomical substrate and functional processes. Binding of spatial features is suggested as one possible mechanism.

[bibtex-key = klein:cbr:04] [bibtex-entry]

C Lebrun, D Rey, S Chanalet, V Bourg, C Bensa, M Chatel, N Ayache, and G Malandain. The contribution of automatic anatomical matching of sequential brain MRI scans in the monitoring of multiple sclerosis lesions. Revue Neurologique, 160(8-9):805-10, September 2004. Note: In French.

Keyword(s): multiple sclerosis. Abstract:

INTRODUCTION: Magnetic resonance imaging (MRI) has transformed management of patients with multiple sclerosis. The exact contribution of brain MRI remains a subject of debate, but it is generally considered to provide a more specific and more sensitive outcome measure for monitoring purposes and for testing new therapies. The choice of MRI techniques, and measurement reproducibility for multiple sclerosis brain lesions are not defined with precision for routine practice. There are many sources of error when comparing successive images which can be overcome to some extent with repositioning and image processing techniques. METHODS: We evaluated the impact of image repositioning on treatment decision-making for twelve relapsing remitting patients. Brain MRIs were performed every three months for a one-year period. Two neurologists interpreted the non-repositioned and repositioned images giving their analysis of changes in the lesions visualized on the T2 sequences and their therapeutic decisions. RESULTS: For the first neurologist, analysis of the non-repositioned images yielded six patients whose lesions had worsened while for the repositioned images there were only three. For the second neurologist, four patients had more lesions with the non-repositioned images and only three with repositioning. The subjective interpretations were the same for the two neurologists when they used repositioned images. CONCLUSIONS: Comparison by two neurologists of non-repositioned and repositioned MRI, with no other image processing, affected the analysis and in certain cases propositions for treatment.

[bibtex-key = lebrun:rn:2004] [bibtex-entry]

A. MacKenzie-Graham, E.F. Lee, I.D. Dinov, M. Bota, D.W. Shattuck, S. Ruffins, H. Yuan, F. Konstantinidis, A. Pitiot, Y. Ding, G. Hu, R.E. Jacobs, and A.W. Toga. A multimodal, multidimensional atlas of the C57BL/6J mouse brain. Journal of Anatomy, 204(2):93-102, February 2004.

Abstract:

Strains of mice, through breeding or the disruption of normal genetic pathways, are widely used to model human diseases. Atlases are an invaluable aid in understanding the impact of such manipulations by providing a standard for comparison. We have developed a digital atlas of the adult C57BL/6J mouse brain as a comprehensive framework for storing and accessing the myriad types of information about the mouse brain. Our implementation was constructed using several different imaging techniques: magnetic resonance microscopy, blockface imaging, classical histology and immunohistochemistry. Along with raw and annotated images, it contains database management systems and a set of tools for comparing information from different techniques. The framework allows facile correlation of results from different animals, investigators or laboratories by establishing a canonical representation of the mouse brain and providing the tools for the insertion of independent data into the same space as the atlas. This tool will aid in managing the increasingly complex and voluminous amounts of information about the mammalian brain. It provides a framework that encompasses genetic information in the context of anatomical imaging and holds tremendous promise for producing new insights into the relationship between genotype and phenotype. We describe a suite of tools that enables the independent entry of other types of data, facile retrieval of information and straightforward display of images. Thus, the atlas becomes a framework for managing complex genetic and epigenetic information about the mouse brain. The atlas and associated tools may be accessed at http://www.loni.ucla.edu/MAP.

[bibtex-key = pitiot:joa:2004] [bibtex-entry]

Grégoire Malandain, Éric Bardinet, Koen Nelissen, and Wim Vanduffel. Fusion of autoradiographs with an MR volume using 2-D and 3-D linear transformations. NeuroImage, 23(1):111-127, September 2004.

Abstract:

In the past years, the development of 3-D medical imaging has enabled the 3-D imaging of in vivo tissues, from an anatomical (MR, CT) or even functional (fMRI, PET, SPECT) point of view. However, despite immense technological progress, the resolution of these images is still short of the level of anatomical or functional details that in vitro imaging (e.g. histology, autoradiography) permits. The motivation of this work is to compare fMRI activations to activations observed in autoradiographic images from the same animals. We aim to fuse post-mortem autoradiographic data with a pre-mortem anatomical MR image. We first reconstruct a 3-D volume from the 2-D autoradiographic sections, coherent both in geometry and intensity. Then, this volume is fused with the MR image. This way, we ensure that the reconstructed 3-D volume can be superimposed onto the MR image that represents the reference anatomy. We demonstrate that this fusion can be achieved by using only simple global transformations (rigid and/or affine, 2-D and 3-D), while yielding very satisfactory results.

[bibtex-key = malandain:ni:2004] [bibtex-entry]

R.R. Peeters, P. Kornprobst, M. Nikolova, S. Sunaert, T. Vieville, G. Malandain, R. Deriche, O. Faugeras, M. Ng, and P. Van Hecke. The use of superresolution techniques to reduce slice thickness in functional MRI. International Journal of Imaging Systems and Technology, 14(3):131-138, 2004. Note: Special issue on High Resolution Image Reconstruction.

Keyword(s): fMRI, Super-Resolution algorithm, SNR. Abstract:

The problem of increasing the slice resolution of functional MRI (fMRI) images without a loss in signal-to-noise ratio is considered. In standard fMRI experiments, increasing the slice resolution by a certain factor decreases the signal-to-noise ratio of the images with the same factor. For this purpose an adapted EPI MRI acquisition protocol is proposed, allowing one to acquire slice-shifted images from which one can generate interpolated super-resolution images, with an increased resolution in the slice direction. To solve the problem of correctness and robustness of the created super-resolution images from these slice-shifted datasets, the use of discontinuity preserving regularization methods is proposed. Tests on real morphological, synthetic functional, and real functional MR datasets have been performed, by comparing the obtained super-resolution datasets with high-resolution reference datasets. In the morphological experiments the image spatial resolution of the different types of images are compared. In the synthetic and real fMRI experiments, on the other hand, the quality of the different datasets is studied as function of their resulting activation maps. From the results obtained in this study, we conclude that the proposed super-resolution techniques can both improve the signal-to-noise ratio and augment the detectability of small activated areas in fMRI image sets acquired with thicker slices.

[bibtex-key = peeters-kornprobst:ijist:2004] [bibtex-entry]

A. Pitiot, H. Delingette, P. M. Thompson, and N. Ayache. Expert Knowledge Guided Segmentation System for Brain MRI. NeuroImage, 23(supplement 1):S85-S96, 2004. Note: Special Issue: Mathematics in Brain Imaging. [bibtex-key = Pitiot:Neuroimage:2004] [bibtex-entry]

M. Sermesant, K. Rhode, S. Hegde, G. Sanchez-Ortiz, D. Rueckert, P. Lambiase, C. Bucknall, D. Hill, and R. Razavi. Electromechanical Modelling of the Myocardium using XMR Interventional Imaging. Journal of Cardiovascular Magnetic Resonance, 6(1):123-125, 2004. Note: Abstract. [bibtex-key = Sermesant:JCMR:04] [bibtex-entry]

Olivier Simon, Ferath Kherif, Guillaume Flandin, Jean-Baptiste Poline, Denis Rivière, Jean-François Mangin, Denis LeBihan, and Stanislas Dehaene. Automatized clustering and functional geometry of human parietofrontal networks for language, space, and number. NeuroImage, 23(3):1192-1202, November 2004.

Abstract:

Human functional MRI studies frequently reveal the joint activation of parietal and of lateral and mesial frontal areas during various cognitive tasks. To analyze the geometrical organization of those networks, we used an automatized clustering algorithm that g parcels out sets of areas based on their similar profile of task-related activations or deactivations. This algorithm allowed us to reanalyze published fMRI data (Simon, O., Mangin, J.F., Cohen, L., Le Bihan, D., Dehaene, S., 2002. Topographical layout of hand, eye, calculation, and language-related areas in the human parietal lobe. Neuron 33, 475-487) and to reproduce the previously observed geometrical organization of activations for saccades, attention, grasping, pointing, calculation, and language processing in the parietal lobe. Further, we show that this organization extends to lateral and mesial prefrontal regions. Relative to the parietal lobe, the prefrontal functional geometry is characterized by a partially symmetrical anteroposterior ordering of activations, a decreased representation of effector-specific tasks, and a greater emphasis on higher cognitive functions of attention, higher-order spatial representation, calculation, and language. Anatomically, our results in humans are closely homologous to the known connectivity of parietal and frontal regions in the macaque monkey.

[bibtex-key = simon:neuroimage:04] [bibtex-entry]

Luc Soler, Nicholas Ayache, Stéphane Nicolau, Xavier Pennec, Clément Forest, Hervé Delingette, and Jacques Marescaux. Traitement d'images médicales pour la planification, la simulation et l'aide intra-opératoire des actes chirurgicaux. La Revue de l'Electricité et de l'Electronique, pp 64-71, janvier 2004. [bibtex-key = Soler:Electricien:2004] [bibtex-entry]

Radu Stefanescu, Xavier Pennec, and Nicholas Ayache. Grid Powered Nonlinear Image Registration with Locally Adaptive Regularization. Medical Image Analysis, 8(3):325-342, September 2004. Keyword(s): non-rigid registration, adaptive regularization, grid, parallel. [bibtex-key = Stefanescu:MEDIA:04] [bibtex-entry]

Radu Stefanescu, Xavier Pennec, and Nicholas Ayache. Grid-Enabled Non-Rigid Registration of Medical Images. Parallel Processing Letters, 14(2):197-216, 2004. Keyword(s): grid, non-rigid registration, parallel, cluster. [bibtex-key = Stefanescu:PPL:04] [bibtex-entry]

H. Delingette and N. Ayache. Soft Tissue Modeling for Surgery Simulation. In N. Ayache, editor, Computational Models for the Human Body, Handbook of Numerical Analysis (Ed : Ph. Ciarlet), pages 453-550. Elsevier, 2004. [bibtex-key = Delingette:HNA:04] [bibtex-entry]

Luc Soler, Nicholas Ayache, Stéphane Nicolau, Xavier Pennec, Clément Forest, Hervé Delingette, Didier Mutter, and Jacques Marescaux. Traitements d'images médicales pour la planification, la simulation et l'aide intra-opératoire des actes chirurgicaux. In M. Faupel, P. Smigielski, and R. Grzymala, editors, Imagerie et Photonique pour les sciences du vivant et la médecine, pages 19-31. Edition Fontis Media, 2004. ISBN: 2-88476-005-9. [bibtex-key = Soler:ImageriePhotonique:2004] [bibtex-entry]

N. Ayache. Epidaure: a Research Project in Medical Image Analysis, Simulation and Robotics at INRIA. IEEE Transactions on Medical Imaging, 22(10):1185-1201, October 2003. [bibtex-key = Ayache-edito-TMI03] [bibtex-entry]

Pierre-Yves Bondiau, Grégoire Malandain, Pierre Chauvel, Frédérique Peyrade, Adel Courdi, Nicole Iborra, Jean-Pierre Caujolle, and Pierre Gastaud. Automatic three-dimensional model for protontherapy of the eye: Preliminary results. Medical Physics, 30(6):1013-1020, June 2003. Abstract:

Recently, radiotherapy possibilities have been dramatically increased by software and hardware developments. Improvements in medical imaging devices have increased the importance of three-dimensional (3D) images as the complete examination of these data by a physician is not possible. Computer techniques are needed to present only the pertinent information for clinical applications. We describe a technique for an automatic 3D reconstruction of the eye and CT scan merging with fundus photographs (retinography). The final result is a "virtual eye" to guide ocular tumor protontherapy. First, we make specific software to automatically detect the position of the eyeball, the optical nerve, and the lens in the CT scan. We obtain a 3D eye reconstruction using this automatic method. Second, we describe the retinography and demonstrate the projection of this modality. Then we combine retinography with a reconstructed eye, using a CT scan to get a virtual eye. The result is a computer 3D scene rendering a virtual eye into a skull reconstruction. The virtual eye can be useful for the simulation, the planning, and the control of ocular tumor protontherapy. It can be adapted to treatment planning to automatically detect eye and organs at risk position. It should be highlighted that all the image processing is fully automatic to allow the reproduction of results, this is a useful property to conduct a consistent clinical validation. The automatic localization of the organ at risk in a CT scan or an MRI by automatic software could be of great interest for radiotherapy in the future for comparison of one patient at different times, the comparison of different treatments centers, the possibility of pooling results of different treatments centers, the automatic generation of doses-volumes histograms, the comparison between different treatment planning for the same patient and the comparison between different patients at the same time. It will also be less time consuming.

[bibtex-key = bondiau-malandain-al:mp:2003] [bibtex-entry]

Pascal Cachier, Eric Bardinet, Didier Dormont, Xavier Pennec, and Nicholas Ayache. Iconic Feature Based Nonrigid Registration: The PASHA Algorithm. Computer Vision and Image Understanding, 89(2-3):272-298, Feb.-march 2003. Note: Special Issue on Nonrigid Registration. Keyword(s): registration, matching, similarity measures, deformations. [bibtex-key = Cachier:CVIU:03] [bibtex-entry]

Olivier Clatz, Hervé Delingette, Eric Bardinet, Didier Dormont, and Nicholas Ayache. Création d'un Modèle Biomécanique Spécifique du Cerveau par l'Analyse d'Images et son Application à la Neurochirurgie Stéréotaxique. Mécanique et Industrie, 4(4):429-433, 2003. Note: Numéro spécial CFM 2003. [bibtex-key = Clatz:Mec_et_ind:03] [bibtex-entry]

P Hellier, C Barillot, I Corouge, B Gibaud, G Le Goualher, D L Collins, A Evans, G Malandain, N Ayache, G E Christensen, and H J Johnson. Retrospective evaluation of intersubject brain registration. IEEE Transactions on Medical Imaging, 22(9):1120-30, September 2003.

Abstract:

Although numerous methods to register brains of different individuals have been proposed, no work has been done, as far as we know, to evaluate and objectively compare the performances of different nonrigid (or elastic) registration methods on the same database of subjects. In this paper, we propose an evaluation framework, based on global and local measures of the relevance of the registration. We have chosen to focus more particularly on the matching of cortical areas, since intersubject registration methods are dedicated to anatomical and functional normalization, and also because other groups have shown the relevance of such registration methods for deep brain structures. Experiments were conducted using 6 methods on a database of 18 subjects. The global measures used show that the quality of the registration is directly related to the transformation's degrees of freedom. More surprisingly, local measures based on the matching of cortical sulci did not show significant differences between rigid and non rigid methods.

[bibtex-key = hellier:tmi:2003] [bibtex-entry]

Ferath Kherif, Jean-Baptiste Poline, Sébastien Meriaux, Habib Benali, Guillaume Flandin, and Matthew Brett. Group analysis in functional neuroimaging: selecting subjects using similarity measures. NeuroImage, 20(4):2197-2208, December 2003.

Keyword(s): fMRI, Group analysis, Multivariate analysis, Statistical analysis. Abstract:

Standard group analyses of fMRI data rely on spatial and temporal averaging of individuals. This averaging operation is only sensible when the mean is a good representation of the group. This is not the case if subjects are not homogeneous, and it is therefore a major concern in fMRI studies to assess this group homogeneity. We present a method that provides relevant distances or similarity measures between temporal series of brain functional images belonging to different subjects. The method allows a multivariate comparison between data sets of several subjects in the time or in the space domain. These analyses assess the global intersubject variability before averaging subjects and drawing conclusions across subjects, at the population level. We adapt the RV coefficient to measure meaningful spatial or temporal similarities and use multidimensional scaling to give a visual representation of each subject's position with respect to other subjects in the group. We also provide a measure for detecting subjects that may be outliers. Results show that the method is a powerful tool to detect subjects with specific temporal or spatial patterns, and that, despite the apparent loss of information, restricting the analysis to a homogeneous subgroup of subjects does not reduce the statistical sensitivity of standard group fMRI analyses.

[bibtex-key = Kherif:NeuroImage:03] [bibtex-entry]

Pierre-Jean Lahaye, Jean-Baptiste Poline, Guillaume Flandin, Silke Dodel, and Line Garnero. Functional connectivity: studying nonlinear, delayed interactions between BOLD signals. NeuroImage, 20(2):962-974, October 2003. Keyword(s): fMRI. [bibtex-key = Lahaye:NeuroImage:03] [bibtex-entry]

J. Montagnat, M. Sermesant, H. Delingette, G. Malandain, and N. Ayache. Anisotropic filtering for model-based segmentation of 4D cylindrical echocardiographic images. Pattern Recognition Letters, 24(4-5):815-828, February 2003. Note: Special Issue on Ultrasonic Image Processing and Analysis. Keyword(s): anisotropic diffusion, 4D, Heart, segmentation, ultrasound, medical images, motion tracking. [bibtex-key = Montagnat:PattRecLetters:03] [bibtex-entry]

Xavier Pennec, Pascal Cachier, and Nicholas Ayache. Tracking Brain Deformations in Time-Sequences of 3D US Images. Pattern Recognition Letters, 24(4-5):801-813, February 2003. Note: Special Issue on Ultrasonic Image Processing and Analysis. Keyword(s): registration, matching, ultrasound, motion tracking, deformations. [bibtex-key = Pennec:Cachier:PattRecLetters:03] [bibtex-entry]

G. Picinbono, H. Delingette, and N. Ayache. Non-Linear Anisotropic Elasticity for Real-Time Surgery Simulation. Graphical Models, 65(5):305-321, September 2003. Keyword(s): journal, simulation. [bibtex-key = Picinbono:GraphMod:03] [bibtex-entry]

Maxime Sermesant, Clément Forest, Xavier Pennec, Hervé Delingette, and Nicholas Ayache. Deformable biomechanical models: Application to 4D cardiac image analysis. Medical Image Analysis, 7(4):475-488, December 2003. [bibtex-key = Sermesant:Media:03] [bibtex-entry]

J. Yelnik, P. Damier, S. Demeret, D. Gervais, E. Bardinet, B.P. Bejjani, C. Francois, J.L. Houeto, I. Arnule, D. Dormont, D. Galanaud, B. Pidoux, P. Cornu, and Y. Agid. Localization of stimulating electrodes in patients with Parkinson disease by using a three-dimensional atlas-magnetic resonance imaging coregistration method. Journal of Neurosurgery, 99(1):89-99, July 2003. Abstract:

OBJECT: The aim of this study was to correlate the clinical improvement in patients with Parkinson disease (PD) treated using deep brain stimulation (DBS) of the subthalamic nucleus (STN) with the precise anatomical localization of stimulating electrodes. METHODS: Localization was determined by superimposing figures from an anatomical atlas with postoperative magnetic resonance (MR) images obtained in each patient. This approach was validated by an analysis of experimental and clinical MR images of the electrode, and the development of a three-dimensional (3D) atlas-MR imaging coregistration method. The PD motor score was assessed through two contacts for each of two electrodes implanted in 10 patients: the "therapeutic contact" and the "distant contact" (that is, the next but one to the therapeutic contact). Seventeen therapeutic contacts were located within or on the border of the STN, most of which were associated with significant improvement of the four PD symptoms tested. Therapeutic contacts located in other structures (zona incerta, lenticular fasciculus, or midbrain reticular formation) were also linked to a significant positive effect. Stimulation applied through distant contacts located in the STN improved symptoms of PD, whereas that delivered through distant contacts in the remaining structures had variable effects ranging from worsening of symptoms to their improvement. CONCLUSIONS: The authors have demonstrated that 3D atlas-MR imaging coregistration is a reliable method for the precise localization of DBS electrodes on postoperative MR images. In addition, they have confirmed that although the STN is the main target during DBS treatment for PD, stimulation of surrounding regions, particularly the zona incerta or the lenticular fasciculus, can also improve symptoms of PD.

[bibtex-key = Yelnik:JNeuroSurg:03] [bibtex-entry]

M. A. González Ballester, A. Zisserman, and M. Brady. Estimation of the Partial Volume Effect in MRI. Medical Image Analysis, 6(4):389-405, December 2002. [bibtex-key = Gonzalez:Media:02] [bibtex-entry]

P. Jannin, J.M. Fitzpatrick, D.J. Hawkes, X. Pennec, R. Shahidi, and M.W. Vannier. Validation of Medical Image Processing in Image-guided Therapy. IEEE Transactions on Medical Imaging, 21(12):1445-1449, December 2002. [bibtex-key = Jannin-edito-TMI02] [bibtex-entry]

Carine Karachi, Chantal François, Karine Parain, Eric Bardinet, Dominique Tandé, Etienne Hirsch, and Jérôme Yelnik. Three-dimensional cartography of functional territories in the human striatopallidal complex by using calbindin immunoreactivity. Journal of Comparative Neurology, 450(2):122-134, August 2002. Abstract:

This anatomic study presents an analysis of the distribution of calbindin immunohistochemistry in the human striatopallidal complex. Entire brains were sectioned perpendicularly to the mid-commissural line into 70-microm-thick sections. Every tenth section was immunostained for calbindin. Calbindin labeling exhibited a gradient on the basis of which three different regions were defined: poorly labeled, strongly labeled, and intermediate. Corresponding contours were traced in individual sections and reformatted as three-dimensional structures. The poorly labeled region corresponded to the dorsal part of the striatum and to the central part of the pallidum. The strongly labeled region included the ventral part of the striatum, the subcommissural part of the external pallidum but also the adjacent portion of its suscommissural part, and the anterior pole of the internal pallidum. The intermediate region was located between the poorly and strongly labeled regions. As axonal tracing and immunohistochemical studies in monkeys show a similar pattern, poorly, intermediate, and strongly labeled regions were considered as the sensorimotor, associative, and limbic territories of the human striatopallidal complex, respectively. However, the boundaries between these territories were not sharp but formed gradients of labeling, which suggests overlapping between adjacent territories. Similarly, the ventral boundary of the striatopallidal complex was blurred, suggesting a structural intermingling with the substantia innominata. This three-dimensional partitioning of the human striatopallidal complex could help to define functional targets for high-frequency stimulation with greater accuracy and help to identify new stimulation sites.

[bibtex-key = Bardinet:CompNeurol:2002] [bibtex-entry]

Ferath Kherif, Jean-Baptiste Poline, Guillaume Flandin, Habib Benali, Olivier Simon, Stanislas Dehaene, and Keith J. Worsley. Multivariate Model Specification for fMRI Data. NeuroImage, 16(4):1068-1083, August 2002. Keyword(s): fMRI, model selection, multivariate analysis. [bibtex-key = Kherif:NeuroImage:02] [bibtex-entry]

Grégoire Malandain and Jean-Daniel Boissonnat. Computing the Diameter of a Point Set. International Journal of Computational Geometry & Applications, 12(6):489-510, December 2002.

Keyword(s): computational geometry, diameter, width, approximation, point sets, furthest neighbors, double normal. Abstract:

Given a finite set of points ${\cal P}$ in ${\R}^d$, the diameter of $\cal P$ is defined as the maximum distance between two points of $\cal P$. We propose a very simple algorithm to compute the diameter of a finite set of points. Although the algorithm is not worst-case optimal, an extensive experimental study has shown that it is extremely fast for a large variety of point distributions. In addition, we propose a comparison with the recent approach of Har-Peled and derive hybrid algorithms to combine advantages of both approaches.

[bibtex-key = malandain-boissonnat:ijcga:2002] [bibtex-entry]

G. Picinbono, H. Delingette, and N. Ayache. Modèle déformable élastique non-linéaire pour la simulation de chirurgie en temps réel. Les Comptes Rendus de l'Académie des Sciences (CRAS), C.R. Biologies, 325(4):335-344, 2002. Keyword(s): journal, simulation. [bibtex-key = Picinbono-CRAS02] [bibtex-entry]

G. Picinbono, J-C. Lombardo, H. Delingette, and N. Ayache. Improving realism of a surgery simulator: linear anisotropic elasticity, complex interactions and force extrapolation. Journal of Visualisation and Computer Animation, 13(3):147-167, July 2002. Keyword(s): journal, simulation. [bibtex-key = Picinbono:VCA:01] [bibtex-entry]

Alain Pitiot, Paul M. Thompson, and Arthur W. Toga. Adaptive Elastic Segmentation of Brain MRI via Shape Model Guided Evolutionary Programming. IEEE Transactions on Medical Imaging, 21(8):910-923, August 2002. Keyword(s): MRI. [bibtex-key = Pitiot:TMI:02] [bibtex-entry]

S. Prima, S. Ourselin, and N. Ayache. Computation of the Mid-Sagittal Plane in 3D Brain Images. IEEE Transactions on Medical Imaging, 21(2):122-138, February 2002. Keyword(s): registration, matching. [bibtex-key = Prima:TMI:02] [bibtex-entry]

David Rey, Gérard Subsol, Hervé Delingette, and Nicholas Ayache. Automatic Detection and Segmentation of Evolving Processes in 3D Medical Images: Application to Multiple Sclerosis. Medical Image Analysis, 6(2):163-179, June 2002.

Keyword(s): Automation, Brain, pathology, Human, Image Processing Computer-Assisted, methods, Imaging Three-Dimensional, methods, Magnetic Resonance Imaging, methods, Models Neurological, Multiple Sclerosis, diagnosis, Reproducibility of Results, Sensitivity and Specificity, Support Non-U.S. Gov't. Abstract:

The study of temporal series of medical images can be helpful for physicians to perform pertinent diagnoses and to help them in the follow-up of a patient: in some diseases, lesions, tumors or anatomical structures vary over time in size, position, composition, etc., either because of a natural pathological process or under the effect of a drug or a therapy. It is a laborious and subjective task to visually and manually analyze such images. Thus the objective of this work was to automatically detect regions with apparent local volume variation with a vector field operator applied to the local displacement field obtained after a non-rigid registration between two successive temporal images. On the other hand, quantitative measurements, such as the volume variation of lesions or segmentation of evolving lesions, are important. By studying the information of apparent shrinking areas in the direct and reverse displacement fields between images, we are able to segment evolving lesions. Then we propose a method to segment lesions in a whole temporal series of images. In this article we apply this approach to automatically detect and segment multiple sclerosis lesions that evolve in time series of MRI scans of the brain. At this stage, we have only applied the approach to a few experimental cases to demonstrate its potential. A clinical validation remains to be done, which will require important additional work.

[bibtex-key = Rey:MEDIA:02] [bibtex-entry]

N. Ayache. Medical Imaging Informatics. From Digital Anatomy to Virtual Scapels and Image Guided Therapy. In R Haux and C Kulikowski, editors, Medical Imaging Informatics (IMIA Yearbook of Medical Informatics). Schattauer Verlagsgesellschaft mbH, Stuttgart, 2002. ISBN: 3-7945-2193-5. [bibtex-key = Ayache:IMIA:02] [bibtex-entry]

G. Subsol, B. Mafart, A. Silvestre, and M.A. de Lumley. 3D Image Processing for the Study of the Evolution of the Shape of the Human Skull: Presentation of the Tools and Preliminary Results. In B. Mafart, H. Delingette, and G. Subsol, editors, Three-Dimensional Imaging in Paleoanthropology and Prehistoric Archaeology, pages 37-45. BAR International Series 1049, 2002. [bibtex-key = Subsol-BAR-2002] [bibtex-entry]

H. Delingette and J. Montagnat. Shape and Topology Constraints on Parametric Active Contours. Computer Vision and Image Understanding, 83(2):140-171, 2001. Keyword(s): journal, reconstruction. [bibtex-key = Delingette:CVIU:01] [bibtex-entry]

A. Guimond, A. Roche, N. Ayache, and J. Meunier. Multimodal Brain Warping Using the Demons Algorithm and Adaptative Intensity Corrections. IEEE Transactions on Medical Imaging, 20(1):58-69, 2001.

