Publications of year 2022


  1. 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-entry]

  2. 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-entry]

  3. 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-entry]

  4. 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-entry]

Articles in journal, book chapters

  1. 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-entry]

  2. 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-entry]

  3. 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-entry]

  4. 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: [bibtex-entry]

  5. 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-entry]

  6. 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-entry]

  7. 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-entry]

  8. 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-entry]

  9. 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-entry]

  10. 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-entry]

  11. 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-entry]

  12. 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 Keyword(s): Prostate, Magnetic Resonance Imaging, Volume, PSA density, Segmentation. [bibtex-entry]

  13. 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-entry]

  14. 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-entry]

  15. 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-entry]

  16. 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-entry]

  17. 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-entry]

  18. 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-entry]

  19. 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-entry]

  20. 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-entry]

  21. 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-entry]

  22. 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-entry]

  23. 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-entry]

  24. 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-entry]

  25. 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-entry]

Conference articles

  1. 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-entry]

  2. 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-entry]

  3. 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-entry]

  4. 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-entry]

  5. 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-entry]

  6. 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-entry]

  7. 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-entry]

  8. 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-entry]

  9. 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-entry]

  10. 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-entry]


  1. Francisco J Burgos-Fernandez, Buntheng Ly, Fernando Dìaz-Doutón, Meritxell Vilaseca, Jaume Pujol, and Maxime Sermesant. Deep learning for eye fundus diagnosis based on multispectral imaging. ARVO 2022 - Annual meeting of the Association for Research in Vision and Ophthalmology, May 2022. Note: Poster. [bibtex-entry]

  2. Elodie Maignant, Xavier Pennec, and Alain Trouvé. Looking for invariance in Locally Linear Embedding. Curves and Surfaces 2022, June 2022. Note: Poster. Keyword(s): Locally linear embedding. [bibtex-entry]

  3. James Benn, Anna Calissano, Stephen Marsland, and Xavier Pennec. The Currents Space of Graphs. Note: Working paper or preprint, December 2022. [bibtex-entry]

  4. Anna Calissano, Théodore Papadopoulo, Xavier Pennec, and Samuel Deslauriers-Gauthier. Graph Alignment Exploiting the Spatial Organisation Improves the Similarity of Brain Networks. Note: Working paper or preprint, December 2022. [bibtex-entry]

  5. Yann Fraboni, Richard Vidal, Laetitia Kameni, and Marco Lorenzi. A General Theory for Federated Optimization with Asynchronous and Heterogeneous Clients Updates. Note: Working paper or preprint, July 2022. [bibtex-entry]

  6. Yann Fraboni, Richard Vidal, Laetitia Kameni, and Marco Lorenzi. Sequential Informed Federated Unlearning: Efficient and Provable Client Unlearning in Federated Optimization. Note: Working paper or preprint, December 2022. [bibtex-entry]

  7. Etrit Haxholli and Marco Lorenzi. Augmented Neural ODE Flows. Note: Working paper or preprint, December 2022. [bibtex-entry]

  8. Etrit Haxholli and Marco Lorenzi. On Tail Decay Rate Estimation of Loss Function Distributions. Note: Working paper or preprint, December 2022. Keyword(s): Extreme Value Theory Tail Modelling Loss Function Distributions Peaks-Over-Threshold Cross-Tail-Estimation Model Ranking, Extreme Value Theory, Tail Modelling, Loss Function Distributions, Peaks-Over-Threshold, Cross-Tail-Estimation, Model Ranking. [bibtex-entry]

  9. Dimbihery Rabenoro and Xavier Pennec. A geometric framework for asymptotic inference of principal subspaces in PCA. Note: Working paper or preprint, November 2022. [bibtex-entry]



This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All person copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

Les documents contenus dans ces répertoires sont rendus disponibles par les auteurs qui y ont contribué en vue d'assurer la diffusion à temps de travaux savants et techniques sur une base non-commerciale. Les droits de copie et autres droits sont gardés par les auteurs et par les détenteurs du copyright, en dépit du fait qu'ils présentent ici leurs travaux sous forme électronique. Les personnes copiant ces informations doivent adhérer aux termes et contraintes couverts par le copyright de chaque auteur. Ces travaux ne peuvent pas être rendus disponibles ailleurs sans la permission explicite du détenteur du copyright.

Last modified: Tue Dec 5 00:30:03 2023
Author: epione-publi.

This document was translated from BibTEX by bibtex2html