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Publications of year 2022

Thesis

  1. 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.
    @phdthesis{jousse:tel-03890672,
    TITLE = {{Statistical modeling of face morphology for dermatology and plastic surgery}},
    AUTHOR = {Jousse, Florent},
    url-hal= {https://theses.hal.science/tel-03890672},
    NUMBER = {2022COAZ4052},
    SCHOOL = {{Universit{\'e} C{\^o}te d'Azur}},
    YEAR = {2022},
    MONTH = Sep,
    KEYWORDS = {Statistical shape modeling ; Shape registration ; Face modeling ; Geodesic kernel ; Disentangled learning ; Partial least squares ; Mod{\'e}lisation statistique de forme ; Recalage de formes ; Mod{\'e}lisation du visage ; Noyau g{\'e}od{\'e}sique ; D{\'e}m{\^e}lage de repr{\'e}sentations ; Moindres carr{\'e}s partiels},
    TYPE = {Theses},
    PDF = {https://theses.hal.science/tel-03890672/file/2022COAZ4052.pdf},
    HAL_ID = {tel-03890672},
    HAL_VERSION = {v1},
    
    }
    


  2. 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.
    @phdthesis{thanwerdas:tel-03698752,
    TITLE = {{Riemannian and stratified geometries on covariance and correlation matrices}},
    AUTHOR = {Thanwerdas, Yann},
    url-hal= {https://hal.archives-ouvertes.fr/tel-03698752},
    NUMBER = {2022COAZ4024},
    SCHOOL = {{Universit{\'e} C{\^o}te d'Azur}},
    YEAR = {2022},
    MONTH = May,
    KEYWORDS = {Riemannian geometry ; Covariance matrices ; Correlation matrices ; Families of metrics ; Geodesics ; Stratified spaces ; G{\'e}om{\'e}trie riemannienne ; Matrices de covariance ; Matrices de corr{\'e}lation ; Familles de m{\'e}triques ; G{\'e}od{\'e}siques ; Espaces stratifi{\'e}s},
    TYPE = {Theses},
    PDF = {https://hal.archives-ouvertes.fr/tel-03698752v2/file/2022COAZ4024.pdf},
    HAL_ID = {tel-03698752},
    HAL_VERSION = {v2},
    
    }
    


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.
    @article{abinader:hal-03514292,
    TITLE = {{SimulAD: A dynamical model for personalized simulation and disease staging in Alzheimer's disease}},
    AUTHOR = {Abi Nader, Cl{\'e}ment and Ribaldi, Federica and Frisoni, Giovanni B and Garibotto, Valentina and Robert, Philippe and Ayache, Nicholas and Lorenzi, Marco},
    url-hal= {https://hal.inria.fr/hal-03514292},
    JOURNAL = {{Neurobiology of Aging}},
    PUBLISHER = {{Elsevier}},
    VOLUME = {113},
    PAGES = {73-83},
    YEAR = {2022},
    MONTH = May,
    DOI = {10.1016/j.neurobiolaging.2021.12.015},
    KEYWORDS = {Alzheimer's disease ; Disease progression models ; Clinical trials ; Biomarkers},
    PDF = {https://hal.inria.fr/hal-03514292/file/nboa_2021_final.pdf},
    HAL_ID = {hal-03514292},
    HAL_VERSION = {v1},
    
    }
    


  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.
    @article{albors:hal-03863600,
    TITLE = {{Meshless Electrophysiological Modeling of Cardiac Resynchronization Therapy-Benchmark Analysis with Finite-Element Methods in Experimental Data}},
    AUTHOR = {Albors, Carlos and Lluch, {\`E}ric and Gomez, Juan Francisco and Cedilnik, Nicolas and Mountris, Konstantinos and Mansi, Tommaso and Khamzin, Svyatoslav and Dokuchaev, Arsenii and Solovyova, Olga and Pueyo, Esther and Sermesant, Maxime and Sebastian, Rafael and Morales, Hern{\'a}n and Camara, Oscar},
    url-hal= {https://hal.inria.fr/hal-03863600},
    JOURNAL = {{Applied Sciences}},
    PUBLISHER = {{MDPI}},
    VOLUME = {12},
    NUMBER = {13},
    PAGES = {6438},
    YEAR = {2022},
    MONTH = Jul,
    DOI = {10.3390/app12136438},
    HAL_ID = {hal-03863600},
    HAL_VERSION = {v1},
    
    }
    


  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.
    @article{audelan:hal-03594219,
    TITLE = {{Robust Bayesian fusion of continuous segmentation maps}},
    AUTHOR = {Audelan, Beno{\^i}t and Hamzaoui, Dimitri and Montagne, Sarah and Renard-Penna, Rapha{\"e}le and Delingette, Herv{\'e}},
    url-hal= {https://hal.inria.fr/hal-03594219},
    JOURNAL = {{Medical Image Analysis}},
    PUBLISHER = {{Elsevier}},
    VOLUME = {78},
    PAGES = {102398},
    YEAR = {2022},
    MONTH = May,
    DOI = {10.1016/j.media.2022.102398},
    KEYWORDS = {Image segmentation ; Data fusion ; Consensus ; Mixture},
    PDF = {https://hal.inria.fr/hal-03594219/file/manuscript.pdf},
    HAL_ID = {hal-03594219},
    HAL_VERSION = {v1},
    