Keyword(s): registration, matching, deformations. Abstract:

This paper presents an original method for three-dimensional elastic registration of multimodal images. We propose to make use of a scheme that iterates between correcting for intensity differences between images and performing standard monomodal registration. The core of our contribution resides in providing a method that finds the transformation that maps the intensities of one image to those of another. It makes the assumption that there are at most two functional dependencies between the intensities of structures present in the images to register, and relies on robust estimation techniques to evaluate these functions. We provide results showing successful registration between several imaging modalities involving segmentations, T1 magnetic resonance (MR), T2 MR, proton density (PD) MR and computed tomography (CT). We also argue that our intensity modeling may be more appropriate than mutual information (MI) in the context of evaluating high-dimensional deformations, as it puts more constraints on the parameters to be estimated and, thus, permits a better search of the parameter space.

[bibtex-key = Guimon:Roche:TMI:01] [bibtex-entry]

M.G. Linguraru and J.M. Brady. An Anisotropic Diffusion Approach for Early Detection of Breast Cancer. Acta Universitatis Cibiniensis, Technical Series, XLIII:49-60, 2001. [bibtex-key = Linguraru:Acta:01] [bibtex-entry]

Y. Machida, Y. Hamamura, M. A. González Ballester, S. Nozaki, K. Okamoto, S. Uchizono, N. Ichinose, Y. Kassai, H. Kanazawa, and Y. Usui. Development of MR Parallel Imaging, SPEEDER (in Japanese). Medical Review, 83:52-58, November 2001. [bibtex-key = Gonzalez:MedReview:2001] [bibtex-entry]

O. Migneco, M. Benoit, P.M. Koulibaly, I. Dygai, C. Bertogliati, P. Desvignes, Ph. Robert, G. Malandain, F. Bussière, and J. Darcourt. Perfusion brain SPECT and Statistical Parametric Mapping analysis indicate that apathy is a cingulate syndrome: a study in Alzheimer's disease and non-demented patients. NeuroImage, 13(5):896-902, 2001.

Keyword(s): apathy, cingulate, statistical parametric mapping, ECD. Abstract:

Apathy is the most frequent behavioral symptom in Alzheimer's disease and is also frequently reported in other brain organic disorders occurring in the elderly. Based on the literature, we hypothesized that apathy was related to an anterior cingulate hypofunction. Forty-one subjects were studied. According to ICD 10 diagnostic criteria, 28 patients had Alzheimer dementia (demented: diagnostic group 1), and 13 had organic personality disorders or mild cognitive impairment not attributable to dementia (nondemented: diagnostic group 2). Apathy was evaluated by the Neuro-Psychiatric Inventory. As a result each diagnostic group was divided into two symptomatic subgroups: apathetic or nonapathetic. Brain perfusion was measured by 99mTc-labeled bicisate (ECD) brain SPECT and the images were compared using Statistical Parametric Mapping (SPM96). We began by comparing apathetic vs nonapathetic patients, whatever their diagnostic group (whole population), then analyzed them within each group. Twenty-one subjects were apathetic (14 in group 1 and 7 in group 2) and 20 were not (14 in group 1 and 6 in group 2). For the whole population, the Z map showed a significant decrease in ECD uptake for the apathetic patients in the anterior cingulate (P < 0.002) bilaterally. This area was also identified as hypoactive by SPM analysis in the demented (P < 0.035) and in the nondemented (P < 0.02) apathetic patient groups. Finally, conjunction analysis indicated that the anterior cingulate was the common hypoactive structure of the two apathetic subgroups (Z = 4.35, P < 0.0009). These results point to a close relationship between apathy and the anterior cingulate region.

[bibtex-key = Migneco:Neuroimage:01] [bibtex-entry]

J. Montagnat, H. Delingette, and N. Ayache. A review of deformable surfaces: topology, geometry and deformation. Image and Vision Computing, 19(14):1023-1040, December 2001. Keyword(s): journal, reconstruction. [bibtex-key = Montagnat:IVC:01] [bibtex-entry]

Sébastien Ourselin, Alexis Roche, Gérard Subsol, Xavier Pennec, and Nicholas Ayache. Reconstructing a 3D Structure from Serial Histological Sections. Image and Vision Computing, 19(1-2):25-31, January 2001. Keyword(s): registration, matching, histology. [bibtex-key = Ourselin:IVC:01] [bibtex-entry]

Alexis Roche, Xavier Pennec, Grégoire Malandain, and Nicholas Ayache. Rigid Registration of 3D Ultrasound with MR Images: a New Approach Combining Intensity and Gradient Information. IEEE Transactions on Medical Imaging, 20(10):1038-1049, October 2001.

Keyword(s): registration, ultrasound, magnetic resonance, correlation ratio, robust estimation, multimodal. Abstract:

We present a new image-based technique to rigidly register intraoperative three-dimensional ultrasound (US) with preoperative magnetic resonance (MR) images. Automatic registration is achieved by maximization of a similarity measure which generalizes the correlation ratio, and whose novelty is to incorporate multivariate information from the MR data (intensity and gradient). In addition, the similarity measure is built upon a robust intensity-based distance measure, which makes it possible to handle a variety of US artifacts. A cross-validation study has been carried out using a number of phantom and clinical data. This indicates that the method is quite robust and that the worst registration errors are of the order of the MR image resolution.

[bibtex-key = Roche:TMI:01] [bibtex-entry]

L Soler, H Delingette, G Malandain, J Montagnat, N Ayache, C Koehl, O Dourthe, B Malassagne, M Smith, D Mutter, and J Marescaux. Fully automatic anatomical, pathological, and functional segmentation from CT scans for hepatic surgery. Comput Aided Surg, 6(3):131-42, 2001.

Keyword(s): Human, Image Processing Computer-Assisted, methods, Liver, anatomy & histology, Support Non-U.S. Gov't, Surgery Computer-Assisted, Tomography X-Ray Computed. Abstract:

OBJECTIVE: To improve the planning of hepatic surgery, we have developed a fully automatic anatomical, pathological, and functional segmentation of the liver derived from a spiral CT scan. MATERIALS AND METHODS: From a 2 mm-thick enhanced spiral CT scan, the first stage automatically delineates skin, bones, lungs, kidneys, and spleen by combining the use of thresholding, mathematical morphology, and distance maps. Next, a reference 3D model is immersed in the image and automatically deformed to the liver contours. Then an automatic Gaussian fitting on the imaging histogram estimates the intensities of parenchyma, vessels, and lesions. This first result is next improved through an original topological and geometrical analysis, providing an automatic delineation of lesions and veins. Finally, a topological and geometrical analysis based on medical knowledge provides hepatic functional information that is invisible in medical imaging: portal vein labeling and hepatic anatomical segmentation according to the Couinaud classification. RESULTS: Clinical validation performed on more than 30 patients shows that delineation of anatomical structures by this method is often more sensitive and more specific than manual delineation by a radiologist. CONCLUSION: This study describes the methodology used to create the automatic segmentation of the liver with delineation of important anatomical, pathological, and functional structures from a routine CT scan. Using the methods proposed in this study, we have confirmed the accuracy and utility of the creation of a 3D liver model compared with the conventional reading of the CT scan by a radiologist. This work may allow improved preoperative planning of hepatic surgery by more precisely delineating liver pathology and its relationship to normal hepatic structures. In the future, this data may be integrated with computer-assisted surgery and thus represents a first step towards the development of an augmented-reality surgical system.

[bibtex-key = soler:cas:2001] [bibtex-entry]

N. Ayache. Imagerie et robotique médicales: du microscope informatique au simulateur de chirurgie. Technique et Science Informatiques, 19(1), January 2000. [bibtex-key = ayache2000] [bibtex-entry]

S. Cotin, H. Delingette, and N. Ayache. A Hybrid Elastic Model allowing Real-Time Cutting, Deformations and Force-Feedback for Surgery Training and Simulation. The Visual Computer, 16(8):437-452, 2000. Keyword(s): journal, simulation. [bibtex-key = cotinVisualComputer] [bibtex-entry]

J. Duncan and N. Ayache. Medical Image Analysis: Progress over two decades and the challenges ahead. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(1):85-106, 2000. [bibtex-key = ayache2000b] [bibtex-entry]

M. A. González Ballester, A. Zisserman, and M. Brady. Segmentation and Measurement of Brain Structures in MRI Including Confidence Bounds. Medical Image Analysis, 4(3):189-200, 2000. [bibtex-key = Gonzalez:Media:2000] [bibtex-entry]

A. Guimond, J. Meunier, and J.-P. Thirion. Average Brain Models: A Convergence Study. Computer Vision and Image Understanding, 77(2):192-210, 2000. Keyword(s): atlas. [bibtex-key = guimond99.1] [bibtex-entry]

K. Krissian, G. Malandain, N. Ayache, R. Vaillant, and Y. Trousset. Model-Based Detection of Tubular Structures in 3D Images. Computer Vision and Image Understanding, 80(2):130-171, 2000.

Keyword(s): filtering, vessel detection, multiscale analysis, segmentation. Abstract:

Detection of tubular structures in 3D images is an important issue for vascular detection in medical imaging. We present in this paper a new approach for centerline detection and reconstruction of 3D tubular structures. Several models of vessels are introduced for estimating the sensivity of the image second order derivatives according to elliptical cross-section, to curvature of the axis, or to partial volume effects. Our approach uses a multiscale analysis for extracting vessels of different sizes according to the scale. For a given model of vessel, we derive an analytic expression of the relationship between the radius of the structure and the scale at which it is detected. The algorithm gives both centerline extraction and radius estimation of the vessels allowing their reconstruction. The method has been tested on both synthetic and real images, with encouraging results. This work was done in collaboration with GEMS (General Electric Medical Systems, Buc, France).

[bibtex-key = krissian-al2000] [bibtex-entry]

A. Roche, G. Malandain, and N. Ayache. Unifying Maximum Likelihood Approaches in Medical Image Registration. International Journal of Imaging Systems and Technology, 11(1):71-80, 2000. Note: Special Issue on 3D Imaging. Keyword(s): registration, matching, similarity measures. [bibtex-key = Roche:IJST:2000] [bibtex-entry]

L Soler, H Delingette, G Malandain, N Ayache, C Koehl, J M Clement, O Dourthe, and J Marescaux. An automatic virtual patient reconstruction from CT-scans for hepatic surgical planning. Stud Health Technol Inform, 70:316-22, 2000.

Keyword(s): Computer Graphics, Computer Simulation, Hepatectomy, Human, Image Processing Computer-Assisted, Liver Diseases, radiography, Tomography X-Ray Computed, User-Computer Interface. Abstract:

PROBLEM/BACKGROUND: In order to help hepatic surgical planning we perfected automatic 3D reconstruction of patients from conventional CT-scan, and interactive visualization and virtual resection tools. TOOLS AND METHODS: From a conventional abdominal CT-scan, we have developed several methods allowing the automatic 3D reconstruction of skin, bones, kidneys, lung, liver, hepatic lesions, and vessels. These methods are based on deformable modeling or thresholding algorithms followed by the application of mathematical morphological operators. From these anatomical and pathological models, we have developed a new framework for translating anatomical knowledge into geometrical and topological constraints. More precisely, our approach allows to automatically delineate the hepatic and portal veins but also to label the portal vein and finally to build an anatomical segmentation of the liver based on Couinaud definition which is currently used by surgeons all over the world. Finally, we have developed a user friendly interface for the 3D visualization of anatomical and pathological structures, the accurate evaluation of volumes and distances and for the virtual hepatic resection along a user-defined cutting plane. RESULTS: A validation study on a 30 patients database gives 2 mm of precision for liver delineation and less than 1 mm for all other anatomical and pathological structures delineation. An in vivo validation performed during surgery also showed that anatomical segmentation is more precise than the delineation performed by a surgeon based on external landmarks. This surgery planning system has been routinely used by our medical partner, and this has resulted in an improvement of the planning and performance of hepatic surgery procedures. CONCLUSION: We have developed new tools for hepatic surgical planning allowing a better surgery through an automatic delineation and visualization of anatomical and pathological structures. These tools represent a first step towards the development of an augmented reality system combined with computer assisted tele-robotical surgery.

[bibtex-key = soler:shti:2000] [bibtex-entry]

J.-P. Thirion, S. Prima, G. Subsol, and N. Roberts. Statistical Analysis of Normal and Abnormal Dissymmetry in Volumetric Medical Images. Medical Image Analysis, 4(2):111-121, June 2000.

Keyword(s): Aphasia, pathology, Brain, anatomy & histology, Computer Simulation, Epilepsies Partial, pathology, Human, Image Processing Computer-Assisted, Imaging Three-Dimensional, Laterality, Magnetic Resonance Imaging, Male. Abstract:

We present a general method to study the dissymmetry of anatomical structures such as those found in the human brain. Our method relies on the estimate of 3D dissymmetry fields, the use of 3D vector field operators, and T2 statistics to compute significance maps. We also present a fully automated implementation of this method which relies mainly on the intensive use of a 3D non-rigid inter-patient matching tool. Such a tool is applied successively between the images and their symmetric versions with respect to an arbitrary plane, both to realign the images with respect to the mid-plane of the subject and to compute a dense 3D dissymmetry map. Inter-patient matching is also used to fuse the data of a population of subjects. We then describe three main application fields: the study of the normal dissymmetry within a given population, the comparison of the dissymmetry between two populations, and the detection of the significant abnormal dissymmetries of a patient with respect to a reference population. Finally, we present preliminary results illustrating these three applications for the case of the human brain.

[bibtex-key = Thirion00a] [bibtex-entry]

Xavier Pennec, Nicholas Ayache, and Jean-Philippe Thirion. Landmark-based registration using features identified through differential geometry. In I. Bankman, editor, Handbook of Medical Imaging, chapter 31, pages 499-513. Academic Press, September 2000. Keyword(s): registration, matching, validation, uncertainty. [bibtex-key = Pennec:HMIP:00] [bibtex-entry]

N. Ayache and G. Subsol. El Cerebro in Cuatro Dimensiones. Mundo Cientifico, 203:30-33, July 1999. [bibtex-key = Ayache99] [bibtex-entry]

N. Ayache and G. Subsol. Le cerveau en quatre dimensions. La Recherche, 320:46-49, May 1999. [bibtex-key = Ayache99-1] [bibtex-entry]

S. Cotin, H. Delingette, and N. Ayache. Real-time elastic deformations of soft tissues for surgery simulation. IEEE Transactions on Visualization and Computer Graphics, 5(1):62-73, January-March 1999. Keyword(s): journal, simulation. [bibtex-key = cotin99] [bibtex-entry]

H. Delingette. General Object Reconstruction based on Simplex Meshes. International Journal of Computer Vision, 32(2):111-146, September 1999. Keyword(s): journal, reconstruction. [bibtex-key = delingette-ijcv99] [bibtex-entry]

J.-L. Dugelay, K. Fintzel, S. Valente, and H. Delingette. Clonage de visage et spatialisation video : Outils pour la téléconférence virtuelle. Traitement du signal, 16(1):60-72, July 1999. Keyword(s): journal, reconstruction. [bibtex-key = dugelay-tsi99] [bibtex-entry]

S. Ourselin, C. Sattonnet, A. Roche, and G. Subsol. Automatic alignement of histological sections for 3D reconstruction and analysis. Analytical Cellular Pathology, 18(3):123, 1999. Note: Abstracts of the 1999 Annual Meeting of the Association Française de Cytométrie, Dijon, 12-15 October 1999. Keyword(s): registration, matching, histology, MRI. [bibtex-key = Ourselin99.2] [bibtex-entry]

J.-P. Thirion and G. Calmon. Deformation Analysis to Detect and Quantify Active Lesions in Three-Dimensional Medical Image Sequences. IEEE Transactions on Medical Imaging, 18(5):429-441, 1999. Keyword(s): Lesion, mass effect, motion field analysis, multiple sclerosis, stereology, volume measurement. [bibtex-key = Thirion99] [bibtex-entry]

J. Webb, A. Guimond, N. Roberts, P. Eldridge, D. Chadwick, J. Meunier, and J.-P. Thirion. Automatic detection of hippocampal atrophy on magnetic resonance images. Magnetic Resonance Imaging, 17(8):1149-1161, April 1999. [bibtex-key = webb99.1] [bibtex-entry]

Nicholas Ayache. L'analyse automatique des images médicales, état de l'art et perspectives. Annales de l'Institut Pasteur, 9(1):13-21, avril--juin 1998. Note: Numéro spécial sur les progrès récents de l'imagerie médicale. [bibtex-key = ayache-pasteur98] [bibtex-entry]

N. Ayache, S. Cotin, H. Delingette, J.-M. Clément, J. Marescaux, and M. Nord. Simulation of Endoscopic Surgery. Journal of Minimally Invasive Therapy and Allied Technologies (MITAT), 7(2):71-77, July 1998. Keyword(s): journal, simulation. [bibtex-key = cotin_mitat] [bibtex-entry]

Eric Bardinet, Laurent D. Cohen, and Nicholas Ayache. A parametric deformable model to fit unstructured 3D data. Computer Vision and Image Understanding, 71(1):39-54, 1998. [bibtex-key = Bardinet:CVIU:98] [bibtex-entry]

Serge Benayoun and Nicholas Ayache. Dense non-rigid motion estimation in sequences of medical images using differential constraints. International Journal of Computer Vision, 26(1):25-40, 1998. Keyword(s): registration, matching, deformations, motion tracking. [bibtex-key = Benayoun:IJCV:98] [bibtex-entry]

J. Declerck, J. Feldmar, and N. Ayache. Definition of a four-dimensional continuous planispheric transformation for the tracking and the analysis of left-ventricle motion. Medical Image Analysis, 2(2):197-213, June 1998. Keyword(s): Motion tracking, Heart, 4D. [bibtex-key = Declerck-98.6] [bibtex-entry]

H. Delingette. Towards Realistic Soft Tissue Modeling in Medical Simulation. Proceedings of the IEEE, pp 512-523, April 1998. Note: Special Issue on Surgery Simulation. Keyword(s): journal, simulation. [bibtex-key = delingette_ieee98] [bibtex-entry]

Márta Fidrich. Iso-surface Extraction in $n$-D applied to Tracking Feature Curves across Scale. Image and Vision Computing, 16(8):545-556, 1998. [bibtex-key = Fidrich98d] [bibtex-entry]

Márta Fidrich and Jean-Philippe Thirion. Stability of Corner Points in Scale Space: The Effect of Small Non-Rigid Deformations. Computer Vision and Image Understanding, 72(1):72-83, 1998. [bibtex-key = Fidrich98b] [bibtex-entry]

G. Malandain and S. Fernández-Vidal. Euclidean Skeletons. Image and Vision Computing, 16(5):317-327, April 1998. [bibtex-key = malandain-vidal98] [bibtex-entry]

J Marescaux, J M Clement, V Tassetti, C Koehl, S Cotin, Y Russier, D Mutter, H Delingette, and N Ayache. Virtual reality applied to hepatic surgery simulation: the next revolution. Annals of Surgery, 228(5):627-34, November 1998. Keyword(s): Computer Simulation, Digestive System Surgical Procedures, methods, Image Processing Computer-Assisted, Liver, surgery, Support Non-U.S. Gov't, journal, simulation. Abstract:

OBJECTIVE: This article describes a preliminary work on virtual reality applied to liver surgery and discusses the repercussions of assisted surgical strategy and surgical simulation on tomorrow's surgery. SUMMARY BACKGROUND DATA: Liver surgery is considered difficult because of the complexity and variability of the organ. Common generic tools for presurgical medical image visualization do not fulfill the requirements for the liver, restricting comprehension of a patient's specific liver anatomy. METHODS: Using data from the National Library of Medicine, a realistic three-dimensional image was created, including the envelope and the four internal arborescences. A computer interface was developed to manipulate the organ and to define surgical resection planes according to internal anatomy. The first step of surgical simulation was implemented, providing the organ with real-time deformation computation. RESULTS: The three-dimensional anatomy of the liver could be clearly visualized. The virtual organ could be manipulated and a resection defined depending on the anatomic relations between the arborescences, the tumor, and the external envelope. The resulting parts could also be visualized and manipulated. The simulation allowed the deformation of a liver model in real time by means of a realistic laparoscopic tool. CONCLUSIONS: Three-dimensional visualization of the organ in relation to the pathology is of great help to appreciate the complex anatomy of the liver. Using virtual reality concepts (navigation, interaction, and immersion), surgical planning, training, and teaching for this complex surgical procedure may be possible. The ability to practice a given gesture repeatedly will revolutionize surgical training, and the combination of surgical planning and simulation will improve the efficiency of intervention, leading to optimal care delivery.

[bibtex-key = marescaux:as:1998] [bibtex-entry]

J Marescaux, J M Clement, M Vix, Y Russier, V Tassetti, D Mutter, S Cotin, and N Ayache. [A new concept in surgery of the digestive tract: surgical procedure assisted by computer, from virtual reality to telemanipulation]. Chirurgie, 123(1):16-24, February 1998. Note: In french. Keyword(s): Anatomy Cross-Sectional, Computer Simulation, English Abstract, Forecasting, Hepatectomy, instrumentation, Human, Image Processing Computer-Assisted, instrumentation, Liver Neoplasms, surgery, Phantoms Imaging, Robotics, instrumentation, Surgical Procedures Operative, trends, User-Computer Interface. Abstract:

Surgical simulation increasingly appears to be an essential aspect of tomorrow's surgery. The development of a hepatic surgery simulator is an advanced concept calling for a new writing system which will transform the medical world: virtual reality. Virtual reality extends the perception of our five senses by representing more than the real state of things by the means of computer sciences and robotics. It consists of three concepts: immersion, navigation and interaction. Three reasons have led us to develop this simulator: the first is to provide the surgeon with a comprehensive visualisation of the organ. The second reasons is to allow for planning and surgical simulation that could be compared with the detailed flight-plan for a commercial jet pilot. The third lies in the fact that virtual reality is an integrated part of the concept of computer assisted surgical procedure. The project consists of a sophisticated simulator which must include five requirements: a) visual fidelity, b) interactivity, c) physical properties, d) physiological properties, e) sensory input and output. In this report we describe how to obtain a realistic 3D model of the liver from bi-dimensional 2D medical images for anatomical and surgical training. The introduction of a tumor and the consequent planning and virtual resection is also described, as are force feedback and real-time interaction.

[bibtex-key = marescaux:chirurgie:1998] [bibtex-entry]

J. Montagnat and H. Delingette. Globally constrained deformable models for 3D object reconstruction. Signal Processing, 71(2):173-186, 1998. Keyword(s): journal, reconstruction. [bibtex-key = Montagnat-SPAIJ98] [bibtex-entry]

Xavier Pennec. Toward a generic framework for recognition based on uncertain geometric features. Videre: Journal of Computer Vision Research, 1(2):58-87, 1998. Keyword(s): registration, matching, uncertainty. [bibtex-key = Pennec:Videre:98] [bibtex-entry]

Xavier Pennec and Nicholas Ayache. A geometric algorithm to find small but highly similar 3D substructures in proteins. Bioinformatics, 14(6):516-522, 1998. Keyword(s): registration, matching, protein structure. [bibtex-key = Pennec:CABIOS:98] [bibtex-entry]

Xavier Pennec and Nicholas Ayache. Uniform distribution, distance and expectation problems for geometric features processing. Journal of Mathematical Imaging and Vision, 9(1):49-67, July 1998. Note: A preliminary version appeared as INRIA Research Report 2820, March 1996. Keyword(s): statistics, geometry, Riemannian geometry. [bibtex-key = Pennec:JMIV:98] [bibtex-entry]

L. Robert and G. Malandain. Fast Binary Image Processing Using Binary Decision Diagrams. Computer Vision and Image Understanding, 72(1):1-9, October 1998. [bibtex-key = robert-al98] [bibtex-entry]

L. Soler, G. Malandain, and H. Delingette. Segmentation automatique : application aux angioscanners 3D du foie. Traitement du signal, 15(5):411-431, 1998. Keyword(s): journal, reconstruction. [bibtex-key = soler-tsi98] [bibtex-entry]

G. Subsol, J.-Ph. Thirion, and N. Ayache. A Scheme for Automatically Building 3D Morphometric Anatomical Atlases: application to a Skull Atlas. Medical Image Analysis, 2(1):37-60, 1998.

Keyword(s): registration, matching, atlas, deformations, Algorithms, Anatomy Artistic, methods, Comparative Study, Craniofacial Abnormalities, pathology, Diagnosis Computer-Assisted, methods, Human, Medical Illustration, Skull, anatomy & histology. Abstract:

We present a general scheme for automatically building a morphometric anatomical atlas. We detail each stage of the method, including the non-rigid registration algorithm, three-dimensional line averaging and statistical processes. We apply the method to obtain a quantitative atlas of skull crest lines. Finally, we use the resulting atlas to study a craniofacial disease; we show how we can obtain qualitative and quantitative results by contrasting a skull affected by a mandible deformation with the atlas.

[bibtex-key = Subsol98] [bibtex-entry]

J.-P. Thirion. Image matching as a diffusion process: an analogy with Maxwell's demons. Medical Image Analysis, 2(3):243-260, 1998.

Keyword(s): registration, matching, deformations, Algorithms, Animals, Brain, anatomy & histology, Computer Simulation, Diagnostic Imaging, methods, Dogs, Heart, anatomy & histology, Human, Image Processing Computer-Assisted, methods, Models Theoretical, Thermodynamics. Abstract:

In this paper, we present the concept of diffusing models to perform image-to-image matching. Having two images to match, the main idea is to consider the objects boundaries in one image as semi-permeable membranes and to let the other image, considered as a deformable grid model, diffuse through these interfaces, by the action of effectors situated within the membranes. We illustrate this concept by an analogy with Maxwell's demons. We show that this concept relates to more traditional ones, based on attraction, with an intermediate step being optical flow techniques. We use the concept of diffusing models to derive three different non-rigid matching algorithms, one using all the intensity levels in the static image, one using only contour points, and a last one operating on already segmented images. Finally, we present results with synthesized deformations and real medical images, with applications to heart motion tracking and three-dimensional inter-patients matching.

