Publications of year 2020

1. 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-entry]



2. Xavier Pennec, Stephan Sommer, and Tom Fletcher. Riemannian Geometric Statistics in Medical Image Analysis. Academic Press, 2020. [bibtex-entry]

1. 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-entry]



2. 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-entry]



3. 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-entry]



4. 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-entry]

1. 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-entry]



2. 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-entry]



3. 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-entry]



4. 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-entry]



5. 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-entry]



6. 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-entry]



7. 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-entry]



8. 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-entry]



9. 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-entry]



10. 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-entry]



11. 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-entry]



12. 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-entry]



13. 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-entry]



14. 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-entry]



15. 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-entry]



16. 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-entry]



17. 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-entry]



18. 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-entry]

1. 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-entry]



2. 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-entry]



3. 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-entry]



4. 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-entry]



5. 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-entry]



6. 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-entry]



7. 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-entry]



8. 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-entry]



9. 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-entry]



10. 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-entry]



11. 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-entry]



12. 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-entry]

1. Julian Krebs and Tommaso Mansi. Method and System for Deep Motion Model Learning in Medical Images. US20200090345A1, United States, March 2020. [bibtex-entry]



2. Julian Krebs, Tommaso Mansi, Hervé Delingette, and Nicholas Ayache. Probabilist Motion Model for Generating Medical Images or Medical Image Sequences. US16834269, United States, October 2020. [bibtex-entry]

1. Zihao Wang, Zhifei Xu, Jiayi He, Hervé Delingette, and Jun Fan. Long Short-Term Memory Neural Equalizer. Note: Working paper or preprint, November 2020. Keyword(s): decision feedback equalizer, neuromorphic computing, deep learning, LSTM. [bibtex-entry]

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