[bibtex-key = Thirion98] [bibtex-entry]

Nicholas Ayache, Stephane Cotin, and Hervé Delingette. Surgery Simulation with visual and haptic feedback. In Y. Shirai and S. Hirose, editors, Robotics Research, the Eigth International Symposium, pages 311-316. Springer, 1998. Keyword(s): workshop, simulation. [bibtex-key = ayache-isrr98] [bibtex-entry]

G. Subsol. Crest Lines for Curve Based Warping. In A. W. Toga, editor, Brain Warping, chapter 13, pages 225-246. Academic Press, 1998. [bibtex-key = Subsol98.2] [bibtex-entry]

J.-P. Thirion. Diffusing Models and Applications. In A. W. Toga, editor, Brain Warping, chapter 9, pages 143-155. Academic Press, 1998. Keyword(s): registration, matching. [bibtex-key = Thirion98b] [bibtex-entry]

P Chauvel, W Sauerwein, N Bornfeld, W Friedrichs, N Brassart, A Courdi, J Herault, J P Pignol, P Y Bondiau, and G Malandain. Clinical and technical requirements for proton treatment planning of ocular diseases. The SERAG (South Europe Radiotherapy Group). Front Radiat Ther Oncol, 30:133-42, 1997. Keyword(s): Comparative Study, Conjunctival Neoplasms, diagnosis, Dose-Response Relationship Radiation, Follow-Up Studies, Fundus Oculi, Human, Image Processing Computer-Assisted, Magnetic Resonance Imaging, Melanoma, diagnosis, Neoplasm Recurrence Local, diagnosis, Predictive Value of Tests, Protons, therapeutic use, Radiotherapy Planning Computer-Assisted, methods, Retrospective Studies, Tomography X-Ray Computed, Treatment Outcome, Uveal Neoplasms, diagnosis. [bibtex-key = chauvel:frto:1997] [bibtex-entry]

S. Cotin, H. Delingette, N. Ayache, J.M. Clement, J. Marescaux, and M. Nord. Simulation Active de Chirurgie Endoscopique. Revue Européenne de Technologie Biomédicale (RBM), 19(5):167-172, 1997. Keyword(s): journal, simulation. [bibtex-key = cotin_rbm] [bibtex-entry]

J. Declerck, J. Feldmar, M.L. Goris, and F. Betting. Automatic registration and alignment on a template of cardiac stress & rest SPECT reoriented images. IEEE Transactions on Medical Imaging, 16(6):727-737, 1997. Keyword(s): registration, matching, deformations. [bibtex-key = declerck:tmi:97] [bibtex-entry]

H. Delingette. Réalité virtuelle et médecine. Revue de la société des électriciens et des électroniciens (REE), 8:43-45, September 1997. Keyword(s): journal, simulation. [bibtex-key = ree97] [bibtex-entry]

J. Feldmar, N. Ayache, and F. Betting. 3D-2D projective registration of free-form curves and surfaces. Journal of Computer Vision and Image Understanding, 65(3):403-424, 1997. [bibtex-key = Feldmar4] [bibtex-entry]

J. Feldmar, J. Declerck, G. Malandain, and N. Ayache. Extension of the ICP Algorithm to Non-Rigid Intensity-Based Registration of 3D Volumes. Computer Vision and Image Understanding, 66(2):193-206, May 1997. Keyword(s): registration, matching, deformations. [bibtex-key = feldmar-al97] [bibtex-entry]

Alexandre Guimond, Gérard Subsol, and Jean-Philippe Thirion. Automatic MRI Database Exploration and Applications. International Journal of Pattern Recognition and Artificial Intelligence, 11(8):1345-1366, December 1997. [bibtex-key = guimond97.3] [bibtex-entry]

André Guéziec, Xavier Pennec, and Nicholas Ayache. Medical Image Registration using Geometric Hashing. IEEE Computational Science and Engineering, 4(4):29-41, Oct-Dec 1997. Note: Special issue on Geometric Hashing. Keyword(s): registration, matching. [bibtex-key = GueziecPennecAyache:CSE:97] [bibtex-entry]

J Marescaux, J M Clement, M Nord, Y Russier, V Tassetti, D Mutter, S Cotin, and N Ayache. [A new concept in digestive surgery: the computer assisted surgical procedure, from virtual reality to telemanipulation]. Bull Acad Natl Med, 181(8):1609-21, November 1997. Keyword(s): review, survey, review, survey, Computer Simulation, Digestive System Surgical Procedures, English Abstract, Human, Telemedicine, User-Computer Interface. Abstract:

Surgical simulation increasingly appears to be an essential aspect of tomorrow's surgery. The development of a hepatic surgery simulator is an advanced concept calling for a new writing system which will transform the medical world: virtual reality. Virtual reality extends the perception of our five senses by representing more than the real state of things by the means of computer sciences and robotics. It consists of three concepts: immersion, navigation and interaction. Three reasons have led us to develop this simulator: the first is to provide the surgeon with a comprehensive visualisation of the organ. The second reason is to allow for planning and surgical simulation that could be compared with the detailed flight-plan for a commercial jet pilot. The third lies in the fact that virtual reality is an integrated part of the concept of computer assisted surgical procedure. The project consists of a sophisticated simulator which has to include five requirements: visual fidelity, interactivity, physical properties, physiological properties, sensory input and output. In this report we will describe how to get a realistic 3D model of the liver from bi-dimensional 2D medical images for anatomical and surgical training. The introduction of a tumor and the consequent planning and virtual resection is also described, as are force feedback and real-time interaction.

[bibtex-key = marescaux:banm:1997] [bibtex-entry]

Xavier Pennec and Jean-Philippe Thirion. A Framework for Uncertainty and Validation of 3D Registration Methods based on Points and Frames. International Journal of Computer Vision, 25(3):203-229, December 1997. Keyword(s): registration, matching, uncertainty, statistics, validation. [bibtex-key = Pennec:IJCV:97] [bibtex-entry]

L Picard, E Maurincomme, M Soderman, J Feldmar, R Anxionnat, L Launay, K Ericson, G Malandain, S Bracard, E Kerrien, O Flodmark, and N Ayache. X-ray angiography in stereotactic conditions: techniques and interest for interventional neuroradiology. Stereotact Funct Neurosurg, 68(1-4 Pt 1):117-20, 1997. Keyword(s): Angiography Digital Subtraction, methods, Carotid Arteries, anatomy & histology, Cerebral Angiography, methods, Human, Image Enhancement, Magnetic Resonance Angiography, methods, Radiology Interventional, methods, Stereotaxic Techniques. Abstract:

This paper reports work in progress on X-ray angiography acquired under stereotactic conditions. The objective is to be able to match multimodality images (typically {MRI} and X-ray) without a stereotactic frame but with stereotactic precision. We have identified potential problems and have studied them in detail. We conclude that, although the overall application is feasible, much work remains to be done on the estimation of the X-ray system conic projection and on automatic matching based on vascular structures.

[bibtex-key = picard:sfn:1997] [bibtex-entry]

G. Quatrehomme, S. Cotin, G. Subsol, H. Delingette, Y. Garidel, G. Grévin, and M. Fidrich. A Fully Three-Dimensional Method for Facial Reconstruction Based on Deformable Models. Journal of Forensic Sciences, 42(4):649-652, July 1997. Keyword(s): journal, medical. [bibtex-key = Quatrehomme97b] [bibtex-entry]

G. Subsol, N. Roberts, M. Doran, and J.-Ph. Thirion. Automatic Analysis of Cerebral Atrophy. Magnetic Resonance Imaging, 15(8):917-927, 1997. [bibtex-key = Subsol97] [bibtex-entry]

J. West, J. M. Fitzpatrick, M. Y. Wang, B. M. Dawant, C. R. Maurer, Jr., R. M. Kessler, R. J. Maciunas, C. Barillot, D. Lemoine, A. Collignon, F. Maes, P. Suetens, D. Vandermeulen, P. A. van den Elsen, S. Napel, T. S. Sumanaweera, B. Harkness, P. F. Hemler, D. L. G. Hill, D. J. Hawkes, C. Studholme, J. B. A. Maintz, M. A. Viergever, G. Malandain, X. Pennec, M. E. Noz, G. Q. Maguire, Jr., M. Pollack, C. A. Pelizzari, R. A. Robb, D. Hanson, and R. P. Woods. Comparison and evaluation of retrospective intermodality brain image registration techniques. Journal of Computer Assisted Tomography, 21(4):554-566, 1997.

Keyword(s): registration, matching, multimodal, validation, uncertainty. Abstract:

PURPOSE: The primary objective of this study is to perform a blinded evaluation of a group of retrospective image registration techniques using as a gold standard a prospective, marker-based registration method. To ensure blindedness, all retrospective registrations were performed by participants who had no knowledge of the gold standard results until after their results had been submitted. A secondary goal of the project is to evaluate the importance of correcting geometrical distortion in MR images by comparing the retrospective registration error in the rectified images, i.e., those that have had the distortion correction applied, with that of the same images before rectification. METHOD: Image volumes of three modalities (CT, MR, and PET) were obtained from patients undergoing neurosurgery at Vanderbilt University Medical Center on whom bone-implanted fiducial markers were mounted. These volumes had all traces of the markers removed and were provided via the Internet to project collaborators outside Vanderbilt, who then performed retrospective registrations on the volumes, calculating transformations from CT to MR and/ or from PET to MR. These investigators communicated their transformations again via the Internet to Vanderbilt, where the accuracy of each registration was evaluated. In this evaluation, the accuracy is measured at multiple volumes of interest (VOIs), i.e., areas in the brain that would commonly be areas of neurological interest. A VOI is defined in the MR image and its centroid c is determined. Then, the prospective registration is used to obtain the corresponding point c' in CT or PET. To this point, the retrospective registration is then applied, producing c" in MR. Statistics are gathered on the target registration error (TRE), which is the distance between the original point c and its corresponding point c". RESULTS: This article presents statistics on the TRE calculated for each registration technique in this study and provides a brief description of each technique and an estimate of both preparation and execution time needed to perform the registration. CONCLUSION: Our results indicate that retrospective techniques have the potential to produce satisfactory results much of the time, but that visual inspection is necessary to guard against large errors.

[bibtex-key = West.etal:JCAT:97] [bibtex-entry]

N Ayache. Analyzing 3D images of the brain. NeuroImage, 4(3 Pt 2), December 1996. Keyword(s): Brain Mapping, Computer Graphics, Human, Image Processing Computer-Assisted, Robotics, Software, User-Computer Interface. [bibtex-key = ayache:neuroimage:1996] [bibtex-entry]

E. Bardinet, L.D. Cohen, and N. Ayache. Tracking and motion analysis of the left ventricle with deformable superquadrics. Medical Image Analysis, 1(2), 1996. Note: Also INRIA Research Report RR-2797, INRIA Sophia-Antipolis, February 1996. [bibtex-key = BCA96e] [bibtex-entry]

S Cotin, H Delingette, M Bro-Nielsen, N Ayache, J M Clement, V Tassetti, and J Marescaux. Geometric and physical representations for a simulator of hepatic surgery. Stud Health Technol Inform, 29:139-51, 1996. Keyword(s): Computer Simulation, Education Medical, Human, Image Processing Computer-Assisted, Liver, anatomy & histology, Support Non-U.S. Gov't, User-Computer Interface. Abstract:

Despite the large interest in simulators of minimally invasive surgery, it is still unclear to what extent simulators can achieve the task of training medical students in surgical procedures. The answer to that question is certainly linked to the realism of displays and force-feedback systems and to the level of interaction provided by the computer system. In this paper, we describe the virtual environment for anatomical and surgical training on the liver, currently under construction at INRIA. We specifically address the problems of geometric representation and physical modeling and their impact on the two aforementioned problems: realism and real-time interaction.

[bibtex-key = cotin:shti:1996] [bibtex-entry]

J. Feldmar and N. Ayache. Rigid, Affine and Locally Affine Registration of Free-Form Surfaces. International Journal of Computer Vision, 18(2):99-120, May 1996. Keyword(s): matching, registration, deformations. [bibtex-key = Feldmar-ayache-ijcv96] [bibtex-entry]

C. Nastar and N. Ayache. Frequency-based Non-rigid Motion Analysis: Application to Four Dimensional Medical Images. IEEE Transactions on Pattern Analysis and Machine Intelligence, 18(11):1067-1079, novembre 1996. [bibtex-key = Nastar-Ayache] [bibtex-entry]

N. Roberts, G. Subsol, J.-Ph. Thirion, M. Puddephat, and G. W. Whitehouse. Automatic Analysis of Deformation of the Cerebral Ventricles. Magnetic Resonance Materials in Physics, Biology and Medicine, 4(2):62-63, 1996. [bibtex-key = Roberts96] [bibtex-entry]

G. Subsol, J.-Ph. Thirion, and N. Ayache. Construction automatique d'atlas anatomiques morphométriques à partir d'images médicales tridimensionnelles : application à un atlas du crâne. Traitement du signal, 13(6):651-674, 1996. [bibtex-key = Subsol97.2] [bibtex-entry]

J.-P. Thirion. New Feature Points based on Geometric Invariants for 3D Image Registration. International Journal of Computer Vision, 18(2):121-137, May 1996. [bibtex-key = Thirion96d] [bibtex-entry]

J.-P. Thirion. The Extremal Mesh and the Understanding of 3D Surfaces. International Journal of Computer Vision, 19(2):115-128, August 1996. [bibtex-key = Thirion96e] [bibtex-entry]

H. Delingette and G. Subsol. L'Image dans la Réalité Virtuelle. In Nouvelles Interfaces Homme-Machine, number 18 of ARAGO. Observatoire Français des Techniques Avancées, 1996. Keyword(s): chapter-book, simulation. [bibtex-key = OFTA96] [bibtex-entry]

N. Ayache. Medical Computer Vision, Virtual Reality and Robotics. Image and Vision Computing, 13(4):295-313, May 1995. [bibtex-key = ayache-ivc] [bibtex-entry]

G. Bertrand and G. Malandain. A note on ``Building skeleton models via 3D medial surface-axis thinning algorithms''. Graphical Models and Image Processing, 57(6):537-538, November 1995. [bibtex-key = bertrand-al95] [bibtex-entry]

M. Hébert, H. Delingette, and K. Ikeuchi. Shape Representation and Image Segmentation Using Deformable Surfaces. IEEE Transactions on Pattern Analysis and Machine Intelligence, 17(7), June 1995. Keyword(s): journal, recognition. [bibtex-key = delingette_pami_95] [bibtex-entry]

O. Monga and S. Benayoun. Using partial derivatives of 3D images to extract typical surface features. Computer Vision and Image Understanding, 61(2):171-189, March 1995. Note: Aussi rapport de recherche INRIA numero 1599, Février 1992.

Abstract:

Three-dimensional edge detection in voxel images is used to locate points corresponding to surfaces of 3D structures. The next stage is to characterize the local geometry of these surfaces in order to extract points or lines which may be used by registration and tracking procedures. Typically one must calculate second-order differential characteristics of the surfaces such as the maximum, mean, and Gaussian curvature. The classical approach is to use local surface fitting, thereby confronting the problem of establishing links between 3D edge detection and local surface approximation. To avoid this problem, we propose to compute the curvatures at locations designated as edge points using directly the partial derivatives of the image. By assuming that the surface is defined locally by a isointensity contour (i.e., the 3D gradient at an edge point corresponds to the normal to the surface), one can calculate directly the curvatures and characterize the local curvature extrema (ridge points) from the first, second, and third derivatives of the gray level function. These partial derivatives can be computed using the operators of the edge detection. In the more general case where the contours are not isocontours (i.e., the gradient at an edge point only approximates the normal to the surface), the only differential invariants of the image are in R^4. This leads us to treat the 3D image as a hypersurface (a three-dimensional manifold) in R^4. We give the relationships between the curvatures of the hypersurface and the curvatures of the surface defined by edge points. The maximum curvature at a point on the hypersurface depends on the second partial derivatives of the 3D image. We note that it may be more efficient to smooth the data in R^4. Moreover, this approach could also be used to detect corners of vertices. We present experimental results obtained using real data (X ray scanner data) and applying these two methods. As an example of the stability, we extract ridge lines in two 3D X ray scanner data of a skull taken in different positions.

[bibtex-key = monga-benayoun95] [bibtex-entry]

J.-P. Thirion and A Gourdon. Computing the Differential Characteristics of Isointensity Surfaces. Journal of Computer Vision and Image Understanding, 61(2):190-202, March 1995. [bibtex-key = Thirion95c] [bibtex-entry]

N. Ayache, P. Cinquin, I. Cohen, L. D. Cohen, I. L. Herlin, F. Leitner, and O. Monga. Segmentation of Complex 3D medical Objects: a challenge and a requirement for computer assisted surgery planning and performing. In Computer Integrated Surgery. MIT-Press, 1995. [bibtex-key = ayache_inbook] [bibtex-entry]

G. Bertrand and G. Malandain. A new characterization of three-dimensional simple points. Pattern Recognition Letters, 15(2):169-175, February 1994. [bibtex-key = bertrand-al94] [bibtex-entry]

A. Guéziec and N. Ayache. Smoothing and Matching of 3-D Space Curves. International Journal of Computer Vision, 12(1):79-104, January 1994. [bibtex-key = Gueziec&Ayache:IJCV] [bibtex-entry]

G. Malandain, S. Fernández-Vidal, and J.-M. Rocchisani. Mise en correspondance d'objets 3D par une approche mécanique : application aux images médicales multimodales. Traitement du signal, 11(6):541-558, 1994. [bibtex-key = malandain-al95b] [bibtex-entry]

J.-P. Thirion. Direct Extraction of Boundaries from Computed Tomography Scans. IEEE Transactions on Medical Imaging, 13(2):322-328, June 1994. [bibtex-key = Thirion94d] [bibtex-entry]

Laurent D. Cohen and Isaac Cohen. Finite Element Methods for active contour models and balloons from 2-D to 3-D. IEEE Transactions on Pattern Analysis and Machine Intelligence, 15(11), November 1993. [bibtex-key = Cohen_CohenPAMI92] [bibtex-entry]

G. Malandain, G. Bertrand, and N. Ayache. Topological segmentation of discrete surfaces. International Journal of Computer Vision, 10(2):183-197, 1993. [bibtex-key = malandain-al93] [bibtex-entry]

N. Ayache. Computer Vision Applied to 3D Medical Images: Results, Trends and Future Challenges. In T. Kanade and R. Paul, editors, 6th Int. Symposium on Robotics Research. MIT-Press, 1993. Note: Available as INRIA Research Report 2050. [bibtex-key = ayache93a] [bibtex-entry]

Chahab Nastar and Nicholas Ayache. A New Physically Based Model for Efficient Tracking and Analysis of Deformations. In Geometric Reasoning - from Perception to Action, Lecture notes in computer science. Springer, 1993. [bibtex-key = NastarSPRINGER] [bibtex-entry]

I. Cohen, L.D. Cohen, and N. Ayache. Using deformable surfaces to segment 3-D images and infer differential structures. Computer Vision, Graphics, and Image Processing: Image Understanding, 56(2):242-263, 1992. [bibtex-key = Cohen_Cohen_Ayache:cvgip92] [bibtex-entry]

H. Delingette, M. Hébert, and K. Ikeuchi. Shape Representation and Image Segmentation using deformable surfaces. Image and Vision Computing, 10(3):132-144, April 1992. Keyword(s): journal, reconstruction. [bibtex-key = delingette_ivc_92] [bibtex-entry]

A. Guéziec and N. Ayache. Lissage et reconnaissance de courbes gauches bruitées. Traitement du signal, 9(6), 1992. [bibtex-key = Gueziec&Ayache:TS] [bibtex-entry]

I.L. Herlin and N. Ayache. Extraction de traits caractéristiques dans des séquences d'images échocardiographiques. Technique et Science Informatiques, 11(4), 1992. [bibtex-key = tsi-herlin-92] [bibtex-entry]

Isabelle L. Herlin and Nicholas Ayache. Feature Extraction and analysis methods for sequences of ultrasound images. Image and Vision Computing, 10(10):673-682, 1992. [bibtex-key = herlin-ayache-ivc92] [bibtex-entry]

O. Monga, N. Ayache, and P. Sander. Using uncertainty to link edge detection and local surface modelling. Image and Vision Computing, 10(6):673-682, Août 1992. [bibtex-key = monga-ayache-sander91] [bibtex-entry]

Olivier Monga, Peter Sander, and Nicholas Ayache. From Voxel to Intrinsic Surface Features. Image and Vision Computing, 10(6):403-417, 1992. [bibtex-key = monga-sander-ayache-ivc92] [bibtex-entry]

J.-Ph. Thirion. Realistic 3D Simulation of Shapes and Shadows for Image Processing. Computer Vision, Graphics and Image Processing, pp 82-90, January 1992. [bibtex-key = Thirion91a] [bibtex-entry]

J.-Ph. Thirion. Segmentation of Tomographic Data without Image Reconstruction. IEEE Transactions on Medical Imaging, pp 102-110, March 1992. [bibtex-key = Thirion91b] [bibtex-entry]

N. Ayache, I. Cohen, and I.L. Herlin. Medical Image Tracking. In Active Vision, Andrew Blake and Alan Yuille, chapter 17. MIT Press, 1992. Note: In press. [bibtex-key = na-isaac-isa] [bibtex-entry]

Nicholas Ayache and Francis Lustman. Trinocular Stereovision for Robotics. IEEE Transactions on Pattern Analysis and Machine Intelligence, 13(1), 1991. [bibtex-key = ayache-lustman-pami91] [bibtex-entry]

O. Monga, R. Deriche, G. Malandain, and J.-P. Cocquerez. Recursive filtering and edge tracking: two primary tools for 3-D edge detection. Image and Vision Computing, 9(4):203-214, August 1991. [bibtex-key = monga-al91b] [bibtex-entry]

J.-M Rocchisani, O. Monga, R. Deriche, and G. Malandain. Automatic multidimensional segmentation of nuclear medicine images using fast recursive filters. European Journal of Nuclear Medicine, 16:419, 1990. [bibtex-key = rocchisani90] [bibtex-entry]

Nicholas Ayache and Olivier Faugeras. Maintaining Representations of the Environment of a Mobile Robot. International Journal of Robotics and Automation, 5(6):804-819, 1989. [bibtex-key = ayache-faugeras-ijra89] [bibtex-entry]

Nicholas Ayache and Olivier Faugeras. Building, registrating and fusing noisy visual maps. International Journal of Robotics Research, 7(6):45-65, 1988. [bibtex-key = ayache-faugeras-ijrr88] [bibtex-entry]

Nicholas Ayache and Bernard Faverjon. Efficient Registration of stereo images by matching graph descriptions of edge segments. International Journal of Computer Vision, pp 107-131, 1987. [bibtex-key = ayache-faverjon-IJCV87] [bibtex-entry]

Nicholas Ayache and Olivier Faugeras. HYPER: a new approach for the recognition and positioning of 2D objects. IEEE Transactions on Pattern Analysis and Machine Intelligence, 8(1):44-54, 1986. [bibtex-key = ayache-pami86] [bibtex-entry]

Lisa Guzzi, Maria A. Zuluaga, Fabien Lareyre, Gilles Di Lorenzo, Sébastien Goffart, Andrea Chierici, Juliette Raffort, and Hervé Delingette. Differentiable Soft Morphological Filters for Medical Image Segmentation. In MICCAI 2024 - Medical Image Computing and Computer Assisted Intervention, Marrakesh, Morocco, October 2024. Keyword(s): Image Segmentation, Morphological Operations, Deep Learning. [bibtex-key = guzzi:hal-04592007] [bibtex-entry]

Guillaume Olikier. Retractions on closed sets. In MTNS 2024 - 26th International Symposium on Mathematical Theory of Networks and Systems, Cambridge (GB), United Kingdom, August 2024. Keyword(s): retraction, tangent cones, stationarity, line-search methods, low-rank optimization. [bibtex-key = olikier:hal-04581498] [bibtex-entry]

Théodore Soulier, Mariem Hamzaoui, Milena Sales Pitombeira, Daniele De Paula Faria, Arya Yazdan-Panah, Matteo Tonietto, Claire Leroy, Michel Bottlaender, Benedetta Bodini, Ninon Burgos, Nicholas Ayache, Olivier Colliot, and Bruno Stankoff. Generating PET-derived maps of myelin content from clinical MRI using curricular discriminator training in generative adversarial networks. In SPIE Medical Imaging, San Diego, United States, February 2024. Keyword(s): Multiple Sclerosis, Magnetic Resonance Imaging, Positron Emission Tomography, Myelin, Generative Adversarial Network, Curriculum Learning, Image synthesis. [bibtex-key = soulier:hal-04362506] [bibtex-entry]

Riccardo Taiello, Melek Önen, Clémentine Gritti, and Marco Lorenzi. Let Them Drop: Scalable and Efficient Federated Learning Solutions Agnostic to Stragglers. In ARES 2024 - International Conference on Availability, Reliability and Security, Vienna, Austria, July 2024. ACM. [bibtex-key = taiello:hal-04659083] [bibtex-entry]

Morten Akhoj, Xavier Pennec, and Stefan Sommer. Tangent phylogenetic PCA. In Scandinavian Conference on Image Analysis 2023, volume 13886 of Lecture Notes in Computer Science, Levi Ski Resort (Lapland), Finland, pages 77-90, April 2023. Springer Nature Switzerland. [bibtex-key = akhoj:hal-03842847] [bibtex-entry]

Safaa Al-Ali, Jordi Llopis-Lorente, Maria Teresa Mora, Maxime Sermesant, Beatriz Trénor, and Irene Balelli. A causal discovery approach for streamline ion channels selection to improve drug-induced TdP risk assessment. In 2023 Computing in Cardiology (CinC), 2023 Computing in Cardiology (CinC), Atlanta (GA), United States, October 2023. Keyword(s): Causal discovery, Drug safety, Ions channel, TdP risk. [bibtex-key = alali:hal-04105144] [bibtex-entry]

Anna Calissano, Elodie Maignant, and Xavier Pennec. Towards Quotient Barycentric Subspaces. In GSI 2023: Geometric Science of Information, volume 14071 of Lecture Notes in Computer Science, Saint-Malo (France), France, pages 366-374, August 2023. Springer Nature Switzerland. Keyword(s): Discrete Group, Quotient Space, Barycentric Subspace Analysis, Graph Space, Object Oriented Data Analysis. [bibtex-key = calissano:hal-04162647] [bibtex-entry]

Nicolas Cedilnik and Jean-Marc Peyrat. Weighted tissue thickness. In FIMH 2023 - 12th International Conference On Functional Imaging And Modeling Of The Heart, Lecture Notes in Computer Science, Lyon, France, June 2023. Springer. Keyword(s): Thickness, Thickness measurements, Medical image analysis. [bibtex-key = cedilnik:hal-04111276] [bibtex-entry]

Hind Dadoun, Hervé Delingette, Anne-Laure Rousseau, Eric de Kerviler, and Nicholas Ayache. Joint representation learning from french radiological reports and ultrasound images. In IEEE ISBI 2023 - International Symposium on Biomedical Imaging, Cartagena de Indias, Colombia, April 2023. IEEE. Keyword(s): multimodal learning deep clustering natural language processing ultrasound examinations kidneys, multimodal learning, deep clustering, natural language processing, ultrasound examinations, kidneys. [bibtex-key = dadoun:hal-03984528] [bibtex-entry]

Zhijie Fang, Hervé Delingette, and Nicholas Ayache. Anatomical Landmark Detection for Initializing US and MR Image Registration. In MICCAI ASMUS 2023 - 4th International Workshop of Advances in Simplifying Medical UltraSound - a workshop held in conjunction with MICCAI 2023, the 26th International Conference on Medical Image Computing and Computer Assisted Intervention, Vancouver, Canada, October 2023. Keyword(s): Landmark detection, Image-guided intervention, Convolutional neural network and Prostate cancer. [bibtex-key = fang:hal-04189905] [bibtex-entry]

Yann Fraboni, Lucia Innocenti, Michela Antonelli, Richard Vidal, Laetitia Kameni, Sebastien Ourselin, and Marco Lorenzi. Validation of Federated Unlearning on Collaborative Prostate Segmentation. In DECAF MICCAI 2023 Workshops, volume 14393 of Lecture Notes in Computer Science, Toronto, Canada, pages 322-333, October 2023. Medical Image Computing and Computer Assisted Intervention, Springer Nature Switzerland. Keyword(s): federated unlearning, prostate cancer, segmentation, Medical imaging. [bibtex-key = fraboni:hal-04417106] [bibtex-entry]

Etrit Haxholli and Marco Lorenzi. Enhanced Distribution Modelling via Augmented Architectures For Neural ODE Flows. In DLDE-III Workshop in the 37th Conference on Neural Information Processing Systems (NeurIPS 2023), New Orleans, Louisiana, United States, December 2023. [bibtex-key = haxholli:hal-03911870] [bibtex-entry]

Etrit Haxholli and Marco Lorenzi. Faster Training of Diffusion Models and Improved Density Estimation via Parallel Score Matching. In NeurIPS 2023 Workshop on Diffusion Models, New Orleans, Louisiana, United States, December 2023. [bibtex-key = haxholli:hal-04032669] [bibtex-entry]

Lucia Innocenti, Michela Antonelli, Francesco Cremonesi, Kenaan Sarhan, Alejandro Granados, Vicky Goh, Sebastien Ourselin, and Marco Lorenzi. Benchmarking Collaborative Learning Methods Cost-Effectiveness for Prostate Segmentation. In ECML - PharML - Applications of Machine Learning in Pharma and Healthcare (Workshop at ECML PKDD 2023), Turin (IT), Italy, September 2023. arXiv. Note: Workshop at ECML PKDD 2023. Keyword(s): Collaborative Learning, Cost-Effectiveness, Prostate Segmentation. [bibtex-key = innocenti:hal-04357349] [bibtex-entry]

Elodie Maignant, Alain Trouvé, and Xavier Pennec. Riemannian Locally Linear Embedding with Application to Kendall Shape Spaces. In GSI 2023: Geometric Science of Information, volume 14071 of Lecture Notes in Computer Science, Saint-Malo, (France), France, pages 12-20, August 2023. Springer Nature Switzerland. Keyword(s): Locally Linear Embedding, Optimisation on Quotient Manifolds, Shape Spaces. [bibtex-key = maignant:hal-04122754] [bibtex-entry]

Hari Sreedhar, Guillaume P R Lajoinie, Charles Raffaelli, and Hervé Delingette. Active Learning Strategies on a Real-World Thyroid Ultrasound Dataset. In DALI 2023 - Data Augmentation, Labelling, and Imperfections / MICCAI Workshop 2023, MICCAI Workshop on Data Augmentation, Labelling, and Imperfections, DALI 2023, held in conjunction with MICCAI 2023 Proceedings, Vancouver, Canada, October 2023. Keyword(s): Thyroid cancer, Active learning, Ultrasound imaging. [bibtex-key = sreedhar:hal-04209622] [bibtex-entry]

Tom Szwagier and Xavier Pennec. Rethinking the Riemannian Logarithm on Flag Manifolds as an Orthogonal Alignment Problem. In GSI 2023: Geometric Science of Information, volume 14071 of Lecture Notes in Computer Science, Saint-Malo, (France), France, pages 375-383, August 2023. Springer Nature Switzerland. Keyword(s): Flag manifolds, Riemannian logarithm, Orthogonal alignment, Procrustes analysis, Flag manifolds Riemannian logarithm Orthogonal alignment Procrustes analysis. [bibtex-key = szwagier:hal-04100534] [bibtex-entry]

Yann Thanwerdas and Xavier Pennec. Characterization of Invariant Inner Products. In GSI 2023 - International Conference on Geometric Science of Information, volume LNCS-14071 of Geometric Science of Information: 6th International Conference, GSI 2023, St. Malo, France, August 30 -- September 1, 2023, Proceedings, Part I, Saint Malo, France, France, pages 384-391, August 2023. Springer Nature Switzerland. Keyword(s): Invariant inner product Invariant Riemannian metric Group action Representation theory, Invariant inner product, Invariant Riemannian metric, Group action, Representation theory. [bibtex-key = thanwerdas:hal-04229093] [bibtex-entry]

Yingyu Yang and Maxime Sermesant. Unsupervised Polyaffine Transformation Learning for Echocardiography Motion Estimation. In FIMH 2023 - The 12th International Conference on Functional Imaging and Modeling of The Heart, Lyon, France, June 2023. Keyword(s): Motion Estimation Echocardiography Polyaffine Transformation, Motion Estimation, Echocardiography, Polyaffine Transformation. [bibtex-key = yang:hal-04109721] [bibtex-entry]

Yann Fraboni, Richard Vidal, Laetitia Kameni, and Marco Lorenzi. A General Theory for Client Sampling in Federated Learning. In International Workshop on Trustworthy Federated Learning in Conjunction with IJCAI 2022 (FL-IJCAI'22), Vienna, Austria, July 2022. [bibtex-key = fraboni:hal-03500307] [bibtex-entry]

Dimitri Hamzaoui, Sarah Montagne, Raphaele Renard-Penna, Nicholas Ayache, and Hervé Delingette. MOrphologically-aware Jaccard-based ITerative Optimization (MOJITO) for Consensus Segmentation. In MICCAI Workshop UNSURE 2022: Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, Singapore, Singapore, September 2022. Keyword(s): Consensus Algorithm, Segmentation 2D et 3D, Jaccard distance, STAPLE. [bibtex-key = hamzaoui:hal-03775967] [bibtex-entry]

Victoriya Kashtanova, Ibrahim Ayed, Andony Arrieula, Mark Potse, Patrick Gallinari, and Maxime Sermesant. Deep Learning for Model Correction in Cardiac Electrophysiological Imaging. In MIDL 2022 - Medical Imaging with Deep Learning, Zurich, Switzerland, July 2022. Keyword(s): Electrophysiology, Deep learning, Simulations, Physics-based learning. [bibtex-key = kashtanova:hal-03687596] [bibtex-entry]

Victoriya Kashtanova, Mihaela Pop, Ibrahim Ayed, Patrick Gallinari, and Maxime Sermesant. APHYN-EP: Physics-based deep learning framework to learn and forecast cardiac electrophysiology dynamics. In STACOM 2022 - 13th Workhop on Statistical Atlases and Computational Modelling of the Heart, Singapore, Singapore, September 2022. Keyword(s): Physics-based learning Deep Learning Electrophysiology Simulations, Physics-based learning, Deep Learning, Electrophysiology, Simulations. [bibtex-key = kashtanova:hal-03894974] [bibtex-entry]

Huiyu Li, Nicholas Ayache, and Hervé Delingette. Data Stealing Attack on Medical Images: Is it Safe to Export Networks from Data Lakes?. In Springer Nature, editor, DeCaF 2022 - International Workshop on Distributed, Collaborative, and Federated Learning, volume LNCS - 13573 of Distributed, Collaborative, and Federated Learning, and Affordable AI and Healthcare for Resource Diverse Global Health Third MICCAI Workshop, DeCaF 2022, and Second MICCAI Workshop, FAIR 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18 and 22, 2022, Proceedings, Singapore, Singapore, September 2022. Note: Best Paper Award. Keyword(s): Data Stealing Attack, Privacy, Medical Images. [bibtex-key = li:hal-03775940] [bibtex-entry]

Buntheng Ly, Sonny Finsterbach, Marta Nuñez-Garcia, Pierre Jaïs, Damien Garreau, Hubert Cochet, and Maxime Sermesant. Interpretable Prediction of Post-Infarct Ventricular Arrhythmia using Graph Convolutional Network. In STACOM 2022 - 13th Workhop on Statistical Atlases and Computational Modelling of the Heart, Singapore, Singapore, September 2022. Keyword(s): Graph Neural Network, Ventricular Arrhythmia, Interpretable AI, Cardiac CT. [bibtex-key = ly:hal-03829609] [bibtex-entry]

Riccardo Taiello, Melek Önen, Olivier Humbert, and Marco Lorenzi. Privacy Preserving Image Registration. In MICCAI 2022 - Medical Image Computing and Computer Assisted Intervention, Singapore, Singapore, September 2022. Keyword(s): Image Registration, Privacy enhancing technologies, Trustworthiness. [bibtex-key = taiello:hal-03697446] [bibtex-entry]

Jean Ogier Du Terrail, Samy-Safwan Ayed, Edwige Cyffers, Felix Grimberg, Chaoyang He, Regis Loeb, Paul Mangold, Tanguy Marchand, Othmane Marfoq, Erum Mushtaq, Boris Muzellec, Constantin Philippenko, Santiago Silva, Maria Telenczuk, Shadi Albarqouni, Salman Avestimehr, Aurélien Bellet, Aymeric Dieuleveut, Martin Jaggi, Sai Praneeth Karimireddy, Marco Lorenzi, Giovanni Neglia, Marc Tommasi, and Mathieu Andreux. FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings. In NeurIPS 2022 - Thirty-sixth Conference on Neural Information Processing Systems, Proceedings of NeurIPS, New Orleans, United States, November 2022. [bibtex-key = terrail:hal-03900026] [bibtex-entry]

Zihao Wang, Yingyu Yang, Maxime Sermesant, and Hervé Delingette. Unsupervised Echocardiography Registration through Patch-based MLPs and Transformers. In STACOM 2022 - 13th workshop on Statistical Atlases and Computational Models of the Heart, Singapore, Singapore, September 2022. Keyword(s): Unsupervised Registration, MLP, Transformer, Echocardiography. [bibtex-key = wang:hal-03792276] [bibtex-entry]

Yingyu Yang, Marie Rocher, Pamela Moceri, and Maxime Sermesant. Explainable Electrocardiogram Analysis with Wave Decomposition: Application to Myocardial Infarction Detection. In STACOM 2022 - 13th workshop on Statistical Atlases and Computational Models of the Heart, Singapore, Singapore, September 2022. Keyword(s): ECG analysis, Reconstruction, Explainable ML, Myocardial infarction classification. [bibtex-key = yang:hal-03888791] [bibtex-entry]

Benoît Audelan, Lopez Stéphanie, Pierre Fillard, Yann Diascorn, Bernard Padovani, and Hervé Delingette. Validation of lung nodule detection a year before diagnosis in NLST dataset based on a deep learning system. In ERS 2021 - European Respiratory Society International Congress, Virtual, United Kingdom, September 2021. [bibtex-key = audelan:hal-03538729] [bibtex-entry]

Irene Balelli, Santiago Silva, and Marco Lorenzi. A Probabilistic Framework for Modeling the Variability Across Federated Datasets of Heterogeneous Multi-View Observations. In International Conference on Information Processing in Medical Imaging, Information processing in medical imaging: proceedings of the 27th International Conference, IPMI 2021, Bornholm, Denmark, June 2021. Keyword(s): Federated Learning, Hierarchical Generative Model, Heterogeneity. [bibtex-key = balelli:hal-03152886] [bibtex-entry]

Francisco J Burgos-Fernández, Buntheng Ly, Fernando Dìaz-Doutón, Meritxell Vilaseca, Jaume Pujol, and Maxime Sermesant. Automatic classification of multispectral eye fundus images using deep learning. In Libro de Resúmenes RNO2021, Online, Spain, November 2021. [bibtex-key = burgosfernandez:hal-03513023] [bibtex-entry]

Hind Dadoun, Hervé Delingette, Anne-Laure Rousseau, Eric de Kerviler, and Nicholas Ayache. Combining Bayesian and Deep Learning Methods for the Delineation of the Fan in Ultrasound Images. In ISBI 2021 - 18th IEEE International Symposium on Biomedical Imaging, Nice, France, April 2021. Keyword(s): Ultrasound imaging, Deep Learning, Ultrasound fan area detection, pre-processing. [bibtex-key = dadoun:hal-03127809] [bibtex-entry]

Gaëtan Desrues, Delphine Feuerstein, Thierry Legay, Serge Cazeau, and Maxime Sermesant. Personal-by-design: a 3D Electromechanical Model of the Heart Tailored for Personalisation. In FIMH 2021 - 11th International Conference on Functional Imaging and Modeling of the Heart, Stanford, CA, United States, June 2021. Keyword(s): Personalisation, Digital twin, Cardiac electromechanical model, Electrophysiology, Electrocardiogram. [bibtex-key = desrues:hal-03369345] [bibtex-entry]

Maxime Di Folco, Nicolas Guigui, Patrick Clarysse, Pamela Moceri, and Nicolas Duchateau. Investigation of the impact of normalization on the study of interactions between myocardial shape and deformation. In FIMH 2021 - 11th International Conference on Functional Imaging and Modeling of the Heart, volume 12738 of Lectune notes in computer science (LNCS), Stanford, United States, pages 223-231, June 2021. Springer. Keyword(s): Cardiac imaging, manifold learning, myocardial strain, heart shape. [bibtex-key = difolco:hal-03203378] [bibtex-entry]

Yann Fraboni, Richard Vidal, Laetitia Kameni, and Marco Lorenzi. Clustered Sampling: Low-Variance and Improved Representativity for Clients Selection in Federated Learning. In ICML 2021 - 38th International Conference on Machine Learning, online, United States, July 2021. Keyword(s): Client sampling, federated learning, sampling variance, data representativity. [bibtex-key = fraboni:hal-03232421] [bibtex-entry]

Yann Fraboni, Richard Vidal, and Marco Lorenzi. Free-rider Attacks on Model Aggregation in Federated Learning. In AISTATS 2021 - 24th International Conference on Artificial Intelligence and Statistics, San Diego, United States, April 2021. [bibtex-key = fraboni:hal-03123638] [bibtex-entry]

Nicolas Guigui, Elodie Maignant, Alain Trouvé, and Xavier Pennec. Parallel Transport on Kendall Shape Spaces. In GSI 2021 - 5th conference on Geometric Science of Information, volume 12829 of Lecture Notes in Computer Science, Paris, France, pages 103-110, July 2021. Springer. [bibtex-key = guigui:hal-03160677] [bibtex-entry]

Nicolas Guigui, Pamela Moceri, Maxime Sermesant, and Xavier Pennec. Cardiac Motion Modeling with Parallel Transport and Shape Splines. In ISBI 2021 - 18th IEEE International Symposium on Biomedical Imaging, IEEE 18th International Symposium on Biomedical Imaging (ISBI), 2021, Nice, France, pages pp. 1394-1397, April 2021. IEEE. Keyword(s): LDDMM, Cardiac Modelling, Shape Analysis. [bibtex-key = guigui:hal-03142196] [bibtex-entry]

Nicolas Guigui and Xavier Pennec. A reduced parallel transport equation on Lie Groups with a left-invariant metric. In GSI 2021 - 5th conference on Geometric Science of Information, volume 12829 of Lecture Notes in Computer Science, Paris, France, pages 119-126, July 2021. Springer, Cham. [bibtex-key = guigui:hal-03154318] [bibtex-entry]

Mariem Hamzaoui, Théodore Soulier, Arya Yazdan-Panah, Marius Schmidt- Mengin, Olivier Colliot, Nicholas Ayache, and Bruno Stankoff. Intensity based Regions Of Interest (ROIs) preselection followed by Convolutional Neuronal Network (CNN) based segmentation for new lesions detection in Multiple Sclerosis. In MICCAI 2021 MSSEG2 - 24th International Conference on Medical Image Computing and Computer Assisted Intervention - Challenge on multiple sclerosis new lesions segmentation challenge using a data management and processing infrastructure - MICCAI-MSSEG-2, Strasbourg, France, September 2021. Keyword(s): Classical image processing, CNNs, Hybrid approach. [bibtex-key = hamzaoui:hal-03826791] [bibtex-entry]

Josquin Harrison, Marco Lorenzi, Benoit Legghe, Xavier Iriart, Hubert Cochet, and Maxime Sermesant. Phase-independent Latent Representation for Cardiac Shape Analysis. In MICCAI 2021 - 24th International Conference on Medical Image Computing and Computer Assisted Intervention, volume 12906 of LNCS - Lecture Notes in Computer Science, Strasbourg, France, September 2021. Keyword(s): Shape Analysis, Atrial Fibrillation, Thrombosis, Graph Representation, Latent Space Model, Multi-Task Learning, Meta-Learning. [bibtex-key = harrison:hal-03375871] [bibtex-entry]

Florent Jousse, Xavier Pennec, Hervé Delingette, and Matilde Gonzalez. Geodesic squared exponential kernel for non-rigid shape registration. In FG 2021 - IEEE International Conference on Automatic Face and Gesture Recognition, JODHPUR, India, December 2021. [bibtex-key = jousse:hal-03500440] [bibtex-entry]

Victoriya Kashtanova, Ibrahim Ayed, Nicolas Cedilnik, Patrick Gallinari, and Maxime Sermesant. EP-Net 2.0: Out-of-Domain Generalisation for Deep Learning Models of Cardiac Electrophysiology. In FIMH 2021 - 11th International Conference on Functional Imaging and Modeling of the Heart, volume 12738 of Lecture Notes in Computer Science, Stanford, CA (virtual), United States, pages 482-492, June 2021. Springer International Publishing. Keyword(s): Electrophysiology, Deep learning, Simulation. [bibtex-key = kashtanova:hal-03369201] [bibtex-entry]

Buntheng Ly, Sonny Finsterbach, Marta Nuñez-Garcia, Hubert Cochet, and Maxime Sermesant. Scar-Related Ventricular Arrhythmia Prediction from Imaging Using Explainable Deep Learning. In FIMH 2021 - 11th International Conference on Functional Imaging and Modeling of the Heart, volume 12738 of Lecture Notes in Computer Science, Stanford, United States, pages 461-470, June 2021. Springer International Publishing. Keyword(s): Conditional-VAE, Sustained Ventricular Arrhythmia, CTcardiac imaging, Myocardium thickness, Image Classification. [bibtex-key = ly:hal-03378951] [bibtex-entry]

Marius Schmidt-Mengin, Arya Yazdan-Panah, Théodore Soulier, Mariem Hamzaoui, Nicholas Ayache, and Olivier Colliot. Segmentation of new multiple sclerosis lesions on FLAIR MRI using online hard example mining. In MICCAI-MSSEG-2 - 25th International Conference on Medical Image Computing and Computer Assisted Intervention - challenge on multiple sclerosis new lesions segmentation challenge using a data management and processing infrastructure, Strasbourg, France, September 2021. Keyword(s): Segmentation, Deep learning, Hard example mining, Multiple Sclerosis, MRI. [bibtex-key = schmidtmengin:hal-03826787] [bibtex-entry]

Yann Thanwerdas and Xavier Pennec. Geodesics and Curvature of the Quotient-Affine Metrics on Full-Rank Correlation Matrices. In GSI 2021 - 5th conference on Geometric Science of Information, volume 12829 of Proceedings of Geometric Science of Information, Paris, France, pages 93-102, July 2021. Springer, Cham. Keyword(s): Correlation matrices, SPD matrices, Quotient manifold, Quotient-affine metric, Riemannian geometry. [bibtex-key = thanwerdas:hal-03157992] [bibtex-entry]

Paul Tourniaire, Marius Ilie, Paul Hofman, Nicholas Ayache, and Hervé Delingette. Attention-based Multiple Instance Learning with Mixed Supervision on the Camelyon16 Dataset. In MICCAI 2021 - Workshop on Computational Pathology, volume 156 of Proceedings of Machine Learning Research, Strasbourg, France, pages 216-226, September 2021. PMLR. Keyword(s): Attention Mechanism, Mixed Supervision, Histopathology. [bibtex-key = tourniaire:hal-03342963] [bibtex-entry]

Zihao Wang, Clair Vandersteen, Charles Raffaelli, Nicolas Guevara, François Patou, and Hervé Delingette. One-shot Learning Landmarks Detection. In MICCAI 2021 - Workshop on Data Augmentation, Labeling, and Imperfections, volume 13003 of Lecture Notes in Computer Science (LNCS), strasbourg, France, pages 163-172, October 2021. Springer. [bibtex-key = wang:hal-03024759] [bibtex-entry]

Yingyu Yang and Maxime Sermesant. Shape Constraints in Deep Learning for Robust 2D Echocardiography Analysis. In FIMH 2021 - 11th International Conference on Functional Imaging and Modeling of the Heart, Stanford, United States, June 2021. Keyword(s): Segmentation, Deep Learning, Deformation, Echocardiography. [bibtex-key = yang:hal-03371358] [bibtex-entry]

Benoît Audelan, Dimitri Hamzaoui, Sarah Montagne, Raphaële Renard-Penna, and Hervé Delingette. Robust Fusion of Probability Maps. In MICCAI 2020 - 23rd International Conference on Medical Image Computing and Computer Assisted Intervention, Lima/ Virtuel, Peru, October 2020. [bibtex-key = audelan:hal-02934590] [bibtex-entry]

Jaume Banus, Maxime Sermesant, Oscar Camara, and Marco Lorenzi. Joint data imputation and mechanistic modelling for simulating heart-brain interactions in incomplete datasets. In MICCAI 2020 - 23th International Conference on Medical Image Computing and Computer Assisted Intervention, Lima / Virtual, Peru, pages 478-486, October 2020. Keyword(s): Gaussian Process, Variational Inference, Lumped model, Missing features, Biomechanical simulation. [bibtex-key = banus:hal-02952576] [bibtex-entry]

Emmanuel Chevallier and Nicolas Guigui. Wrapped statistical models on manifolds: motivations, the case SE(n), and generalization to symmetric spaces. In Joint Structures and Common Foundations of Statistical Physics, Information Geometry and Inference for Learning, Les Houches, France, July 2020. Keyword(s): Non-Euclidean statistics, wrapped distributions, exponential map, moment matching estimator. [bibtex-key = chevallier:hal-03154401] [bibtex-entry]

Dimitri Hamzaoui, Sarah Montagne, Pierre Mozer, Raphaële Renard-Penna, and Hervé Delingette. Segmentation automatique de la prostate à l'aide d'un réseau de neurones profond. In Congrès Francais d'Urologie, Paris, France, pages 696-697, November 2020. [bibtex-key = hamzaoui:hal-03126932] [bibtex-entry]

Nina Miolane, Nicolas Guigui, Hadi Zaatiti, Christian Shewmake, Hatem Hajri, Daniel Brooks, Alice Le Brigant, Johan Mathe, Benjamin Hou, Yann Thanwerdas, Stefan Heyder, Olivier Peltre, Niklas Koep, Yann Cabanes, Thomas Gerald, Paul Chauchat, Bernhard Kainz, Claire Donnat, Susan Holmes, and Xavier Pennec. Introduction to Geometric Learning in Python with Geomstats. In Meghann Agarwal, Chris Calloway, Dillon Niederhut, and David Shupe, editors, SciPy 2020 - 19th Python in Science Conference, Austin, Texas, United States, pages 48-57, July 2020. Keyword(s): Index Terms-differential geometry, statistics, manifold, machine learning. [bibtex-key = miolane:hal-02908006] [bibtex-entry]

Pamela Moceri, Nicolas Duchateau, N Dursent, Xavier Iriart, Sébastien Hascoet, D Baudouy, Emile Ferrari, and Maxime Sermesant. Right ventricular remodelling in CHD-PAH patients using 3D speckle tracking. In JESFC 2020 - 30es Journées Européennes de la Société Française de Cardiologie, volume 12 of Archives of Cardiovascular Diseases Supplements, Paris, France, pages 163-4, January 2020. [bibtex-key = moceri:hal-02445303] [bibtex-entry]

Marta Nuñez-Garcia, Nicolas Cedilnik, Shuman Jia, Hubert Cochet, Marco Lorenzi, and Maxime Sermesant. Estimation of imaging biomarker's progression in post-infarct patients using cross-sectional data. In STACOM 2020 - 11th International Workshop on Statistical Atlases and Computational Models of the Heart, Lima, Peru, pages p.108-116, October 2020. Keyword(s): Post-infarct cardiac remodeling, Ventricular arrhythmia, Cross-sectional data, Disease progression modeling. [bibtex-key = nunezgarcia:hal-02961506] [bibtex-entry]

Marta Nuñez-Garcia, Nicolas Cedilnik, Shuman Jia, Maxime Sermesant, and Hubert Cochet. Automatic multiplanar CT reformatting from trans-axial into left ventricle short-axis view. In STACOM 2020 - 11th International Workshop on Statistical Atlases and Computational Models of the Heart, Lima, Peru, pages p.108-116, October 2020. Keyword(s): Automatic image reformatting, Short-axis view, Deep learning segmentation, Cardiac imaging. [bibtex-key = nunezgarcia:hal-02961500] [bibtex-entry]

Fanny Orlhac, Thibaut Cassou-Mounat, Jean-Yves Pierga, Marie Luporsi, Christophe Nioche, Charles Bouveyron, Nicholas Ayache, Nina Jehanno, Alain Livartowski, and Irene Buvat. Can we identify ''twin patients'' to predict response to neoadjuvant chemotherapy in breast cancer?. In SNMMI Annual Meeting, Virtual Meeting, United States, July 2020. [bibtex-key = orlhac:inserm-02952453] [bibtex-entry]

Fanny Orlhac, Anne-Capucine Rollet, Irène Buvat, Jacques Darcourt, Véronique Bourg, Christophe Nioche, Charles Bouveyron, Nicholas Ayache, and Olivier Humbert. Identifying a reliable radiomic signature from scarce data: illustration for 18F-FDOPA PET images in glioblastoma patients. In EANM Annual Meeting - Annual Meeting of the European Association of Nuclear Medicine, Virtual Meeting, Austria, October 2020. [bibtex-key = orlhac:inserm-02952445] [bibtex-entry]

Santiago Silva, Andre Altmann, Boris Gutman, and Marco Lorenzi. Fed-BioMed: A general open-source frontendframework for federated learning in healthcare. In MICCAI 2020 - 23rd International Conference on Medical Image Computing and Computer Assisted Intervention - 1st Workshop on Distributed and Collaborative Learning, DCL: MICCAI Workshop on Distributed and Collaborative Learning, Lima/ Virtuel, Peru, pages 201-210, October 2020. Springer. Keyword(s): federated learning, healthcare, medical imaging. [bibtex-key = silva:hal-02966789] [bibtex-entry]

Zihao Wang, Clair Vandersteen, Thomas Demarcy, Dan Gnansia, Charles Raffaelli, Nicolas Guevara, and Hervé Delingette. A Deep Learning based Fast Signed Distance Map Generation. In MIDL 2020 - Medical Imaging with Deep Learning, Montréal, Canada, July 2020. [bibtex-key = wang:hal-02570026] [bibtex-entry]

Luigi Antelmi, Nicholas Ayache, Philippe Robert, and Marco Lorenzi. Sparse Multi-Channel Variational Autoencoder for the Joint Analysis of Heterogeneous Data. In ICML 2019 - 36th International Conference on Machine Learning, Long Beach, United States, June 2019. [bibtex-key = antelmi:hal-02154181] [bibtex-entry]

Benoît Audelan and Hervé Delingette. Unsupervised Quality Control of Image Segmentation based on Bayesian Learning. In MICCAI 2019 - 22nd International Conference on Medical Image Computing and Computer Assisted Intervention, Shenzhen, China, October 2019. Keyword(s): Image segmentation, Bayesian learning, Quality control. [bibtex-key = audelan:hal-02265131] [bibtex-entry]

Nicholas Ayache. AI and Healthcare: towards a Digital Twin?. In 5th International Symposium on Multidiscplinary Computational Anatomy, Fukuoka, Japan, March 2019. Note: Talk given by M. Nicholas Ayache at the MCA 2019. [bibtex-key = ayache:hal-02063234] [bibtex-entry]

Ibrahim Ayed, Nicolas Cedilnik, Patrick Gallinari, and Maxime Sermesant. EP-Net: Learning Cardiac Electrophysiology Models for Physiology-based Constraints in Data-Driven Predictions. In FIMH 2019 - 10th International Conference on Functional Imaging of the Hearth, Bordeaux, France, pages 55-63, June 2019. Springer. [bibtex-key = ayed:hal-02106618] [bibtex-entry]

Tania Bacoyannis, Julian Krebs, Nicolas Cedilnik, Hubert Cochet, and Maxime Sermesant. Deep Learning Formulation of ECGI for Data-driven Integration of Spatiotemporal Correlations and Imaging Information. In FIMH 2019 - 10th International Conference on Functional Imaging and Modeling of the Heart, volume LNCS 11504, Bordeaux, France, pages 20-28, June 2019. Springer. Keyword(s): ECGI, Deep learning, Generative Model, Simulation. [bibtex-key = bacoyannis:hal-02108958] [bibtex-entry]

Jaume Banus, Marco Lorenzi, Oscar Camara, and Maxime Sermesant. Large Scale Cardiovascular Model Personalisation for Mechanistic Analysis of Heart and Brain Interactions. In FIMH 2019 - 10th International Conference on Functional Imaging and Modeling of the Heart, Bordeaux, France, pages 285-293, June 2019. [bibtex-key = banus:hal-02361466] [bibtex-entry]

Nicolas Cedilnik, Josselin Duchateau, Frederic Sacher, Pierre Jaïs, Hubert Cochet, and Maxime Sermesant. Fully Automated Electrophysiological Model Personalisation Framework from CT Imaging. In FIMH 2019 - 10th International Conference on Functional Imaging and Modeling of the Heart, Bordeaux, France, pages 325-333, June 2019. Keyword(s): Model Personalisation, Segmentation, Deep learning, Imaging. [bibtex-key = cedilnik:hal-02106609] [bibtex-entry]

Nicolas Cedilnik, Shuman Jia, Pierre Jaïs, Hubert Cochet, and Maxime Sermesant. Automatic non-invasive substrate analysis from CT images in post-infarction VT. In EHRA 2019 - European Heart Rhythm Association, volume 21, Lisbonne, Portugal, pages 720-739, March 2019. [bibtex-key = cedilnik:hal-02181793] [bibtex-entry]

Nicolas Cedilnik and Maxime Sermesant. Eikonal Model Personalisation using Invasive Data to Predict Cardiac Resynchronisation Therapy Electrophysiological Response. In STACOM 2019 - 10th Workshop on Statistical Atlases and Computational Modelling of the Heart, Shenzen, China, October 2019. Keyword(s): Electrophysiology, Computer model, Personalisation, Cardiac resynchronisation therapy. [bibtex-key = cedilnik:hal-02368288] [bibtex-entry]

Gaëtan Desrues, Hervé Delingette, and Maxime Sermesant. Towards Hyper-Reduction of Cardiac Models using Poly-Affine Deformation. In STACOM 2019: Statistical Atlases and Computational Models of the Heart, Shenzhen, China, October 2019. [bibtex-key = desrues:hal-02429678] [bibtex-entry]

Sara Garbarino and Marco Lorenzi. Modeling and inference of spatio-temporal protein dynamics across brain networks. In IPMI 2019 - International Conference on Information Processing in Medical Imaging, volume 11492 of Lecture Notes in Computer Science book series, Hong Kong, Hong Kong SAR China, pages 57-69, June 2019. springer. Note: Bayesian non--parametric model, protein propagation, Alzheimer'sdisease, Gaussian process, dynamical systems, spatio--temporal model, disease progression modeling. [bibtex-key = garbarino:hal-02165021] [bibtex-entry]

Nicolas Guigui, Shuman Jia, Maxime Sermesant, and Xavier Pennec. Symmetric Algorithmic Components for Shape Analysis with Diffeomorphisms. In GSI 2019 - 4th conference on Geometric Science of Information, volume Lecture Notes in Computer Science 11712 of Proceedings of Geometric Science of Information, Toulouse, France, pages 759-768, August 2019. F. Nielsen and F. Barbaresco, Springer. Keyword(s): Symmetric Spaces, Parallel Transport, Shape Registration. [bibtex-key = guigui:hal-02148832] [bibtex-entry]

Julian Krebs, Tommaso Mansi, Nicholas Ayache, and Hervé Delingette. Probabilistic Motion Modeling from Medical Image Sequences: Application to Cardiac Cine-MRI. In STACOM 2019 - 10th Workshop on Statistical Atlases and Computational Modelling of the Heart, Shenzhen, China, October 2019. Note: Probabilistic Motion Model, Motion Tracking, Temporal Super-Resolution, Diffeomorphic Registration, Temporal Variational Autoencoder. [bibtex-key = krebs:hal-02239318] [bibtex-entry]

Georgios Lazaridis, Marco Lorenzi, Sebastien Ourselin, and David Garway-Heath. Enhancing OCT Signal by Fusion of GANs: Improving Statistical Power of Glaucoma Clinical Trials. In MICAI 2019 - 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, volume LNCS. LNIP - 11764 of Medical Image Computing and Computer Assisted Intervention -- MICCAI 2019, Shenzhen, China, pages 3-11, October 2019. Springer International Publishing. [bibtex-key = lazaridis:hal-03374557] [bibtex-entry]

Alexandre Legay, Thomas Tiennot, Jean-François Gelly, Maxime Sermesant, and Jean Bulté. End-to-end Cardiac Ultrasound Simulation for a Better Understanding of Image Quality. In STACOM 2019 - 10th International Workshop on Statistical Atlases and Computational Models of the Heart: Atrial Segmentation and LV Quantification Challenges, volume LNCS. LNIP - 12009 of Statistical Atlases and Computational Models of the Heart. Multi-Sequence CMR Segmentation, CRT-EPiggy and LV Full Quantification Challenges, Shenzhen, China, pages 167-175, October 2019. Springer International Publishing. Keyword(s): Ultrasound, Cardiac Modelling, Probe Design, Image Quality. [bibtex-key = legay:hal-03687459] [bibtex-entry]

Buntheng Ly, Hubert Cochet, and Maxime Sermesant. Style Data Augmentation for Robust Segmentation of Multi-Modality Cardiac MRI. In STACOM 2019 - 10th Workhop on Statistical Atlases and Computational Modelling of the Heart, Shenzhen, China, October 2019. Keyword(s): Deep Learning, Image segmentation, Cardiac Magnetic Resonance Imaging, Multi-modality, Late Gadolinium Enhanced. [bibtex-key = ly:hal-02401643] [bibtex-entry]

R azvan Marinescu, Marco Lorenzi, Stefano Blumberg, Alexandra Young, Pere Planell-Morell, Neil Oxtoby, Arman Eshaghi, Keir Yong, Sebastian Crutch, Polina Golland, and Daniel Alexander. Disease Knowledge Transfer Across Neurodegenerative Diseases. In MICCAI 2019 - 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, volume LNCS. LNIP - 11765 of Medical Image Computing and Computer Assisted Intervention -- MICCAI 2019, Shenzhen, China, pages 860-868, October 2019. Springer International Publishing. [bibtex-key = marinescu:hal-03374569] [bibtex-entry]

Pamela Moceri, Nicolas Duchateau, Delphine Baudouy, Céline Sanfiorenzo, Fabien Squara, Emile Ferrari, and Maxime Sermesant. Incremental prognostic value of changes in 3D right ventricular function in pulmonary hypertension. In JE SFC 2019 - 29es Journées Européennes de la Société Française de Cardiologie, Paris, France, January 2019. [bibtex-key = moceri:hal-02161692] [bibtex-entry]

Pamela Moceri, Nicolas Duchateau, Delphine Baudouy, Fabien Squara, Emile Ferrari, and Maxime Sermesant. 3D right ventricular strain and shape in volume overload: comparative analysis of Tetralogy of Fallot and atrial septal defect patients. In JE SFC 2019 - 29es Journées Européennes de la Société Française de Cardiologie, Paris, France, January 2019. [bibtex-key = moceri:hal-02161694] [bibtex-entry]

Yann Thanwerdas and Xavier Pennec. Exploration of Balanced Metrics on Symmetric Positive Definite Matrices. In GSI 2019 - 4th conference on Geometric Science of Information, volume Lecture Notes in Computer Science 11712 of Proceedings of Geometric Science of Information, Toulouse, France, pages 484-493, August 2019. Springer. Keyword(s): Dually flat connections, SPD matrices, Information geometry. [bibtex-key = thanwerdas:hal-02158525] [bibtex-entry]

Yann Thanwerdas and Xavier Pennec. Is affine invariance well defined on SPD matrices? A principled continuum of metrics. In GSI 2019 - 4th conference on Geometric Science of Information, volume Lecture Notes in Computer Science 11712 of Proceedings of Geometric Science of Information, Toulouse, France, pages 502-510, August 2019. Springer. Keyword(s): SPD matrices, Riemannian symmetric spaces. [bibtex-key = thanwerdas:hal-02147020] [bibtex-entry]

Zihao Wang, Clair Vandersteen, Thomas Demarcy, Dan Gnansia, Charles Raffaelli, Nicolas Guevara, and Hervé Delingette. Deep Learning based Metal Artifacts Reduction in post-operative Cochlear Implant CT Imaging. In MICCAI 2019 - 22nd International Conference on Medical Image Computing and Computer Assisted Intervention, Shenzhen, China, pages 121-129, October 2019. Keyword(s): Metal Artifacts Reduction, Generative adversarial networks. [bibtex-key = wang:hal-02196557] [bibtex-entry]

Wilhelm Wimmer, Clair Vandersteen, Nicolas Guevara, Marco Caversaccio, and Hervé Delingette. Robust Cochlear Modiolar Axis Detection in CT. In MICCAI 2019 - 22nd International Conference on Medical Image Computing and Computer Assisted Intervention, Medical Image Computing and Computer Assisted Intervention -- MICCAI 2019. MICCAI 2019. Lecture Notes in Computer Science, Shenzhen, China, pages 3-10, October 2019. Keyword(s): Approximate maximum like-lihood, Natural growth, Kinematic surface recognition. [bibtex-key = wimmer:hal-02402475] [bibtex-entry]

Yingyu Yang, Stephane Gillon, Jaume Banus, Pamela Moceri, and Maxime Sermesant. Non-Invasive Pressure Estimation in Patients with Pulmonary Arterial Hypertension: Data-driven or Model-based?. In STACOM 2019 - 10th Workshop on Statistical Atlases and Computational Modelling of the Heart, Shenzhen, China, October 2019. Keyword(s): Cardiac modelling, Machine learning, Pulmonary hypertension. [bibtex-key = yang:hal-02382941] [bibtex-entry]

Clement Abi Nader, Nicholas Ayache, Philippe Robert, and Marco Lorenzi. Alzheimer's Disease Modelling and Staging through Independent Gaussian Process Analysis of Spatio-Temporal Brain Changes. In Machine Learning in Clinical Neuroimaging (MLCN) workshop, Granada, Spain, September 2018. Keyword(s): Alzheimer's Disease, Disease Progression Modelling, Gaussian Process. [bibtex-key = abinader:hal-01882450] [bibtex-entry]

Luigi Antelmi, Nicholas Ayache, Philippe Robert, and Marco Lorenzi. Multi-Channel Stochastic Variational Inference for the Joint Analysis of Heterogeneous Biomedical Data in Alzheimer's Disease. In Understanding and Interpreting Machine Learning in Medical Image Computing Applications, volume 11038 of LNCS, Granada, Spain, pages 15-23, September 2018. [bibtex-key = antelmi:hal-02397737] [bibtex-entry]

Bidisha Chakraborty, Sophie Giffard-Roisin, Martino Alessandrini, Brecht Heyde, M Sermesant, and Jan d'Hooge. Estimation of the Spatial Resolution of a 2D Strain Estimator Using Synthetic Cardiac Images. In IUS 2018 - IEEE International Ultrasonics Symposium, Kobe, Japan, pages 1-9, October 2018. IEEE. [bibtex-key = chakraborty:hal-02024010] [bibtex-entry]

Shuman Jia, Antoine Despinasse, Zihao Wang, Hervé Delingette, Xavier Pennec, Pierre Jaïs, Hubert Cochet, and Maxime Sermesant. Automatically Segmenting the Left Atrium from Cardiac Images Using Successive 3D U-Nets and a Contour Loss. In STACOM: Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges, volume 11395 of LNCS, Granada, Spain, pages 221-229, September 2018. Keyword(s): distance map, ensemble prediction, loss function, contour loss, left atrium, deep learning, segmentation, 3D U-Net. [bibtex-key = jia:hal-01860285] [bibtex-entry]

Shuman Jia, Nicolas Duchateau, Pamela Moceri, Maxime Sermesant, and Xavier Pennec. Parallel Transport of Surface Deformations from Pole Ladder to Symmetrical Extension. In Shape in Medical Imaging. ShapeMI 2018., volume 11167 of LNCS, Granada, Spain, pages 116-124, September 2018. Springer. [bibtex-key = jia:hal-01860274] [bibtex-entry]

Julian Krebs, Tommaso Mansi, Boris Mailhé, Nicholas Ayache, and Hervé Delingette. Unsupervised Probabilistic Deformation Modeling for Robust Diffeomorphic Registration. In Deep Learning in Medical Image Analysis (MICCAI workshop), Granada, Spain, September 2018. Keyword(s): Image registration, Deep learning, Medical imaging analysis. [bibtex-key = krebs:hal-01845688] [bibtex-entry]

Marco Lorenzi and Maurizio Filippone. Constraining the Dynamics of Deep Probabilistic Models. In ICML 2018 - The 35th International Conference on Machine Learning, volume 80 of PMLR - Proceedings of Machine Learning Research, Stockholm, Sweden, pages 3233-3242, July 2018. Note: 13 pages. Keyword(s): machine learning, dynamical systems, gradient matching, gaussian process. [bibtex-key = lorenzi:hal-01843006] [bibtex-entry]

Pamela Moceri, Nicolas Duchateau, D Baudouy, C Sanfiorenzo, F Squara, E. Ferrari, and M Sermesant. Incremental prognostic value of changes in 3D right ventricular function in pulmonary hypertension. In ESC congress, Munich, Germany, 2018. [bibtex-key = moceri:hal-01994488] [bibtex-entry]

Pamela Moceri, Nicolas Duchateau, Delphine Baudouy, Fabien Squara, Emile Ferrari, and M Sermesant. Volume overload impact on 3D right ventricular shape and strain: comparative analysis of tetralogy of Fallot and atrial septal defect patients. In ESC congress, Munich, Germany, 2018. [bibtex-key = moceri:hal-01994486] [bibtex-entry]

Pamela Moceri, Nicolas Duchateau, N Dursent, Xavier Iriart, Sébastien Hascoet, Delphine Baudouy, Emile Ferrari, and M Sermesant. Right ventricular remodelling in CHD-PAH patients using 3D speckle tracking. In EuroEcho 2018 - 22nd Annual Congressof the European Association of Cardiovascular Imaging, Milan, Italy, December 2018. [bibtex-key = moceri:hal-01994483] [bibtex-entry]

Pamela Moceri, Nicolas Duchateau, Benjamin Sartre, M Sermesant, and Emile Ferrari. Right ventricular function in acute pulmonary embolism: a three-dimensional strain study. In Euroecho, Milan, Italy, 2018. [bibtex-key = moceri:hal-01994484] [bibtex-entry]

Fanny Orlhac, Charles Bouveyron, Thierry Pourcher, Lun Jing, Jean-Marie Guigonis, Jacques Darcourt, Nicholas Ayache, and Olivier Humbert. Identification des cancers mammaires triple-négatifs : analyse statistique de variables radiomiques issues des images TEP et de variables métabolomiques. In 2018 - 4èmes Journées Francophones de Médecine Nucléaire, volume 42 of Médecine Nucléaire, Lille, France, pages 169, May 2018. Keyword(s): Analyse de texture, Cancer du sein, Hétérogénéité tumorale, Traitement des images, Triple-négatif. [bibtex-key = orlhac:hal-01736154] [bibtex-entry]

Fanny Orlhac, Olivier Humbert, Sarah Boughdad, Maud Lasserre, Michael Soussan, Christophe Nioche, Nicholas Ayache, Jacques Darcourt, Frédérique Frouin, and Irène Buvat. Validation d'une méthode d'harmonisation des mesures SUV et des variables radiomiques pour les études TEP multicentriques rétrospectives. In 2018 - 4èmes Journées Francophones de Médecine Nucléaire, volume 42, Lille, France, pages 170, May 2018. Keyword(s): Etude multicentrique, Normalisation, Quantification, Analyse de texture, Hétérogénéité tumorale. [bibtex-key = orlhac:hal-01736147] [bibtex-entry]

Fanny Orlhac, Olivier Humbert, Sarah Boughdad, Maud Lasserre, Michael Soussan, Christophe Nioche, Nicholas Ayache, Jacques Darcourt, Frédérique Frouin, and Irène Buvat. Validation of a harmonization method to correct for SUV and radiomic features variability in multi-center studies. In SNMMI Annual Meeting, volume 59, Philadelphia, United States, pages 288, June 2018. [bibtex-key = orlhac:hal-01759334] [bibtex-entry]

Fanny Orlhac, Olivier Humbert, Thierry Pourcher, Lun Jing, Jean-Marie Guigonis, Jacques Darcourt, Nicholas Ayache, and Charles Bouveyron. Analyse statistique de données radiomiques et métabolomiques : prédiction des lésions mammaires triple-négatives. In 12ème Conférence Francophone d'Epidémiologie Clinique (EPICLIN) et 25èmes Journées des statisticiens des Centre de Lutte Contre le Cancer (CLCC), volume 66 of Revue d'épidémiologie et de santé publique, Nice, France, pages S180-S181, May 2018. Keyword(s): Métabolomique, Analyse statistique, Analyse discriminante, Sélection de variables, Radiomique. [bibtex-key = orlhac:hal-01736164] [bibtex-entry]

Fanny Orlhac, Olivier Humbert, Thierry Pourcher, Lun Jing, Jean-Marie Guigonis, Jacques Darcourt, Nicholas Ayache, and Charles Bouveyron. Statistical analysis of PET radiomic features and metabolomic data: prediction of triple-negative breast cancer. In SNMMI Annual Meeting, volume 59, Philadelphia, United States, pages 1755, June 2018. [bibtex-key = orlhac:hal-01759330] [bibtex-entry]

Santiago Silva, Boris A Gutman, Eduardo Romero, Paul M. Thompson, Andre Altmann, and Marco Lorenzi. Federated Learning in Distributed Medical Databases: Meta-Analysis of Large-Scale Subcortical Brain Data. In International Symposium on Biomedical Imaging, Venice, Italy, April 2018. [bibtex-key = silva:hal-01963637] [bibtex-entry]

Wen Wei, Emilie Poirion, Benedetta Bodini, Stanley Durrleman, Nicholas Ayache, Bruno Stankoff, and Olivier Colliot. Learning Myelin Content in Multiple Sclerosis from Multimodal MRI through Adversarial Training. In MICCAI 2018 -- 21st International Conference On Medical Image Computing & Computer Assisted Intervention, volume 11072, Granada, Spain, September 2018. [bibtex-key = wei:hal-01810822] [bibtex-entry]

Wen Wei, Emilie Poirion, Benedetta Bodini, Stanley Durrleman, Olivier Colliot, Bruno Stankoff, and Nicholas Ayache. FLAIR MR Image Synthesis By Using 3D Fully Convolutional Networks for Multiple Sclerosis. In ISMRM-ESMRMB 2018 - Joint Annual Meeting, Paris, France, pages 1-6, June 2018. [bibtex-key = wei:hal-01723070] [bibtex-entry]

Nicolas Cedilnik, Josselin Duchateau, Rémi Dubois, Pierre Jaïs, Hubert Cochet, and Maxime Sermesant. VT Scan: Towards an Efficient Pipeline from Computed Tomography Images to Ventricular Tachycardia Ablation. In Functional Imaging and Modelling of the Heart, Functional Imaging and Modelling of the Heart, Toronto, Canada, pages 271-279, June 2017. Springer International Publishing. Keyword(s): Electrophysiological modelling, Heart imaging, Ventricular tachycardia, Catheter ablation. [bibtex-key = cedilnik:hal-01498672] [bibtex-entry]

Loïc Devilliers, Xavier Pennec, and Stéphanie Allassonnière. Inconsistency of Template Estimation with the Fréchet mean in Quotient Space. In Information Processing in Medical Imaging. IPMI 2017., volume 10265 of LNCS, Boone, United States, pages 16-27, June 2017. Martin Styner and Marc Niethammer and Dinggang Shen and Stephen Aylward and Ipek Oguz and Hongtu Zhu. [bibtex-key = devilliers:hal-01481074] [bibtex-entry]

Rubén Doste, David Soto-Iglesias, Gabriel Bernardino, Rafael Sebastian, Sophie Giffard-Roisin, Rocìo Cabrera-Lozoya, Maxime Sermesant, Antonio Berruezo, Damián Sánchez-Quintana, and Oscar Camara. A Rule-Based Method to Model Myocardial Fiber Orientation for Simulating Ventricular Outflow Tract Arrhythmias. In Lecture Notes in Computer Science, editor, Functional imaging and modelling of the heart 2017, volume 10263 of Functional imaging and modelling of the heart 2017 Proceedings, Toronto, Canada, June 2017. Keyword(s): Fiber orientation, Rule-based method, Electrophysiological simulations, Arrhythmias, Outflow tracts. [bibtex-key = doste:hal-01533389] [bibtex-entry]

Sophie Giffard-Roisin, Hervé Delingette, Thomas Jackson, Lauren Fovargue, Jack Lee, Aldo Rinaldi, Nicholas Ayache, Reza Razavi, and Maxime Sermesant. Sparse Bayesian Non-linear Regression for Multiple Onsets Estimation in Non-invasive Cardiac Electrophysiology. In Mihaela Pop, editor, Functional imaging and modelling of the heart 2017, Functional imaging and modelling of the heart 2017, Toronto, Canada, pages 230-238, June 2017. Springer International Publishing. Note: Best paper award FIMH 2017, category: Electrophysiology. Keyword(s): ECG Imaging, Cardiac Electrophysiology, Relevance Vector Machine, Personalisation. [bibtex-key = giffardroisin:hal-01498602] [bibtex-entry]

Shuman Jia, Claudia Camaioni, Marc-Michel Rohé, Pierre Jaïs, Xavier Pennec, Hubert Cochet, and Maxime Sermesant. Prediction of Post-Ablation Outcome in Atrial Fibrillation Using Shape Parameterization and Partial Least Squares Regression. In FIMH 2017 - International Conference on Functional Imaging and Modeling of the Heart, volume 10263 of Lecture Notes in Computer Science, Toronto, Canada, pages 314 - 321, June 2017. Keyword(s): atrial fibrillation, catheter ablation, post-ablation outcome, left atrial remodeling, statistical shape analysis, partial least squares, regression. [bibtex-key = jia:hal-01574831] [bibtex-entry]

Julian Krebs, Tommaso Mansi, Hervé Delingette, Li Zhang, Florin C Ghesu, Shun Miao, Andreas Maier, Nicholas Ayache, Rui Liao, and Ali Kamen. Robust non-rigid registration through agent-based action learning. In Medical Image Computing and Computer Assisted Interventions (MICCAI), Medical Image Computing and Computer Assisted Intervention -- MICCAI 2017, Quebec, Canada, pages 344-352, September 2017. Springer International Publishing. Keyword(s): reinforcement learning, Image registration. [bibtex-key = krebs:hal-01569447] [bibtex-entry]

Eric Lluch, Rubén Doste, Sophie Giffard-Roisin, Alexandre This, Maxime Sermesant, Oscar Camara, Mathieu de Craene, and Hernán G Morales. Smoothed Particle Hydrodynamics for Electrophysiological Modeling: An Alternative to Finite Element Methods. In FIMH 2017 - 9th International Conference on Functional Imaging and Modelling of the Heart, volume 141 of Functional imaging and modelling of the heart 2017 Proceedings, Toronto, Canada, pages 333-343, June 2017. Springer International Publishing. Keyword(s): Meshless, FEM, Cardiac electrophysiology, SPH. [bibtex-key = lluch:hal-01533371] [bibtex-entry]

R azvan Valentin Marinescu, Arman Esaghi, Marco Lorenzi, Alexandra L. Young, Neil P. Oxtoby, Sara Garbarino, Timothy J. Shakespeare, Sebastian Crutch, and Daniel C Alexander. A Vertex Clustering Model for Disease Progression: Application to Cortical Thickness Images. In International Conference on Information Processing in Medical Imaging (IPMI), Boone, United States, July 2017. [bibtex-key = marinescu:hal-01843387] [bibtex-entry]

Kristin Mcleod, Maxime Sermesant, and Xavier Pennec. Improving Understanding of Long-Term Cardiac Functional Remodelling via Cross-Sectional Analysis of Polyaffine Motion Parameters. In FIMH 2017 - 9th International Conference on Functional Imaging and Modeling of the Heart, volume 10263 of Lecture Notes in Computer Science, Toronto, Canada, pages 51 - 59, June 2017. Springer. [bibtex-key = mcleod:hal-01574837] [bibtex-entry]

Pamela Moceri, Nicolas Duchateau, Delphine Baudouy, Elie-Dan Schouver, P Bouvier, S Leroy, P Cerboni, P Gibelin, Maxime Sermesant, and Emile Ferrari. Three-dimensional speckle tracking of the right ventricle : implications on survival. In Journées Européennes de la Société Française de Cardiologie, Paris, France, 2017. [bibtex-key = moceri:hal-02161690] [bibtex-entry]

P Moceri, M Sermesant, D Baudouy, E. Ferrari, and Nicolas Duchateau. 3D right ventricular strain: comparative analysis of Tetralogy of Fallot and atrial septal defect. In Euroecho-Imaging 2017 - Twenty-First Annual Meeting of the European Association of Echocardiography, Lisbon, Portugal, December 2017. [bibtex-key = moceri:hal-01994491] [bibtex-entry]

Roch Molléro, Hervé Delingette, Manasi Datar, Tobias Heimann, Jakob Hauser, Dilveer Panesar, Alexander Jones, Andrew Taylor, Marcus Kelm, Titus Kuehne, Marcello Chinali, Gabriele Rinelli, Nicholas Ayache, Xavier Pennec, and Maxime Sermesant. Longitudinal Analysis using Personalised 3D Cardiac Models with Population-Based Priors: Application to Paediatric Cardiomyopathies. In Medical Image Computing and Computer Assisted Intervention (MICCAI), Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2017, Québec City, Canada, pages 350-358, September 2017. Springer International Publishing. [bibtex-key = mollero:hal-01569735] [bibtex-entry]

Roch Molléro, Jakob Hauser, Xavier Pennec, Manasi Datar, Hervé Delingette, Alexander Jones, Nicholas Ayache, Tobias Heimann, and Maxime Sermesant. Longitudinal Parameter Estimation in 3D Electromechanical Models: Application to Cardiovascular Changes in Digestion. In FIMH 2017 - 9th international conference on Functional Imaging and Modeling of the Heart, Functional Imaging and Modelling of the Heart, Toronto, Canada, pages 432-440, June 2017. Springer International Publishing. [bibtex-key = mollero:hal-01522598] [bibtex-entry]

Xavier Pennec. Sample-limited L p Barycentric Subspace Analysis on Constant Curvature Spaces. In Geometric Sciences of Information (GSI 2017), Geometric Science of Information, Paris, France, pages 20-28, November 2017. Springer International Publishing. [bibtex-key = pennec:hal-01574895] [bibtex-entry]

Marc-Michel Rohé, Manasi Datar, Tobias Heimann, Maxime Sermesant, and Xavier Pennec. SVF-Net: Learning Deformable Image Registration Using Shape Matching. In MICCAI 2017 - the 20th International Conference on Medical Image Computing and Computer Assisted Intervention, Medical Image Computing and Computer Assisted Intervention -- MICCAI 2017, Québec, Canada, pages 266-274, September 2017. Springer International Publishing. Keyword(s): Deep Learning, Cardiac Imaging, Registration. [bibtex-key = rohe:hal-01557417] [bibtex-entry]

Marc-Michel Rohé, Maxime Sermesant, and Xavier Pennec. Automatic Multi-Atlas Segmentation of Myocardium with SVF-Net. In STACOM: Statistical Atlases and Computational Models of the Heart. ACDC and MMWHS Challenges, volume 10663 of LNCS, Québec, Canada, pages 170-177, September 2017. [bibtex-key = rohe:hal-01575297] [bibtex-entry]

Jan L. Bruse, Kristin Mcleod, Elena Cervi, Giovanni Biglino, T.-y Hsia, Maxime Sermesant, Xavier Pennec, Andrew Taylor, and Silvia Schievano. Discovering clusters in pathologic cardiac morphology: MR-based hierarchical 3D shape clustering of surgically repaired aortic arches. In Computer Assisted Radiology, 30th International Congress and Exhibition, Heidelberg, Germany, June 2016. [bibtex-key = bruse:hal-01519862] [bibtex-entry]

Claire Cury, Marc M Lorenzi, David M Cash, Jennifer M Nicholas, Alexandre M Routier, Jonathan Rohrer, Sebastien M Ourselin, Stanley M Durrleman, and Marc M Modat. Spatio-Temporal Shape Analysis of Cross-Sectional Data for Detection of Early Changes in Neurodegenerative Disease. In Martin Reuter, Christian Wachinger, and Hervé Lombaert, editors, SeSAMI 2016 - First International Workshop Spectral and Shape Analysis in Medical Imaging, volume 10126 of Spectral and Shape Analysis in Medical Imaging, Athens, Greece, pages 63 - 75, September 2016. Springer. Keyword(s): thalamus, spatio-temporal geodesic regression, FTD, parallel transport, shape. [bibtex-key = cury:hal-01440061] [bibtex-entry]

Thomas Demarcy, Clair Vandersteen, Dan Gnansia, Charles Raffaelli, Hervé Delingette, Nicholas Ayache, and Nicolas Guevara. Estimation de la position post-implantation cochléaire de l'électrode à partir d'images tomodensitométriques cliniques. In 123ème Congrès de la Société Française d'Oto-Rhino-Laryngologie et de Chirurgie de la Face et du Cou, Annales françaises d'Oto-rhino-laryngologie et de Pathologie Cervico-faciale, Paris, France, October 2016. Congrès de la Société Française d'Oto-Rhino-Laryngologie et de Chirurgie de la Face et du Cou. Keyword(s): Cochlear Implant, Computed Tomography. [bibtex-key = demarcy:hal-01398676] [bibtex-entry]

Thomas Demarcy, Clair Vandersteen, Charles Raffaelli, Dan Gnansia, Nicolas Guevara, Nicholas Ayache, and Hervé Delingette. Uncertainty Quantification of Cochlear Implant Insertion from CT Images. In Raj Shekhar, Stefan Wesarg, Miguel Angel Gonzalez Ballester, Klaus Drechsler, Yoshinobu Sato, Marius Erdt, Marius George Linguraru, and Cristina Oyarzun Laura, editors, 5th International Workshop on Clinical Image-Based Procedures - CLIP 2016, Held in Conjunction with MICCAI 2016, volume 9958 of Lecture Notes in Computer Science, Athens, Greece, pages 27-35, October 2016. Springer. Keyword(s): cochlear implant, uncertainty quantification, shape modeling. [bibtex-key = demarcy:hal-01393323] [bibtex-entry]

Nicolas Duchateau, Mathieu de Craene, Pascal Allain, Eric Saloux, and Maxime Sermesant. Infarct localization from myocardial deformation: Prediction and uncertainty quantification by regression from a low-dimensional space. In GRIC - Journées Francophones de Radiologie, Paris, France, 2016. [bibtex-key = duchateau:hal-02161688] [bibtex-entry]

Sophie Giffard-Roisin, Lauren Fovargue, Jessica Webb, Roch Molléro, Jack Lee, Hervé Delingette, Nicholas Ayache, Reza Razavi, and Maxime Sermesant. Estimation of Purkinje Activation from ECG: an Intermittent Left Bundle Branch Block Study. In 7th International Statistical Atlases and Computational Modeling of the Heart (STACOM) Workshop, Held in Conjunction with MICCAI 2016, Lecture Notes in Computer Science, Athens, Greece, October 2016. Note: In press. Keyword(s): Electrophysiology, Electrophysiological Model, Forward EP Model, Parameter Estimation, Purkinje System. [bibtex-key = giffardroisin:hal-01372924] [bibtex-entry]

Shuman Jia, Loïc Cadour, Hubert Cochet, and Maxime Sermesant. STACOM-SLAWT Challenge: Left Atrial Wall Segmentation and Thickness Measurement Using Region Growing and Marker-Controlled Geodesic Active Contour. In 7th International Statistical Atlases and Computational Modeling of the Heart (STACOM) Workshop, Held in Conjunction with MICCAI 2016, volume 10124 of LNCS, Athens, Greece, pages 211-219, October 2016. Springer. Keyword(s): geodesic active contour, atrial fibrillation, left atrial wall thickness, 3-dimensional image segmentation, cardiac computed tomography (CT), region growing. [bibtex-key = jia:hal-01373238] [bibtex-entry]

Stephanie Marchesseau, Nicolas Duchateau, and Hervé Delingette. Segmentation and registration coupling from short-axis Cine MRI: application to infarct diagnosis. In 7th International Statistical Atlases and Computational Modeling of the Heart (STACOM) Workshop, Held in Conjunction with MICCAI 2016, volume 10124 of Lecture Notes in Computer Science, Athens, Greece, pages 48-56, October 2016. Note: In press. Keyword(s): Regional Volumes, Segmentation, Registration, Infarct diagnosis. [bibtex-key = marchesseau:hal-01352460] [bibtex-entry]

Pamela Moceri, Nicolas Duchateau, Delphine Baudouy, Sylvie Leroy, Priscille Bouvier, Elie Dan Schouver, Maxime Sermesant, and Emile Ferrari. Three-dimensional speckle tracking of the right ventricle: implications on survival in pulmonary hypertension. In European Society of Cardiology (ESC) Congress, volume 37 of European Heart Journal, Abstracts from the European Society of Cardiology (ESC) Congress, Rome, Italy, pages 994, August 2016. [bibtex-key = moceri:hal-01315011] [bibtex-entry]

Roch Molléro, Xavier Pennec, Hervé Delingette, Nicholas Ayache, and Maxime Sermesant. A Multiscale Cardiac Model for Fast Personalisation and Exploitation. In MICCAI 2016 - Medical Image Computing and Computer Assisted Intervention, volume 9902 of MICCAI 2016, Lecture Notes in Computer Science, Athens, Greece, pages 174-182, October 2016. [bibtex-key = mollero:hal-01360908] [bibtex-entry]

Marc-Michel Rohé, Roch Molléro, Maxime Sermesant, and Xavier Pennec. Highly Reduced Model of the Cardiac Function for Fast Simulation. In IEEE - IVMSP Workshop 2016, Image, Video, and Multidimensional Signal Processing Workshop (IVMSP), 2016 IEEE 12th, Bordeaux, France, pages 5, July 2016. IEEE. Keyword(s): Reduction Order Model, Biomechanical Model, Simulation 3D. [bibtex-key = rohe:hal-01373715] [bibtex-entry]

Marc-Michel Rohé, Maxime Sermesant, and Xavier Pennec. Barycentric Subspace Analysis: a new Symmetric Group-wise Paradigm for Cardiac Motion Tracking. In MICCAI 2016 - Medical Image Computing and Computer Assisted Intervention, volume 9902 of MICCAI 2016, Lecture Notes in Computer Science, Athens, Greece, pages 300-307, October 2016. Keyword(s): Medical Image Analysis, Atlas Framework, Registration, Manifold atlas. [bibtex-key = rohe:hal-01373706] [bibtex-entry]

Sergio Sanchez-Martinez, Nicolas Duchateau, Tamas Erdei, Gabor Kunszt, Anna Degiovanni, Erberto Carluccio, Alan Fraser, Gemma Piella, and Bart Bijnens. Machine-learning based diagnosis of heart failure with preserved ejection fraction: how much do we agree with the guidelines?. In EuroEcho-Imaging, European Heart Journal: Cardiovascular Imaging, Abstracts from the EuroEcho-Imaging congress, Leipzig, Germany, December 2016. Note: In press. [bibtex-key = sanchezmartinez:hal-01352285] [bibtex-entry]

Yitian Zhou, Mathieu de Craene, Maxime Sermesant, and Olivier Bernard. Phase-Based Registration of Cardiac Tagged MR Images by Incorporating Anatomical Constraints. In International Workshop on Statistical Atlases and Computational Models of the Heart, Athens, Greece, pages 39-47, October 2016. Keyword(s): Cardiac tagged MR, Strain, Tag number constant constraint. [bibtex-key = zhou:hal-02048117] [bibtex-entry]

Yitian Zhou, Mathieu de Craene, Oudom Somphone, Maxime Sermesant, and Olivier Bernard. Generation of Realistic 4D Synthetic CSPAMM Tagged MR Sequences for Benchmarking Cardiac Motion Tracking Algorithms. In International Workshop on Simulation and Synthesis in Medical Imaging, Athens, Greece, pages 108-117, October 2016. [bibtex-key = zhou:hal-02048135] [bibtex-entry]

Martino Alessandrini, Adrian Basarab, Mathieu de Craene, Maxime Sermesant, Hervé Liebgott, Olivier Bernard, and Jan d'Hooge. The role of the image phase in cardiac strain imaging. In EUSIPCO 2015 - 23rd European Signal Processing Conference, Nice, France, pages 2796-2800, August 2015. IEEE. Keyword(s): Simulations, Medical imaging, Heart, Quality assurance, Echocardiography, MRI, Deformation imaging. [bibtex-key = alessandrini:hal-01265886] [bibtex-entry]

Martino Alessandrini, Brecht Heyde, Sophie Giffard-Roisin, Hervé Delingette, Maxime Sermesant, Pascal Allain, Olivier Bernard, Mathieu de Craene, and Jan d'Hooge. Generation of ultra-realistic synthetic echocardiographic sequences to facilitate standardization of deformation imaging. In International Symposium on BIOMEDICAL IMAGING: From Nano to Macro (ISBI 2015), New York, United States, pages 756-759, April 2015. [bibtex-key = alessandrini:hal-01117557] [bibtex-entry]

Stéphanie Allassonnière, Loïc Devilliers, and Xavier Pennec. Estimating the Template in the Total Space with the Fréchet Mean on Quotient Spaces may have a Bias: a Case Study on Vector Spaces Quotiented by the Group of Translations. In Mathematical Foundations of Computational Anatomy (MFCA'15), Proceedings of the fifth international workshop on Mathematical Foundation sof Computational Anatomy (MFCA'15), Munich, Germany, pages 131-142, October 2015. [bibtex-key = allassonniere:hal-01203816] [bibtex-entry]

Chloé Audigier, Tommaso Mansi, Hervé Delingette, Saikiran Rapaka, Tiziano Passerini, Viorel Mihalef, Raoul Pop, Michele Diana, Luc Soler, Ali Kamen, Dorin Comaniciu, and Nicholas Ayache. Challenges to Validate Multi-physics Model of Liver Tumor Radiofrequency Ablation from Pre-clinical Data. In Computational Biomechanics for Medicine X, Munich, Germany, pages 29-40, October 2015. [bibtex-key = audigier:hal-01184543] [bibtex-entry]

Héloïse Bleton, Jan Margeta, Herve Lombaert, Hervé Delingette, and Nicholas Ayache. Myocardial Infarct Localization using Neighborhood Approximation Forests. In Statistical Atlases and Computational Modeling of the Heart (STACOM 2015), Munich, Germany, October 2015. Keyword(s): Machine Learning, Neighbourhood Approximation Forests, myocardial infarction, wall thickness. [bibtex-key = bleton:hal-01203579] [bibtex-entry]

Jan L. Bruse, Kristin Mcleod, Giovanni Biglino, Hopewell N. Ntsinjana, Claudio Capelli, Tain-Yen Hsia, Maxime Sermesant, Xavier Pennec, Andrew Taylor, and Silvia Schievano. A Non-parametric Statistical Shape Model for Assessment of the Surgically Repaired Aortic Arch in Coarctation of the Aorta: How Normal is Abnormal?. In Statistical Atlases and Computational Modeling of the Heart (STACOM 2015), volume 9534 of Lecture Notes in Computer Science, Munich, Germany, October 2015. Springer. [bibtex-key = bruse:hal-01205515] [bibtex-entry]

Hadrien Courtecuisse, Yinoussa Adagolodjo, Hervé Delingette, Christian Duriez, and Yinoussa Adagolodjo. Haptic Rendering of Hyperelastic Models with Friction. In 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Hamburg, Germany, pages 591-596, September 2015. IEEE. [bibtex-key = courtecuisse:hal-01184113] [bibtex-entry]

Nicolas Duchateau, Nerea Mangado, Mario Ceresa, Pavel Mistrik, Sergio Vera, and Miguel Angel Gonzalez Ballester. Virtual cochlear electrode insertion via parallel transport frame. In Biomedical Imaging (ISBI), 2015 IEEE 12th International Symposium on, Biomedical Imaging (ISBI), 2015 IEEE 12th International Symposium on, New York, France, pages 1398 - 1401, April 2015. [bibtex-key = duchateau:hal-01207989] [bibtex-entry]

Nicolas Duchateau and Maxime Sermesant. Prediction of infarct localization from myocardial deformation. In Statistical Atlases and Computational Modeling of the Heart (STACOM 2015), volume 9534 of Statistical Atlases and Computational Modeling of the Heart, Munich, Germany, October 2015. [bibtex-key = duchateau:hal-01208019] [bibtex-entry]

Nicolas Duchateau, Maxime Sermesant, Pierre Gibelin, Emile Ferrari, and Pamela Moceri. 3D regional right ventricular function in pulmonary hypertension. In EuroEcho-Imaging, volume 16 of European Heart Journal: Cardiovascular Imaging, Abstracts from the EuroEcho-Imaging congress., Seville, Spain, pages ii69, 2015. [bibtex-key = duchateau:hal-01217956] [bibtex-entry]

Nicolas Duchateau, Mathieu de Craene, Damien Legallois, Fabien Labombarda, Arnaud Pellissier, Maxime Sermesant, and Eric Saloux. Statistical significance of 3D motion and deformation indexes for the analysis of LAD infarction. In EuroEcho-Imaging, volume 16 of European Heart Journal: Cardiovascular Imaging, Abstracts from the EuroEcho-Imaging congress, Seville, Spain, pages ii81, 2015. [bibtex-key = duchateau:hal-01217963] [bibtex-entry]

Pietro Gori, Olivier Colliot, Linda Marrakchi-Kacem, Yulia Worbe, Alexandre Routier, Cyril Poupon, Andreas Hartmann, Nicholas Ayache, and Stanley Durrleman. Joint Morphometry of Fiber Tracts and Gray Matter structures using Double Diffeomorphisms. In IPMI - Information Processing in Medical Imaging, volume 9123 of Lecture Notes in Computer Science, Isle of Skye, United Kingdom, pages 275-287, June 2015. Keyword(s): diffeomorphism, morphometry, atlas, structural connectivity, shape. [bibtex-key = gori:hal-01142628] [bibtex-entry]

Pietro Gori, Olivier Colliot, Linda Marrakchi-Kacem, Yulia Worbe, Alexandre Routier, Cyril Poupon, Andreas Hartmann, Nicholas Ayache, and Stanley Durrleman. Unified analysis of shape and structural connectivity of neural pathways. In Organisation for Human Brain Mapping, Honolulu, United States, 2015. [bibtex-key = gori:hal-01187461] [bibtex-entry]

Vikash Gupta, Grégoire Malandain, Nicholas Ayache, and Xavier Pennec. A framework for creating population specific multimodal brain atlas using clinical T1 and diffusion tensor images. In MICCAI 2015 Workshop on Computational Diffusion MRI (CDMRI'15), Computational Diffusion MRI, Munich, Germany, pages 99-108, October 2015. Keyword(s): Multimodal brain atlas, Probabilistic white matter parcel-lation map, HIV, DTI-T1 brain template. [bibtex-key = gupta:hal-01261115] [bibtex-entry]

Bishesh Khanal, Marco Lorenzi, Nicholas Ayache, and Xavier Pennec. Simulating Patient Specific Multiple Time-point MRIs From a Biophysical Model of Brain Deformation in Alzheimer's Disease. In Workshop on Computational Biomechanics for Medicine - X, Computational Biomechanics for Medicine: Imaging, Modeling and Computing, Munich, France, pages 167-176, October 2015. Springer International Publishing. Keyword(s): biophysical modeling, Alzheimer's disease, biomechanical simulation, MRI, longitudinal MRI. [bibtex-key = khanal:hal-01217080] [bibtex-entry]

Herve Lombaert, Michael Arcaro, and Nicholas Ayache. Brain Transfer: Spectral Analysis of Cortical Surfaces and Functional Maps. In Sebastien Ourselin, Daniel C. Alexander, Carl-Fredrik Westin, and M. Jorge Cardoso, editors, Information Processing in Medical Imaging (IPMI 2015), volume 9123 of Lecture Notes in Computer Science, Scotland, United Kingdom, pages 474-487, July 2015. Springer. [bibtex-key = lombaert:hal-01203570] [bibtex-entry]

Herve Lombaert, Michael Arcaro, Sabine Kastner, and Nicholas Ayache. Brain Transfer for the Analysis of Cortical Data. In Society for Neuroscience (SfN), Chicago, United States, October 2015. [bibtex-key = lombaert:hal-01203574] [bibtex-entry]

Herve Lombaert, Antonio Criminisi, and Nicholas Ayache. Spectral Forests: Learning of Surface Data, Application to Cortical Parcellation. In Nassir Navab, Joachim Hornegger, William M. Wells, and Alejandro F. Frangi, editors, Medical Image Computingand Computer Assisted Intervention (MICCAI 2015), volume 9349 of Lecture Notes in Computer Science, Munich, Germany, pages 547-555, October 2015. Springer. [bibtex-key = lombaert:hal-01203568] [bibtex-entry]

Matthieu Lê, Hervé Delingette, Jayashree Kalpathy-Cramer, Elizabeth R Gerstner, Tracy Batchelor, Jan Unkelbach, and Nicholas Ayache. Bayesian Personalization of Brain Tumor Growth Model. In Alejandro F. Frangi, Joachim Hornegger, Nassir Navab, and William M. Wells, editors, MICCAI - Medical Image Computing and Computer Assisted Intervention - 2015, volume 9350 of Lecture Notes in Computer Science - LNCS, Munich, Germany, pages 424-432, October 2015. Springer. Keyword(s): Glioma Modeling, Bayesian, Personalization. [bibtex-key = le:hal-01155075] [bibtex-entry]

Matthieu Lê, Jan Unkelbach, Nicholas Ayache, and Hervé Delingette. GPSSI: Gaussian Process for Sampling Segmentations of Images. In Alejandro F. Frangi, Joachim Hornegger, Nassir Navab, and William M. Wells, editors, MICCAI - Medical Image Computing and Computer Assisted Intervention - 2015, volume 9351 of Lecture Notes in Computer Science - LNCS, Munich, Germany, pages 38-46, October 2015. Springer. Keyword(s): Sampling, Gaussian process, Radiotherapy, Segmentation. [bibtex-key = le:hal-01155078] [bibtex-entry]

Jessie Mahé, Nicolas Linard, Marzieh Kohandani Tafreshi, Tom Vercauteren, Nicholas Ayache, Francois Lacombe, and Remi Cuingnet. Motion-Aware Mosaicing for Confocal Laser Endomicroscopy. In Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2015, volume 9349, Munich, Germany, pages 447-454, October 2015. [bibtex-key = mahe:hal-01208437] [bibtex-entry]

Nerea Mangado, Mario Ceresa, Nicolas Duchateau, Hector Dejea, Hans Martin Kjer, Rasmus Paulsen, Sergio Vera, Pavel Mistrik, Javier Herrero, and Miguel Angel Gonzalez Ballester. Automatic generation of a computational model for monopolar stimulation of cochlear implants. In Computer Assisted Radiology and Surgery (CARS), volume 10 of International Journal of Computer Assisted Radiology and Surgery, Barcelona, Spain, pages S67-S68, 2015. [bibtex-key = mangado:hal-01213341] [bibtex-entry]

Nerea Mangado, Nicolas Duchateau, Mario Ceresa, Hans Martin Kjer, Sergio Vera, Pavel Mistrik, Javier Herrero, and Miguel Angel Gonzalez Ballester. Patient-specific virtual insertion of electrode array for electrical simulation of cochlear implants. In Computer Assisted Radiology and Surgery (CARS), volume 10 of International Journal of Computer Assisted Radiology and Surgery, Barcelona, Spain, pages S102-S103, 2015. [bibtex-key = mangado:hal-01213345] [bibtex-entry]

Kristin Mcleod, Maxime Sermesant, Philipp Beerbaum, and Xavier Pennec. Descriptive and Intuitive Population-Based Cardiac Motion Analysis via Sparsity Constrained Tensor Decomposition. In Medical Image Computing and Computer Assisted Intervention (MICCAI 2015), volume 9351 of Lecture notes in computer science (LNCS), Munich, Germany, pages 419-426, October 2015. [bibtex-key = mcleod:hal-01205535] [bibtex-entry]

Nina Miolane and Xavier Pennec. A survey of mathematical structures for extending 2D neurogeometry to 3D image processing. In MICCAI Workshop on Medical Computer Vision: Algorithms for Big Data. MCV 2015., volume 9601 of LNCS, Munich, Germany, pages 155-167, October 2015. Keyword(s): sub-Riemannian geometry, Image processing, neurogeometry. [bibtex-key = miolane:hal-01203518] [bibtex-entry]

Nina Miolane and Xavier Pennec. Biased estimators on Quotient spaces. In Geometric Science of Information. Second International Conference, GSI 2015., volume 9389 of Lecture notes in computer science (LNCS), Palaiseau, France, pages 130-139, October 2015. Springer. [bibtex-key = miolane:hal-01203805] [bibtex-entry]

Roch Molléro, Dominik Neumann, Marc-Michel Rohé, Manasi Datar, Herve Lombaert, Nicholas Ayache, Dorin Comaniciu, Olivier Ecabert, Marcello Chinali, Gabriele Rinelli, Xavier Pennec, Maxime Sermesant, and Tommaso Mansi. Propagation of Myocardial Fibre Architecture Uncertainty on Electromechanical Model Parameter Estimation: A Case Study. In Functional Imaging and Modeling of the Heart, LNCS., 8th International Conference, FIMH 2015, Maastricht, The Netherlands, June 25-27, 2015. Proceedings, Maastricht, Netherlands, pages 448-456, June 2015. [bibtex-key = mollero:hal-01241896] [bibtex-entry]

Xavier Pennec. Barycentric Subspaces Analysis on Spheres. In Mathematical Foundation sof Computational Anatomy (MFCA'15), Proceedings of the fifth international workshop on Mathematical Foundation sof Computational Anatomy (MFCA'15), Munich, Germany, pages 71-82, October 2015. [bibtex-key = pennec:hal-01203815] [bibtex-entry]

Xavier Pennec. Barycentric Subspaces and Affine Spans in Manifolds. In Geometric Science of Information GSI'2015, Second International Conference, volume 9389 of Lecture Notes in Compuer Science, Palaiseau, France, pages 12-21, October 2015. [bibtex-key = pennec:hal-01164463] [bibtex-entry]

Marc-Michel Rohé, Nicolas Duchateau, Maxime Sermesant, and Xavier Pennec. Combination of Polyaffine Transformations and Supervised Learning for the Automatic Diagnosis of LV Infarct. In Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges. STACOM 2015., volume 9534 of LNCS, Munich, Germany, pages 190-198, 2015. Springer. Keyword(s): Medical Imaging, Cardiac Motion, Machine Learning. [bibtex-key = rohe:hal-01206710] [bibtex-entry]

Sergio Sanchez-Martinez, Nicolas Duchateau, Bart Bijnens, Tamás Erdei, Alan Fraser, and Gemma Piella. Characterization of myocardial motion by multiple kernel learning: application to heart failure with preserved ejection fraction. In 8th International Conference, FIMH 2015, Maastricht, The Netherlands, June 25-27, 2015. Proceedings, volume 9126 of Functional Imaging and Modeling of the Heart, LNCS, Maastricht, Netherlands, pages 65-73, 2015. [bibtex-key = sanchezmartinez:hal-01208016] [bibtex-entry]

Sergio Sanchez-Martinez, Nicolas Duchateau, Tamás Erdei, Alan Fraser, Gemma Piella, and Bart Bijnens. Can machine learning help to identify heart failure with preserved ejection fraction?. In EuroEcho-Imaging, volume 16 of European Heart Journal: Cardiovascular Imaging, Abstracts from the EuroEcho-Imaging congress, Seville, Spain, pages ii38-9, 2015. [bibtex-key = sanchezmartinez:hal-01217975] [bibtex-entry]

Sergio Sanchez-Martinez, Nicolas Duchateau, Tamás Erdei, Alan Fraser, Gemma Piella, and Bart Bijnens. Quantifying the contribution of stress echocardiography to the diagnosis of heart failure with preserved ejection fraction. In EuroEcho-Imaging, volume 16 of European Heart Journal: Cardiovascular Imaging, Abstracts from the EuroEcho-Imaging congress, Seville, Spain, pages ii234, 2015. [bibtex-key = sanchezmartinez:hal-01217993] [bibtex-entry]

David Soto-Iglesias, Nicolas Duchateau, Constantine Butakoff, David Andreu, Juan Fernández-Armenta, Bart Bijnens, Antonio Berruezo, Marta Sitges, and Oscar Camara. Quantitative analysis of lead position vs. correction of electrical dyssynchrony in an experimental model of LBBB/CRT. In FIMH: Functional Imaging and Modeling of the Heart, volume LNCS of Functional Imaging and Modeling of the Heart, Maastricht, Netherlands, pages 74-82, June 2015. [bibtex-key = sotoiglesias:hal-01208006] [bibtex-entry]

Hugo Talbot, Stephane Cotin, Reza Razavi, Christopher Rinaldi, and Hervé Delingette. Personalization of Cardiac Electrophysiology Model using the Unscented Kalman Filtering. In Computer Assisted Radiology and Surgery (CARS 2015), Barcelona, Spain, June 2015. [bibtex-key = talbot:hal-01195719] [bibtex-entry]

Hugo Talbot, Nazim Haouchine, Igor Peterlik, Jeremie Dequidt, Christian Duriez, Hervé Delingette, and Stephane Cotin. Surgery Training, Planning and Guidance Using the SOFA Framework. In Eurographics, Zurich, Switzerland, May 2015. [bibtex-key = talbot:hal-01160297] [bibtex-entry]

Anant S. Vemuri, Stéphane Nicolau, Jacques Marescaux, Luc Soler, and Nicholas Ayache. Automatic View-Point Selection for Inter-Operative Endoscopic Surveillance. In Medical Content-based Retrieval for Clinical Decision Support, Munich, Germany, pages 1-8, October 2015. Tanveer Syeda-Mahmood and Hayit Greenspan and Anant Madabhushi. Keyword(s): Computer assisted intervention, Endoscopic Image classification, Endoluminal surgery, Barrett's Oesophagus. [bibtex-key = vemuri:hal-01203463] [bibtex-entry]

Martino Alessandrini, Brecht Heyde, Szymon Cygan, Maxime Sermesant, Hervé Delingette, Olivier Bernard, De Craene, and Jan d'Hooge. Elastic registration vs. block matching for quantification of cardiac function with 3D ultrasound: Initial results of a direct comparison in silico based on a new evaluation pipeline. In IEEE International Ultrasonics Symposium, Chicago, United States, pages 608 - 611, September 2014. [bibtex-key = alessandrini:hal-01095790] [bibtex-entry]

Chloé Audigier, Tommaso Mansi, Hervé Delingette, Saikiran Rapaka, Viorel Mihalef, Daniel Carnegie, Emad Boctor, Michael Choti, Ali Kamen, Dorin Comaniciu, and Nicholas Ayache. Parameter Estimation For Personalization of Liver Tumor Radiofrequency Ablation. In MICCAI Workshop on Abdominal Imaging -- Computational and Clinical Applications, Boston, United States, September 2014. [bibtex-key = audigier:hal-01067709] [bibtex-entry]

Rocio Cabrera Lozoya, Jan Margeta, Loic Le Folgoc, Yuki Komatsu, Berte Benjamin, Jatin Relan, Hubert Cochet, Michel Haïssaguerre, Pierre Jais, Nicholas Ayache, and Maxime Sermesant. Confidence-based Training for Clinical Data Uncertainty in Image-based Prediction of Cardiac Ablation Targets. In bigMCV Workshop MICCAI 2014, Boston, United States, September 2014. [bibtex-key = cabreralozoya:hal-01069085] [bibtex-entry]

Hugo Darmanté, Benoit Bugnas, Regis Bernard De Dompsure, Laurent Barresi, Nina Miolane, Xavier Pennec, Fernand de Peretti, and Nicolas Bronsard. Analyse biométrique de l'anneau pelvien en 3 dimensions - à propos de 100 scanners. In 89e Réunion annuelle de la SOFCOT, volume 100 of Revue de Chirurgie Orthopédique et Traumatologique, Paris, France, November 2014. [bibtex-key = darmante:hal-01094711] [bibtex-entry]

Sophie Giffard-Roisin, Stéphanie Marchesseau, Loic Le Folgoc, Hervé Delingette, and Maxime Sermesant. Evaluation of Personalised Canine Electromechanical Models. In O. Camara, T. Mansi, M. Pop, K. Rhode, M. Sermesant, and A. Young, editors, Proceedings of the 5th international STACOM workshop (Boston, September 18, 2014), number 8896 of 5th International Workshop, STACOM 2014, Held in Conjunction with MICCAI 2014, Boston, MA, USA, September 18, 2014, Revised Selected Papers, Boston, United States, pages 74-82, September 2014. Pop M., Springer. Keyword(s): Cardiac Modelling, Mechanical modeling, Modelling and Simulation, Personalised modelling, Personalized modeling, Cardiac electrical activity, Cardiac Modeling, Cardiac Electrophysiology modeling, Cardiac Electrophisiology, Modelisation cardiaque. [bibtex-key = giffardroisin:hal-01087841] [bibtex-entry]

Pietro Gori, Olivier Colliot, Linda Marrakchi-Kacem, Yulia Worbe, Fabrizio de Vico Fallani, Mario Chavez, Sophie Lecomte, Cyril Poupon, Andreas Hartmann, Nicholas Ayache, and Stanley Durrleman. A Prototype Representation to Approximate White Matter Bundles with Weighted Currents. In MICCAI 2014 - 17th International Conference on Medical Image Computing and Computer Assisted Intervention, Boston, United States, September 2014. [bibtex-key = gori:hal-01010702] [bibtex-entry]

Bishesh Khanal, Marco Lorenzi, Nicholas Ayache, and Xavier Pennec. A Biophysical Model of Shape Changes due to Atrophy in the Brain with Alzheimer's Disease. In P. GOLLAND, N. HATA, C. BARILLOT, J. HORNEGGER, and R. HOWE, editors, MICCAI 2014 - 17th International Conference Medical Image Computing and Computer-Assisted Intervention, volume 8674 of LNCS - Lecture Notes in Computer Science, Springer, Boston, United States, pages 41-48, September 2014. Springer. Keyword(s): Alzheimer's disease, Biophysical model, Atrophy model, Atrophy simulation, Longitudinal modeling. [bibtex-key = khanal:hal-01006478] [bibtex-entry]

Marzieh Kohandani Tafreshi, Virendra Joshi, Alexander Meining, Charles Lightdale, Marc Giovannini, Julien Dauguet, Nicholas Ayache, and Barbara André. Smart Atlas for Supporting the Interpretation of probe-based Confocal Laser Endomicroscopy (pCLE) of Biliary Strictures: First Classification Results of a Computer-Aided Diagnosis Software based on Image Recognition. In Digestive Disease Week (DDW 2014), Chicago, United States, May 2014. [bibtex-key = kohandanitafreshi:hal-01010765] [bibtex-entry]

Marzieh Kohandani Tafreshi, Yan-Qing Li, Rapat Pittayanon, Douglas Pleskow, Virendra Joshi, Philip Chiu, Julien Dauguet, Nicholas Ayache, and Barbara André. Smart Atlas for Supporting the Interpretation of probe-based Confocal Laser Endomicroscopy (pCLE) of Gastric Lesions: First Classification Results of a Computer-Aided Diagnosis Software based on Image Recognition. In Digestive Disease Week (DDW 2014), Chicago, United States, May 2014. [bibtex-key = kohandanitafreshi:hal-01010762] [bibtex-entry]

Marzieh Kohandani Tafreshi, Nicolas Linard, Barbara André, Nicholas Ayache, and Tom Vercauteren. Semi-automated Query Construction for Content-based Endomicroscopy Video Retrieval. In Medical Image Computing and Computer Assisted Intervention (MICCAI), Boston, United States, September 2014. Keyword(s): Microscopic imaging, Biological Imaging, Abdominal imaging, Optical imaging, Machine learning, Database retrieval and data mining, Computer vision, Minimally invasive procedure, Pathology, Intraoperative imaging, Endoscopic imaging. [bibtex-key = kohandanitafreshi:hal-01010673] [bibtex-entry]

Marzieh Kohandani Tafreshi, Bertrand Napoléon, Anne-Isabelle Lemaistre, Marc Giovannini, Virendra Joshi, Julien Dauguet, Nicholas Ayache, and Barbara André. Smart Atlas for Supporting the Interpretation of needle-based Confocal Laser Endomicroscopy (nCLE) of Pancreatic Cysts: First Classification Results of a Computer-Aided Diagnosis Software based on Image Recognition. In Digestive Disease Week (DDW 2014), Chicago, United States, May 2014. [bibtex-key = kohandanitafreshi:hal-01010701] [bibtex-entry]

Loic Le Folgoc, Hervé Delingette, Antonio Criminisi, and Nicholas Ayache. Sparse Bayesian Registration. In Polina Golland, Nobuhiko Hata, Christian Barillot, Joachim Hornegger, and Robert Howe, editors, MICCAI - 17th International Conference on Medical Image Computing and Computer Assisted Intervention, volume 8673 of LNCS - Lecture Notes in Computer Science, Springer, Boston, United States, pages 235-242, September 2014. Springer. Keyword(s): Sparse, Bayesian, Registration, Automatic Relevance Determination, MRI. [bibtex-key = lefolgoc:hal-01006605] [bibtex-entry]

Herve Lombaert, Darko Zikic, Antonio Criminisi, and Nicholas Ayache. Laplacian Forests: Semantic Image Segmentation by Guided Bagging. In Polina Golland, Nobuhiko Hata, Christian Barillot, Joachim Hornegger, and Robert Howe, editors, MICCAI 2014 - 17th International Conference Medical Image Computing and Computer-Assisted Intervention, volume 8674 of LNCS - Lecture Notes in Computer Science, Boston, United States, September 2014. Springer. [bibtex-key = lombaert:hal-01009672] [bibtex-entry]

Marco Lorenzi, Xavier Pennec, Nicholas Ayache, and (adni) For The Alzheimer'S Disease Neuroimaging Initiative. Regional flux analysis of longitudinal atrophy in Alzheimer's disease. In Alzheimer's Association International Conference, Copenhagen, Denmark, July 2014. Note: Oral podium presentation. [bibtex-key = lorenzi:hal-01015978] [bibtex-entry]

Matthieu Lê, Hervé Delingette, Jayashree Kalpathy-Cramer, Elisabeth Gerstner, Helen A. Shih, Tracy Batchelor, Jan Unkelbach, and Nicholas Ayache. Multimodal Analysis of Vasogenic Edema in Glioblastoma Patients for Radiotherapy Planning. In Workshop Image-Guided Adaptive Radiation Therapy, Boston, United States, September 2014. [bibtex-key = le:hal-01093397] [bibtex-entry]

Jan Margeta, Antonio Criminisi, Daniel C. Lee, and Nicholas Ayache. Recognizing cardiac magnetic resonance acquisition planes. In MIUA - Medical Image Understanding and Analysis Conference - 2014, London, United Kingdom, July 2014. Reyes-Aldasoro, Constantino Carlos and Slabaugh, Gregory. Keyword(s): random forests, cardiac MR. [bibtex-key = margeta:hal-01009952] [bibtex-entry]

Nina Miolane and Xavier Pennec. Statistics on Lie groups : a need to go beyond the pseudo-Riemannian framework. In Bayesian inference and Maximum Entropy Methods in Science and Engineering (MaxEnt 2014), volume 1641 of AIP Conference Proceedings, Amboise, France, pages 59-66, September 2014. AIP Proceedings. Keyword(s): manifold, metric, exponential barycenter, Lie group, computational anatomy, Statistics, pseudo-Riemannian. [bibtex-key = miolane:hal-01091515] [bibtex-entry]

H Talbot, F Spadoni, Christian Duriez, M Sermesant, Stéphane Cotin, and Hervé Delingette. Interactive Training System for Interventional Electrocardiology Procedures. In 6th International Symposium on Biomedical Simulation - ISBMS 2014, Strabsourg, France, pages 11 - 19, October 2014. Keyword(s): Electrophysiology, Radio-Frequency Ablation, Arrhythmia, Training System. [bibtex-key = talbot:hal-01078209] [bibtex-entry]

Anant S. Vemuri, Adrien Sportes, Stéphane Nicolau, Jacques Marescaux, Nicholas Ayache, and Luc Soler. Video Synchronization: An Approach to Biopsy Site Re-localization. In Proceedings of Surgetica'2014 : Computer-Assisted Medical Interventions: scientific problems, tools and clinical applications, Chambéry, France, December 2014. Jocelyne TROCCAZ. Keyword(s): Inter operative Relocalization, Endoluminal surgery, Endoscopy. [bibtex-key = vemuri:hal-01089196] [bibtex-entry]

Mathieu de Craene, Martino Alessandrini, Pascal Allain, Stephanie Marchesseau, I Waechter-Stehle, J Weese, E Saloux, H. G. Morales, R Cuingnet, Hervé Delingette, M Sermesant, Olivier Bernard, and J D 'Hooge. Generation of ultra-realistic synthetic echocardiographic sequences. In Biomedical Imaging (ISBI), 2014 IEEE 11th International Symposium on, Beijing, China, pages 73 - 76, April 2014. IEEE. Keyword(s): Ultra-sound imaging, Motion detection and tracking, Modeling of image formation. [bibtex-key = decraene:hal-01095133] [bibtex-entry]

Chloé Audigier, Tommaso Mansi, Hervé Delingette, Saikiran Rapaka, Viorel Mihalef, Puneet Sharma, Ali Kamen, Daniel Carnegie, Emad Boctor, Michael Choti, Dorin Comaniciu, and Nicholas Ayache. Lattice Boltzmann Method For Fast Patient-Specific Simulation of Liver Tumor Ablation from CT Images. In Kensaku Mori, Ichiro Sakuma, Yoshinobu Sato, Christian Barillot, and Nassir Navab, editors, MICCAI - Medical Image Computing and Computer Assisted Intervention - 2013, volume 8151 of Lecture Notes in Computer Science - LNCS, Nagoya, Japan, pages 323-330, September 2013. Springer. [bibtex-key = audigier:hal-00804147] [bibtex-entry]

Thomas Benseghir, Grégoire Malandain, and Régis Vaillant. Iterative Closest Curve: a Framework for Curvilinear Structure Registration Application to 2D/3D Coronary Arteries Registration. In Mori, Kensaku, Sakuma, Ichiro, Sato, Yoshinobu, Barillot, Christian, Navab, and Nassir, editors, MICCAI - Medical Image Computing and Computer Assisted Intervention, volume 8149 of Lecture Notes in Computer Science, Nagoya, Japan, pages 179-186, September 2013. Springer. Keyword(s): registration, curvilinear structure, ICP, chronic total occlusion, CTO, coronary, X-ray, computed tomography angiography, CTA. [bibtex-key = benseghir:hal-00833196] [bibtex-entry]

Marine Breuilly, Grégoire Malandain, Nicholas Ayache, Julien Guglielmi, Thierry Pourcher, Philippe R. Franken, and Jacques Darcourt. Image-based motion detection in 4D images and application to respiratory motion suppression. In ISBI - International Symposium on Biomedical Imaging, Proceedings of the 2013 IEEE 10th International Symposium on Biomedical Imaging: From Nano to Macro, San Francisco, United States, pages 792-795, April 2013. IEEE. [bibtex-key = breuilly:hal-00799368] [bibtex-entry]

Nicolas Cordier, Bjoern Menze, Hervé Delingette, and Nicholas Ayache. Patch-based Segmentation of Brain Tissues. In Bjoern Menze, Mauricio Reyes, Andras Jakab, Elisabeth Gerstner, Justin Kirby, and Keyvan Farahani, editors, MICCAI Challenge on Multimodal Brain Tumor Segmentation, Proceedings of the MICCAI Challenge on Multimodal Brain Tumor Image Segmentation (BRATS) 2013, Nagoya, Japan, pages 6 - 17, September 2013. IEEE. [bibtex-key = cordier:hal-00917084] [bibtex-entry]

Florian Dittmann, Bjoern Menze, Ender Konukoglu, and Jan Unkelbach. Use of Diffusion Tensor Images in Glioma Growth Modeling for Radiotherapy Target Delineation. In Multimodal Brain Image Analysis, volume 8159 of Lecture Notes in Computer Scienc, Nagoya, Japan, pages 63-73, September 2013. [bibtex-key = dittmann:hal-00912667] [bibtex-entry]

Ezequiel Geremia, Bjoern H. Menze, and Nicholas Ayache. Spatially Adaptive Random Forest. In 2013 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, San Francisco, CA, United States, pages 1332-35, 2013. IEEE. [bibtex-key = geremia:hal-00840035] [bibtex-entry]

Pietro Gori, Olivier Colliot, Yulia Worbe, Linda Marrakchi-Kacem, Sophie Lecomte, Cyril Poupon, Andreas Hartmann, Nicholas Ayache, and Stanley Durrleman. Bayesian Atlas Estimation for the Variability Analysis of Shape Complexes. In MICCAI 2013 : Medical Image Computing and Computer Assisted Intervention, Nagoya, Japan, pages 267-274, September 2013. [bibtex-key = gori:hal-01188791] [bibtex-entry]

Pietro Gori, Olivier Colliot, Yulia Worbe, Linda Marrakchi-Kacem, Sophie Lecomte, Cyril Poupon, Andreas Hartmann, Nicholas Ayache, and Stanley Durrleman. Towards joint morphometry of white matter tracts and gray matter surfaces. In Human Brain Mapping, Seattle, United States, 2013. Note: Organization for Human Brain Mapping 2013. [bibtex-key = gori:hal-00816138] [bibtex-entry]

Vikash Gupta, Nicholas Ayache, and Xavier Pennec. Improving DTI Resolution from a Single Clinical Acquisition: A Statistical Approach using Spatial Prior. In Kensaku Mori, Ichiro Sakuma, Yoshinobu Sato, Christian Barillot, and Nassir Navab, editors, Proceedings of Medical Image Computing and Computer Assisted Intervention 2013 (MICCAI), volume 8151 of Lecture Notes in Computer Science - LNCS, Nagoya, Japan, pages 477-484, September 2013. Springer. Keyword(s): DTI, Super-resolution, Partial volume effect, Diffusion Tensor Imaging, Clinical Medical Imaging. [bibtex-key = gupta:hal-00845927] [bibtex-entry]

Marco Lorenzi, Martina Bochetta, Nicholas Ayache, Xavier Pennec, and Giovanni B. Frisoni. Conversion to MCI in healthy individuals with abnormal CSF Ab42 levels is associated with specific longitudinal morphological changes. In Alzheimer's Association International Conference 2013, volume 9, issue 4 (supplement) of Alzheimer's & Dementia: The Journal of the Alzheimer's Association, Boston, United States, pages P596, July 2013. [bibtex-key = lorenzi:hal-00874722] [bibtex-entry]

Marco Lorenzi, Bjoern H. Menze, Marc Niethammer, Nicholas Ayache, and Xavier Pennec. Sparse Scale-Space Decomposition of Volume Changes in Deformations Fields. In Kensaku Mori, Ichiro Sakuma, Yoshinobu Sato, Christian Barillot, and Nassir Navab, editors, Medical Image Computing and Computer Aided Intervention (MICCAI), volume 8150 of Lecture Notes in Computer Science - LNCS, Nagoya, Japan, pages 328-335, September 2013. Springer. Keyword(s): Scale-space decomposition, non-rigid registration, longitudinal analysis, stationary velocity fields. [bibtex-key = lorenzi:hal-00845758] [bibtex-entry]

Marco Lorenzi and Xavier Pennec. Parallel Transport with Pole Ladder: Application to Deformations of time Series of Images. In Nielsen, Frank, Barbaresco, and F., editors, GSI2013 - Geometric Science of Information, volume 8085 of Lecture Notes in Computer Science - LNCS, Paris, France, pages 68-75, August 2013. Springer. [bibtex-key = lorenzi:hal-00819898] [bibtex-entry]

Jan Margeta, Kristin Mcleod, Antonio Criminisi, and Nicholas Ayache. Decision forests for segmentation of left atrium from 3D MRI. In 4th International Workshop on Statistical Atlases and Computational Models of the Heart, Nagoya, Japan, September 2013. [bibtex-key = margeta:hal-00860580] [bibtex-entry]

Kristin Mcleod, Christof Seiler, Maxime Sermesant, and Xavier Pennec. Spatio-Temporal Dimension Reduction of Cardiac Motion for Group-Wise Analysis and Statistical Testing. In Kensaku Mori, Ichiro Sakuma, Yoshinobu Sato, Christian Barillot, and Nassir Navab, editors, MICCAI - Medical Image Computing and Computer Assisted Intervention - 2013, volume 8150 of Lecture Notes in Computer Science, Nagoya, Japan, pages 501-508, 2013. Springer, Heidelberg. [bibtex-key = mcleod:hal-00840041] [bibtex-entry]

Kristin Mcleod, Christof Seiler, Nicolas Toussaint, Maxime Sermesant, and Xavier Pennec. Regional Analysis of Left Ventricle Function using a Cardiac-Specific Polyaffine Motion Model. In Sébastien Ourselin, Daniel Rueckert, and Nicolas Smith, editors, Functional Imaging and Modeling of the Heart 2013 (FIMH), volume 7945 of Lecture Notes in Computer Science, London, United Kingdom, pages 483-490, June 2013. Springer. [bibtex-key = mcleod:hal-00840042] [bibtex-entry]

Mariem Mhiri, Vineeth Varma, Maël Le, Samson Lasaulce, and Abdelaziz Samet. On the benefits of repeated game models for green cross-layer power control in small cells. In BlackSeaCom 2013, Batumi, Georgia, July 2013. Keyword(s): channel state information, repeated game, energy efficiency, Index Terms-distributed power control, channel state information. [bibtex-key = mhiri:hal-01104410] [bibtex-entry]

Xavier Pennec. Bi-invariant means on Lie groups with Cartan-Schouten connections. In Nielsen, Frank, Barbaresco, and F., editors, Geometric Science of Information (GSI 2013), volume 8085 of Lecture Notes in Computer Science - LNCS, Paris, France, pages 59-67, August 2013. Springer. [bibtex-key = pennec:hal-00846373] [bibtex-entry]

Christof Seiler, Xavier Pennec, and Susan Holmes. Random Spatial Structure of Geometric Deformations and Bayesian Nonparametrics. In GSI - Geometric Science of Information - 2013, volume 8085 of Lecture Notes in Computer Science - LNCS, Paris, France, pages 120-127, August 2013. Springer. [bibtex-key = seiler:hal-00847185] [bibtex-entry]

Oudom Somphone, Mathieu de Craene, Roberto Ardon, Benoit Mory, Pascal Allain, Hang Gao, Jan d'Hooge, Stéphanie Marchesseau, Maxime Sermesant, and Eric Saloux. Fast Myocardial Motion and Strain Estimation in 3D Cardiac Ultrasound with Sparse Demons. In International Symposium on Biomedical Imaging (ISBI), 2013, San Francisco, United States, pages 1182-1185, April 2013. IEEE. [bibtex-key = somphone:hal-00840038] [bibtex-entry]

Erin Stretton, Ezequiel Geremia, Bjoern H. Menze, Hervé Delingette, and Nicholas Ayache. Importance of patient DTI's to accurately model glioma growth using the reaction diffusion equation. In 2013 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, San Francisco, CA, United States, pages 1130-32, 2013. IEEE. [bibtex-key = stretton:hal-00840036] [bibtex-entry]

Yuliya Tarabalka, Guillaume Charpiat, Ludovic Brucker, and Bjoern H. Menze. Enforcing Monotonous Shape Growth or Shrinkage in Video Segmentation. In BMVC - British Machine Vision Conference, Bristol, United Kingdom, September 2013. [bibtex-key = tarabalka:hal-00856634] [bibtex-entry]

Birkan Tunç, Alex Smith, Demian Wasserman, Xavier Pennec, William M. Wells, Ragini Verma, and Kilian M. Pohl. Multinomial Probabilistic Fiber Representation for Connectivity Driven Clustering. In Gee, J. C., Joshi, Sarang, Pohl, Kilian M., Wells, William M., Zollei, and L., editors, IPMI 2013 - Information Processing in Medical Imaging, volume 7917 of LNCS, Asilomar, United States, pages 730-741, June 2013. Springer. [bibtex-key = tunc:hal-00846431] [bibtex-entry]

Anant S. Vemuri, Stéphane Nicolau, Nicholas Ayache, Jacques Marescaux, and Luc Soler. Inter-Operative Trajectory Registration for Endoluminal Video Synchronization: Application to Biopsy Site Re-localization. In International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), volume 8149 of Medical Image Computing and Computer-Assisted Intervention - MICCAI 2013, Nagoya, Japan, pages 372-379, September 2013. Springer. Keyword(s): Computer assisted surgery, Surgical Navigation, Biopsy relocalization. [bibtex-key = vemuri:hal-00841712] [bibtex-entry]

H. Bou-Sleiman, Christof Seiler, T. Iizuka, L. Nolte, and Mauricio Reyes. Population-Based Design of Mandibular Plates Based on Bone Quality and Morphology. In Proceedings of Medical Image Computing and Computer Assisted Intervention 2012 (MICCAI), volume 7510 of LNCS, pages 66-73, October 2012. Springer, Heidelberg. [bibtex-key = BouSleimanSeiler:MICCAI:12] [bibtex-entry]

Mathieu De Craene, Pascal Allain, Hang Gao, Adityo Prakosa, Stéphanie Marchesseau, Loic Hilpert, Oudom Somphone, Hervé Delingette, Sherif Makram-Ebeid, Nicolas Villain, Jan D'hooge, Maxime Sermesant, and Eric Saloux. Synthetic and Phantom Setups for the Second cardiac Motion Analysis Challenge (cMAC2). In Proc. MICCAI Workshop on Statistical Atlases and Computational Models of the Heart: Imaging and Modelling Challenge (STACOM12), LNCS, 2012. Springer. [bibtex-key = DeCraene:cMAC2] [bibtex-entry]

Nicolas Duchateau, Mathieu De Craene, Xavier Pennec, Beatriz Merino, Marta Sitges, and Bart Bijnens. Which Reorientation Framework for the Atlas-Based Comparison of Motion from Cardiac Image Sequences?. In Proc. of STIA 2012 (Spatio-=Temporal Image Analysis for Longitudinal and Time-Series Image Data, volume 7570 of LNCS, pages 25-37, October 2012. Springer, Heidelberg. [bibtex-key = Duchateau:STIA:12] [bibtex-entry]

Ezequiel Geremia, Bjoern H. Menze, and Nicholas Ayache. Spatial Decision Forests for Glioma Segmentation in Multi-Channel MR Images. In MICCAI Challenge on Multimodal Brain Tumor Segmentation, LNCS, October 2012. Springer. [bibtex-key = Geremia:BRATS:12] [bibtex-entry]

Ezequiel Geremia, Bjoern H. Menze, Marcel Prastawa, Marc-André Weber, Antonio Criminisi, and Nicholas Ayache. Brain tumor cell density estimation from multi-modal MR images based on a synthetic tumor growth model. In MICCAI Workshop on Medical Computer Vision, LNCS, October 2012. Springer. [bibtex-key = Geremia:MCV:12] [bibtex-entry]

Loic Le Folgoc, Hervé Delingette, Antonio Criminisi, and Nicholas Ayache. Current-based 4D shape analysis for the mechanical personalization of heart models. In Proceedings of MCV Workshop at MICCAI 2012, LNCS, October 2012. Springer. [bibtex-key = Le_Folgoc:MCV:12] [bibtex-entry]

Hervé Lombaert, Leo Grady, Xavier Pennec, Nicholas Ayache, and Farida Cheriet. Spectral Demons - Image Registration via Global Spectral Correspondence. In Proc. of ECCV (2), number 7573 of LNCS, pages 30-44, 2012. [bibtex-key = Lombaert:ECCV:12] [bibtex-entry]

Hervé Lombaert, Leo Grady, Xavier Pennec, Jean-Marc Peyrat, Nicholas Ayache, and Farida Cheriet. Groupwise Spectral Log-Demons Framework for Atlas Construction. In Medical Computer Vision (MCV'12) MICCAI workshop, 2012. Note: Best paper award. [bibtex-key = Lombaert:MCV:12] [bibtex-entry]

Marco Lorenzi, Nicholas Ayache, and Xavier Pennec. Disentangling the normal aging from the pathological Alzheimer's disease progression on cross-sectional structural MR images. In MICCAI workshop on Novel Imaging Biomarkers for Alzheimer's Disease and Related Disorders (NIBAD'12), pages 145-154, October 2012. ISBN: 9781479261994. [bibtex-key = Lorenzi:NIBAD:12] [bibtex-entry]

Marco Lorenzi, Nicholas Ayache, and Xavier Pennec. Regional flux analysis of longitudinal atrophy in Alzheimer's disease. In Proceedings of Medical Image Computing and Computer Assisted Intervention 2012 (MICCAI), volume 7510 of LNCS, pages 739-746, October 2012. Springer, Heidelberg. ISBN: 978-3-642-33414-6. [bibtex-key = Lorenzi:MICCAI:12] [bibtex-entry]

Marco Lorenzi, Giovanni B. Frisoni, Nicholas Ayache, and Xavier Pennec. Probabilistic Flux Analysis of Cerebral Longitudinal Atrophy. In MICCAI workshop on Novel Imaging Biomarkers for Alzheimer's Disease and Related Disorders (NIBAD'12), pages 256-265, October 2012. ISBN: 9781479261994. [bibtex-key = Lorenzi:NIBAD-ch:12] [bibtex-entry]

Stéphanie Marchesseau, Hervé Delingette, Maxime Sermesant, Kawal Rhode, S.G. Duckett, C. Aldo Rinaldi, Reza Razavi, and Nicholas Ayache. Cardiac Mechanical Parameter Calibration based on the Unscented Transform. In Proceedings of Medical Image Computing and Computer Assisted Intervention 2012 (MICCAI), volume 7511 of LNCS, October 2012. Springer, Heidelberg. [bibtex-key = Marchesseau:MICCAI:2012] [bibtex-entry]

Kristin McLeod, Adityo Prakosa, Tommaso Mansi, Maxime Sermesant, and Xavier Pennec. An Incompressible Log-Domain Demons Algorithm for Tracking Heart Tissue. In Proc. MICCAI Workshop on Statistical Atlases and Computational Models of the Heart: Mapping Structure and Function (STACOM11), number 7085 of LNCS, Toronto, pages 55-67, September 2012. Springer. [bibtex-key = McLeod:STACOM:2011] [bibtex-entry]

Kristin McLeod, Christof Seiler, Maxime Sermesant, and Xavier Pennec. A Near-Incompressible Poly-Affine Motion Model for Cardiac Function Analysis. In Proc. MICCAI Workshop on Statistical Atlases and Computational Models of the Heart: Mapping Structure and Function + a Cardiac Electrophysiological Simulation Challenge (STACOM+CESC'12), LNCS, Nice, October 2012. Springer. [bibtex-key = MCLEOD:STACOM:2012] [bibtex-entry]

Adityo Prakosa, Kristin McLeod, Maxime Sermesant, and Xavier Pennec. Evaluation of iLogDemons Algorithm for Cardiac Motion Tracking in Synthetic Ultrasound Sequence. In Proc. MICCAI Workshop on Statistical Atlases and Computational Models of the Heart: Imaging and Modelling Challenge (STACOM12), LNCS, October 2012. Springer. [bibtex-key = Prakosa:STACOM:12] [bibtex-entry]

Nicolas Savoire, Barbara André, and Tom Vercauteren. Online Blind Calibration of Non-Uniform Photodetectors: Application to Endomicroscopy. In Proceedings of Medical Image Computing and Computer Assisted Intervention 2012 (MICCAI), LNCS, October 2012. Springer, Heidelberg. Note: To appear. [bibtex-key = Andre:MICCAI:12] [bibtex-entry]

Christof Seiler, Xavier Pennec, and Mauricio Reyes. Simultaneous Multiscale Polyaffine Registration by Incorporating Deformation Statistics. In Proceedings of Medical Image Computing and Computer Assisted Intervention 2012 (MICCAI), volume 7511 of LNCS, pages 130-137, October 2012. Springer, Heidelberg. ISBN: 978-3-642-33417-7. [bibtex-key = Seiler:MICCAI:12] [bibtex-entry]

Stefan Sommer, Mads Nielsen, and Xavier Pennec. Sparsity and Scale: Compact Representations of Deformation for Diffeomorphic Registration. In IEEE Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA 2012), Breckenridge, Colorado, USA, January 2012.

Abstract:

In order to detect small-scale deformations during disease propagation while allowing large-scale deformation needed for inter-subject registration, we wish to model deformation at multiple scales and represent the deformation at the relevant scales only. With the LDDMM registration framework, enforcing sparsity results in compact representations but with limited ability to represent deformation across scales. In contrast, the LDDKBM extension of LDDMM allows representations of deformation at multiple scales but it does not favour compactness and hence may represent deformation at more scales than necessary. In this paper, we combine a sparsity prior with the multi-scale framework resulting in an algorithm allowing compact representation of deformation across scales. We present a mathematical formulation of the algorithm and evaluate it on a dataset of annotated lung CT images.

[bibtex-key = Sommer:MMBIA:2012] [bibtex-entry]

Erin Stretton, Emmanuel Mandonnet, Ezequiel Geremia, Bjoern H. Menze, Hervé Delingette, and Nicholas Ayache. Predicting the Location of Glioma Recurrence After a Resection Surgery. In Proceedings of 2nd International MICCAI Workshop on Spatiotemporal Image Analysis for Longitudinal and Time-Series Image Data (STIA'12), LNCS, Nice, October 2012. Springer. [bibtex-key = Stretton:STIA:2012] [bibtex-entry]

Hugo Talbot, Christian Duriez, Hadrien Courtecuisse, Jatin Relan, Maxime Sermesant, Stéphane Cotin, and Hervé Delingette. Towards Real-Time Computation of Cardiac Electrophysiology for Training Simulator. In Statistical Atlases and Computational Models of the Heart - STACOM 2012 in the 15th International Conference on Medical Image Computing and Computer Assisted Intervention - MICCAI 2012, Lecture Notes in Computer Science, Nice, France, October 2012. Springer. [bibtex-key = talbot:hal-00750835] [bibtex-entry]

Hugo Talbot, Stéphanie Marchesseau, Christian Duriez, Hadrien Courtecuisse, Jatin Relan, Maxime Sermesant, Stéphane Cotin, and Hervé Delingette. Interactive Electromechanical Model of the Heart for Patient-Specific Therapy Planning and Training using SOFA. In Virtual Human Project (VPH), 2012. [bibtex-key = Talbot:VPH2012] [bibtex-entry]

J. Unkelbach, Bjoern H. Menze, A. Motamedi, F. Dittmann, Ender Konukoglu, Nicholas Ayache, and H. Shih. Glioblastoma growth modeling for radiotherapy target delineation.. In Proc MICCAI Workshop on Image-Guidance and Multimodal Dose Planning in Radiation Therap., pages 12 pages, 2012. [bibtex-key = unkelbach_12_glioblastoma] [bibtex-entry]

Ken C. L. Wong, Jatin Relan, Linwei Wang, Maxime Sermesant, Hervé Delingette, Nicholas Ayache, and Pengcheng Shi. Strain-Based Regional Nonlinear Cardiac Material Properties Estimation From Medical Images. In Proceedings of Medical Image Computing and Computer Assisted Intervention 2012 (MICCAI), LNCS, October 2012. Springer, Heidelberg. Note: To appear. [bibtex-key = Ken:MICCAI:12] [bibtex-entry]

Barbara André, Tom Vercauteren, and Nicholas Ayache. Content-Based Retrieval in Endomicroscopy: Toward an Efficient Smart Atlas for Clinical Diagnosis. In Proceedings of the MICCAI Workshop - Medical Content-based Retrieval for Clinical Decision (MCBR-CDS'11), LNCS, 2011. Springer. [bibtex-key = Andre:MCBRCDS:11] [bibtex-entry]

Barbara André, Tom Vercauteren, Anna M. Buchner, Michael B. Wallace, and Nicholas Ayache. Retrieval evaluation and distance learning from perceived similarity between endomicroscopy videos. In Proceedings of Medical Image Computing and Computer Assisted Intervention (MICCAI), LNCS, pages 8p, 2011. Springer, Heidelberg. [bibtex-key = Andre:MICCAI:11] [bibtex-entry]

S. Bonaretti, Christof Seiler, C. Boichon, P. Bchler, and Mauricio Reyes. Mesh-based vs. Image-based Statistical Model of Appearance of the Human Femur: A Preliminary Comparison Study for the Creation of Finite Element Meshes. In Mesh Processing in Medical Image Analysis Workshop MICCAI, 2011. [bibtex-key = BonarettiSeiler:WorkshopMICCAI:11] [bibtex-entry]

H. Cochet, A. S. Jadidi, O. Corneloup, M. Lederlin, J. Relan, M. Montaudon, M. Sermesant, P. Jaïs, and F. Laurent. Myocardial Scar Modeling from Delayed Enhancement MRI: Usefulness for the Guidance of Ventricular Tachycardia Mapping and Ablation. In Radiological Society of North America, RSNA'11, November 2011. [bibtex-key = Hubert:RSNA:11] [bibtex-entry]

H. Cochet, A. S. Jadidi, F. Sacher, N. Derval, M. Sermesant, J. Relan, S. J. Kim, P. Bordachar, P. Ritter, M. Hocini, M. Montaudon, F. Laurent, N. Ayache, M. Haïssaguerre, and P. Jais. Ventricular Scar At Cardiac CT Correlates To Critical Isthmuses Of Ventricular Tachycardia Circuits And Sites Of Slow Conduction During Sinus Rhythm - Evidence For Clinical Use Of CT Integration Into 3D Mapping Systems. In Heart Rhythm Society '11, May 2011. [bibtex-key = Hubert:HeartRhythm:11] [bibtex-entry]

B. Gibaud, F. Ahmad, C. Barillot, F. Michel, B. Wali, B. Batrancourt, M. Dojat, P. Girard, A. Gaignard, D. Lingrand, J. Montagnat, J. Rojas Balderrama, G. Malandain, X. Pennec, D. Godard, G. Kassel, and M. Pélégrini-Issac. A federated system for sharing and reuse of images and image processing tools in neuroimaging. In Proc. of Computer Assisted Radiology and Surgery 2011 (CARS 2011), June 2011. [bibtex-key = Gibaud:CARS:11] [bibtex-entry]

A. S. Jadidi, H. Cochet, F. Sacher, S. J. Kim, M. Sermesant, J. Relan, N. Derval, S. Miyazaki, A. Shah, D. Scherr, S. B. Wilton, P. Pascale, L. Roten, M. Pederson, S. Knecht, P. Bordachar, P. Ritter, M. Hocini, M. Montaudon, F. Laurent, N. Ayache, M. Haïssaguerre, and P. Jaïs. Ventricular Scar imaging at MRI Correlates to Critical Isthmuses of Ventricular Tachycardia Circuits and Sites of Slow Conduction during Sinus Rhythm - Utility of integrating MR-data into 3D Mapping Systems. In Heart Rhythm Society '11, May 2011. [bibtex-key = Amir:HeartRhythm:11] [bibtex-entry]

Herve Lombaert, Jean-Marc Peyrat, Pierre Croisille, Stanislas Rapacchi, Laurent Fanton, Patrick Clarysse, Hervé Delingette, and Nicholas Ayache. Statistical Analysis of the Human Cardiac Fiber Architecture from DT-MRI. In Leon Axel and Dimitris Metaxas, editors, Proceedings of FIMH Conference 2011, volume 6666 of LNCS, pages 171-179, May 2011. Springer. Note: Best Paper Award. [bibtex-key = Lombaert:FIMH:11] [bibtex-entry]

Herve Lombaert, Jean-Marc Peyrat, Laurent Fanton, Farida Cheriet, Hervé Delingette, Nicholas Ayache, Patrick Clarysse, Isabelle Magnin, and Pierre Croisille. Statistical Atlas of Human Cardiac Fibers: Comparison with Abnormal Hearts. In Proceedings of STACOM Workshop at MICCAI 2011, September 2011. Springer. [bibtex-key = Lombaert:STACOM:11a] [bibtex-entry]

Herve Lombaert, Jean-Marc Peyrat, Laurent Fanton, Farida Cheriet, Hervé Delingette, Nicholas Ayache, Patrick Clarysse, Isabelle Magnin, and Pierre Croisille. Variability of the Human Cardiac Laminar Structure. In Proceedings of STACOM Workshop at MICCAI 2011, September 2011. Springer. [bibtex-key = Lombaert:STACOM:11b] [bibtex-entry]

Herve Lombaert, Jean-Marc Peyrat, Stanislas Rapacchi, Laurent Fanton, Herve Delingette, Nicholas Ayache, and Pierre Croisille. Human Statistical Atlas of Cardiac Fiber Architecture from DT-MRI. In Proceedings of Intl. Soc. Mag. Reson. Med. (ISMRM) 2011, volume 19, pages 280, May 2011. [bibtex-key = Lombaert:ISMRM:11] [bibtex-entry]

Marco Lorenzi, Nicholas Ayache, Giovanni B. Frisoni, and Xavier Pennec. Mapping the effects of A$\beta_{1-42}$ levels on the longitudinal changes in healthy aging: hierarchical modeling based on stationary velocity fields. In Proceedings of Medical Image Computing and Computer Assisted Intervention (MICCAI), volume 6892 of LNCS, pages 663-670, 2011. Springer. [bibtex-key = Lorenzi:MICCAI:11] [bibtex-entry]

Marco Lorenzi, Nicholas Ayache, and Xavier Pennec. Schilds Ladder for the parallel transport of deformations in time series of images. In G. Szekely and H. Hahn, editors, Proceedings of Information Processing in Medical Imaging (IPMI'11), volume 6801 of LNCS, pages 463-474, 2011. Note: Honorable Mention (runner-up) for the Erbsmann Award. [bibtex-key = Lorenzi:IPMI:11] [bibtex-entry]

Marco Lorenzi and Xavier Pennec. Geodesics, parallel transport & one-parameter subgroups. In 3rd MICCAI workshop on Mathematical Foundations of Computational Anatomy Workshop, September 2011. [bibtex-key = Lorenzi:MFCA:11] [bibtex-entry]

Marco Lorenzi, Xavier Pennec, and Giovanni B. Frisoni. Monitoring the brain's longitudinal changes in clinical trials for Alzheimers disease: a robust and reliable non-rigid registration framework. In Alzheimer's Association 2011 International Conference on Alzheimer's Disease (AAICAD), 2011. [bibtex-key = Lorenzi:AAICAD:11] [bibtex-entry]

Jan Margeta, Ezequiel Geremia, Antonio Criminisi, and Nicholas Ayache. Layered Spatio-temporal Forests for Left Ventricle Segmentation from 4D Cardiac MRI Data. In Proceedings of STACOM Workshop at MICCAI 2011, September 2011. Springer. [bibtex-key = Margeta:STACOM:11] [bibtex-entry]

Bjoern H. Menze, Koen Van Leemput, Antti Honkela, Ender Konukoglu, Marc-Andre Weber, Nicholas Ayache, and Polina Golland. A Generative Approach for Image-Based Modeling of Tumor Growth. In G. Szekely and H. Hahn, editors, Proceedings of Information Processing in Medical Imaging (IPMI'11), LNCS 6801, pages 13p, 2011. [bibtex-key = Menze:IPMI:11] [bibtex-entry]

Xavier Pennec and Marco Lorenzi. Which parallel transport for the statistical analysis of longitudinal deformations?. In Colloque GRETSI '11, September 2011. [bibtex-key = Pennec:GRETSI:11] [bibtex-entry]

Mihaela Pop, Maxime Sermesant, Jean-Marc Peyrat, Eugene Crystal, Sudip Ghate, Tommaso Mansi, Ilan Lashevsky, Beiping Qiang, Elliot R. McVeigh, Nicholas Ayache, and Graham A. Wright. A 3D MRI-Based Cardiac Computer Model to Study Arrhythmia and Its In-vivo Experimental Validation. In FIMH, pages 195-205, 2011. [bibtex-key = Pop:FIMH:2011] [bibtex-entry]

Adityo Prakosa, Maxime Sermesant, Hervé Delingette, Eric Saloux, Pascal Allain, Pascal Cathier, Patrick Etyngier, Nicolas Villain, and Nicholas Ayache. Synthetic Echocardiographic Image Sequences for Cardiac Inverse Electro-Kinematic Learning. In Proceedings of Medical Image Computing and Computer Assisted Intervention (MICCAI), LNCS, Toronto, Canada, pages 8p, September 2011. Springer, Heidelberg. [bibtex-key = prakosa:MICCAI:2011] [bibtex-entry]

J. Relan, M. Sermesant, H. Delingette, and N. Ayache. Personalisation of a 3D Ventricular Electrophysiological Model, Using Endocardial and Epicardial Contact Mapping and MRI. In Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges - Second International Workshop, STACOM 2011, Held in Conjunction with MICCAI 2011, pages 14-22, 2011. [bibtex-key = Relan:STACOM:11] [bibtex-entry]

Christof Seiler, Xavier Pennec, and Mauricio Reyes. Geometry-Aware Multiscale Image Registration Via OBBTree-Based Polyaffine Log-Demons. In Proceedings of Medical Image Computing and Computer Assisted Intervention 2011 (MICCAI), volume 6892 of LNCS, pages 631-638, September 2011. Springer, Heidelberg. Note: Young Scientist Award. [bibtex-key = Seiler:MICCAI:11] [bibtex-entry]

Christof Seiler, Xavier Pennec, Lucas Ritacco, and Mauricio Reyes. Femur Specific Polyaffine Model to Regularize the Log-Domain Demons Registration. In Benoit M. Dawant and David R. Haynor, editors, Proceedings of SPIE Medical Imaging '11, volume 7962, pages Paper 7962-15, January 2011. SPIE Publishing. ISBN: 9780819485045. [bibtex-key = Seiler:SPIE:11] [bibtex-entry]

Viviana Siless, Pamela Guevara, Xavier Pennec, and Pierre Fillard. Joint T1 and Brain Fiber Diffeomorphic Registration Using the Demons. In Tianming Liu, Dinggang Shen, Luis Ibanez, and Xiaodong Tao, editors, Multimodal Brain Image Analysis (First Int. MICCAI Workshop on), volume 7012 of Lecture Notes in Computer Science, pages 10-18, 2011. Springer. ISBN: 978-3-642-24445-2.

Keyword(s): Registration - neural fibers - diffeomorphism - Demons Algorithm - intensity-base registration - tensor-base registration. Abstract:

Non-linear image registration is one of the most challenging task in medical image analysis. In this work, we propose an extension of the well-established diffeomorphic Demons registration algorithm to take into account geometric constraints. Combining the deformation field induced by the image and the geometry, we define a mathematically sound framework to jointly register images and geometric descriptors such as fibers or sulcal lines. We demonstrate this framework by registering simultaneously T 1 images and 50 fiber bundles consistently extracted in 12 subjects. Results show the improvement of fibers alignment while maintaining, and sometimes improving image registration. Further comparisons with non-linear T 1 and tensor registration demonstrate the superiority of the Geometric Demons over their purely iconic counterparts.

[bibtex-key = SILESS:MBIA:2011] [bibtex-entry]

Stefan Sommer, François Lauze, Mads Nielsen, and Xavier Pennec. A Multi-scale Kernel Bundle for LDDMM: Towards Sparse Deformation Description Across Space and Scales. In Gabor Szekely and Horst Hahn, editors, Proceedings of Information Processing in Medical Images IPMI'11, volume 6801 of LNCS, pages 624-635, July 2011. Springer. [bibtex-key = Sommer:IPMI:11] [bibtex-entry]

Stefan Sommer, François Lauze, Mads Nielsen, and Xavier Pennec. Kernel Bundle EPDiff: Evolution Equations for Multi-Scale Diffeomorphic Image Registration. In A.M. Bruckstein, B. ter Haar Romeny, A.M. Bronstein, and M.M. Bronstein, editors, Scale Space and Variational Methods in Computer Vision, volume 6667 of Lecture Notes in Computer Science, Ein-Gedi, Israël, June 2011. Springer.

Abstract:

In the LDDMM framework, optimal warps for image registration are found as end-points of critical paths for an energy functional, and the EPDiff equations describe the evolution along such paths. The Large Deformation Diffeomorphic Kernel Bundle Mapping (LDDKBM) extension of LDDMM allows scale space information to be automatically incorporated in registrations and promises to improve the standard framework in several aspects. We present the mathematical foundations of LDDKBM and derive the KB-EPDiff evolution equations, which provide optimal warps in this new framework. To illustrate the resulting diffeomorphism paths, we give examples showing the decoupled evolution across scales and how the method automatically incorporates deformation at appropriate scales.

[bibtex-key = Sommer:SSVM:2011] [bibtex-entry]

Barbara André, Tom Vercauteren, Anna M. Buchner, Muhammad Waseem Shahid, Michael B. Wallace, and Nicholas Ayache. An image retrieval approach to setup difficulty levels in training systems for endomicroscopy diagnosis. In Medical Image Computing and Computer-Assisted Intervention (MICCAI'10), number 6362 of Lecture Notes in Computer Science, Beijing, China, pages 480-487, September 2010. Springer. [bibtex-key = Andre:MICCAI:10] [bibtex-entry]

Barbara André, Tom Vercauteren, Michael B. Wallace, Anna M. Buchner, and Nicholas Ayache. Endomicroscopic video retrieval using mosaicing and visual words. In Proceedings of the Seventh IEEE International Symposium on Biomedical Imaging 2010 (ISBI'10), pages 1419-1422, 2010. IEEE. [bibtex-key = Andre:ISBI:10] [bibtex-entry]

S. Bauer, Christof Seiler, T. Bardyn, P. Büchler, and Mauricio Reyes. Atlas-Based Segmentation of Brain Tumor Images Using a Markov Random Field-Based Tumor Growth Model and Non-Rigid Registration. In EMBC, September 2010. [bibtex-key = BauerSeiler:EMBC:10] [bibtex-entry]

S. Bonaretti, M. Kistler, C. Seiler, M. Reyes, and P. Büchler. Combined Statistical Model of Bone Shape and Mechanical Properties for Bone and Implant Modeling. In CMBBE, February 2010. [bibtex-key = BonarettiSeiler:CMBBE:10] [bibtex-entry]

Caroline Brun, Natasha Leporé, Y.-Y. Chou, Xavier Pennec, Greig de Zubicaray, K.L. McMahon, M.J. Wright, James C. Gee, and Paul M. Thompson. A 3D Statistical Fluid Registration Algorithm. In Workshop on Machine Learning in Medical Imaging (MLMI'2010), Beijing, September 2010. [bibtex-key = Brun:MLMI:2010] [bibtex-entry]

Caroline Brun, Natasha Leporé, Xavier Pennec, Y.-Y. Chou, A.D. Lee, M. Barysheva, Greig de Zubicaray, K.L. McMahon, M.J. Wright, and Paul M. Thompson. Statistically assisted fluid image registration algorithm - SAFIRA. In Proceedings of the Seventh IEEE International Symposium on Biomedical Imaging 2010 (ISBI'10), pages 364-367, 2010. IEEE. [bibtex-key = Brun:ISBI:10] [bibtex-entry]

Stanley Durrleman, Xavier Pennec, Alain Trouvé, Nicholas Ayache, and José Braga. Comparison of the endocast growth of chimpanzees and bonobos via temporal regression and spatiotemporal registration. In Miccai Workshop on Spatio-Temporal Image Analysis for Longitudinal and Time-Series Image Data, Beijing, China, September 2010. [bibtex-key = Durrleman:STIA:2010] [bibtex-entry]

Stanley Durrleman, Xavier Pennec, Alain Trouvé, Nicholas Ayache, and José Braga. Measuring the inter-species variability of endocast growth using shape regression and spatiotemporal registration. In Abstracts of the 79-th annual meeting of the American Assoc. of Physical Anthropologists (AAPA), April 2010, Albuquerque, pages 78-79, 2010. [bibtex-key = Durrleman:AAPA:10] [bibtex-entry]

Vincent Garcia, Olivier Commowick, and Grégoire Malandain. A Robust and Efficient Block Matching Framework for Non Linear Registration of Thoracic CT Images. In Grand Challenges in Medical Image Analysis (MICCAI workshop), Beijing, China, September 2010. [bibtex-key = Garcia:2010:EMPIRE10:2] [bibtex-entry]

Vincent Garcia, Tom Vercauteren, Grégoire Malandain, and Nicholas Ayache. Diffeomorphic demons and the EMPIRE10 challenge. In Grand Challenges in Medical Image Analysis (MICCAI workshop), Beijing, China, September 2010. [bibtex-key = Garcia:2010:EMPIRE10:1] [bibtex-entry]

Ezequiel Geremia, Bjoern H. Menze, Olivier Clatz, Ender Konukoglu, Antonio Criminisi, and Nicholas Ayache. Spatial Decision Forests for MS Lesion Segmentation in Multi-Channel MR Images. In Medical Image Computing and Computer-Assisted Intervention (MICCAI'10), LNCS, Beijing, China, September 2010. Springer. [bibtex-key = Geremia:MICCAI:10] [bibtex-entry]

V. Gorbunova, Stanley Durrleman, Pechin Lo, Xavier Pennec, and M. de Bruijne. Lung CT registration combining intensity, curves and surfaces. In Proceedings of the Seventh IEEE International Symposium on Biomedical Imaging 2010 (ISBI'10), pages 340-343, 2010. IEEE. [bibtex-key = Gorbunova:ISBI:10] [bibtex-entry]

Frederik O. Kaster, Bjoern H. Menze, Marc-André Weber, and Fred A. Hamprecht. A survey on learning tumor classifier from noisy annotations by probabilistic graphical models. In MICCAI Workshop on Medical Computer Vision (MICCAI-MCV'10), Beijing, China, September 2010. [bibtex-key = Kaster:MICCAI-MCV:2010] [bibtex-entry]

Hans Lamecker and Xavier Pennec. Atlas to Image-with-Tumor Registration based on Demons and Deformation Inpainting. In Proc. MICCAI Workshop on Computational Imaging Biomarkers for Tumors - From Qualitative to Quantitative (CIBT'2010), Beijing, September 2010. [bibtex-key = Lamecker:CIBT:2010] [bibtex-entry]

N. Lepore, AA Joshi, RM. Leahy, CC Brun, YY Chou, X. Pennec, AD Lee, M. Barysheva, GI de Zubicaray, MJ. Wright, KL. McMahon, and AW Toga. New Combined Surface and Volume Registration. In Proc. of SPIE 2010, volume 7623, pages 76231E-76231E-9, 2010. [bibtex-key = Lepore:SPIE:2010] [bibtex-entry]

Marco Lorenzi, Nicholas Ayache, G. Frisoni, and Xavier Pennec. 4D registration of serial brain MR's images: a robust measure of changes applied to Alzheimer's disease. In Miccai Workshop on Spatio-Temporal Image Analysis for Longitudinal and Time-Series Image Data, Beijing,