    }
    


  4. Nicholas Ayache. La fée IA au chevet des malades. Pour la Science. Dossier, 115(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.
    @article{ayache:hal-03689197,
    TITLE = {{La f{\'e}e IA au chevet des malades}},
    AUTHOR = {Ayache, Nicholas},
    url-hal= {https://hal.archives-ouvertes.fr/hal-03689197},
    NOTE = {The article is available at the following address: https://www.pourlascience.fr/sd/medecine/la-fee-ia-au-chevet-des-malades-23684.php},
    JOURNAL = {{Pour la Science. Dossier}},
    PUBLISHER = {{Belin}},
    SERIES = {''Jusqu'o{\`u} ira l'intelligence artificielle ?''},
    VOLUME = {115},
    NUMBER = {115},
    PAGES = {18-23},
    YEAR = {2022},
    MONTH = May,
    HAL_ID = {hal-03689197},
    HAL_VERSION = {v1},
    
    }
    


  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.
    @article{bacoyannis:hal-03739242,
    TITLE = {{Deep learning formulation of ECGI evaluated on clinical data}},
    AUTHOR = {Bacoyannis, Tania Marina and Ly, Buntheng and Cochet, H and Sermesant, Maxime},
    url-hal= {https://hal.inria.fr/hal-03739242},
    JOURNAL = {{EP-Europace}},
    PUBLISHER = {{Oxford University Press (OUP)}},
    VOLUME = {24},
    NUMBER = {Supplement\_1},
    YEAR = {2022},
    MONTH = May,
    DOI = {10.1093/europace/euac053.566},
    KEYWORDS = {Electrocardiography ; Inverse Problem ; Deep learning ; Computational Modelling ; Generative Model ; Data Processing ; Clinical Evaluation},
    HAL_ID = {hal-03739242},
    HAL_VERSION = {v1},
    
    }
    


  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.
    @article{balelli:hal-03644819,
    TITLE = {{A Differentially Private Probabilistic Framework for Modeling the Variability Across Federated Datasets of Heterogeneous Multi-View Observations}},
    AUTHOR = {Balelli, Irene and Silva, Santiago and Lorenzi, Marco},
    url-hal= {https://hal.inria.fr/hal-03644819},
    JOURNAL = {{Journal of Machine Learning for Biomedical Imaging}},
    PUBLISHER = {{Melba editors}},
    YEAR = {2022},
    MONTH = Apr,
    HAL_ID = {hal-03644819},
    HAL_VERSION = {v1},
    
    }
    


  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.
    @article{benn:hal-03556752,
    TITLE = {{The Measurement and Analysis of Shapes}},
    AUTHOR = {Benn, James and Marsland, Stephen},
    url-hal= {https://hal.archives-ouvertes.fr/hal-03556752},
    JOURNAL = {{Annals of Global Analysis and Geometry}},
    PUBLISHER = {{Springer Verlag}},
    VOLUME = {62},
    PAGES = {47-70},
    YEAR = {2022},
    MONTH = Apr,
    DOI = {10.1007/s10455-022-09839-z},
    KEYWORDS = {Shape ; Currents ; Hodge theory ; Sobolev diffeomorphisms ; Euler Equations ; Probability densities},
    PDF = {https://hal.archives-ouvertes.fr/hal-03556752/file/Revision3F.pdf},
    HAL_ID = {hal-03556752},
    HAL_VERSION = {v1},
    
    }
    


  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.
    @article{blanken:hal-03942375,
    TITLE = {{Super-Resolved Microbubble Localization in Single-Channel Ultrasound RF Signals Using Deep Learning}},
    AUTHOR = {Blanken, Nathan and Wolterink, Jelmer and Delingette, Herve and Brune, Christoph and Versluis, Michel and Lajoinie, Guillaume},
    url-hal= {https://hal.inria.fr/hal-03942375},
    JOURNAL = {{IEEE Transactions on Medical Imaging}},
    PUBLISHER = {{Institute of Electrical and Electronics Engineers}},
    VOLUME = {41},
    NUMBER = {9},
    PAGES = {2532-2542},
    YEAR = {2022},
    MONTH = Sep,
    DOI = {10.1109/TMI.2022.3166443},
    HAL_ID = {hal-03942375},
    HAL_VERSION = {v1},
    
    }
    


  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.
    @article{dadoun:hal-03583297,
    TITLE = {{Detection, Localization, and Characterization of Focal Liver Lesions in Abdominal US with Deep Learning}},
    AUTHOR = {Dadoun, Hind and Rousseau, Anne-Laure and de Kerviler, Eric and Correas, Jean Michel and Tissier, Anne-Marie and Joujou, Fanny and Bodard, Sylvain and Khezzane, Kemel and de Margerie-Mellon, Constance and Delingette, Herv{\'e} and Ayache, Nicholas},
    url-hal= {https://hal.inria.fr/hal-03583297},
    JOURNAL = {{Radiology: Artificial Intelligence}},
    PUBLISHER = {{RSNA}},
    VOLUME = {4},
    NUMBER = {3},
    YEAR = {2022},
    DOI = {10.1148/ryai.210110},
    HAL_ID = {hal-03583297},
    HAL_VERSION = {v1},
    
    }
    


  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.
    @article{guigui:hal-02894783,
    TITLE = {{Numerical Accuracy of Ladder Schemes for Parallel Transport on Manifolds}},
    AUTHOR = {Guigui, Nicolas and Pennec, Xavier},
    url-hal= {https://hal.inria.fr/hal-02894783},
    JOURNAL = {{Foundations of Computational Mathematics}},
    PUBLISHER = {{Springer Verlag}},
    VOLUME = {22},
    PAGES = {757-790},
    YEAR = {2022},
    MONTH = Jun,
    DOI = {10.1007/s10208-021-09515-x},
    PDF = {https://hal.inria.fr/hal-02894783v3/file/Guigui_et_al-2021-Foundations_of_Computational_Mathematics.pdf},
    HAL_ID = {hal-02894783},
    HAL_VERSION = {v3},
    
    }
    


  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.
    @article{hamzaoui:hal-03888145,
    TITLE = {{Correction to: Prostate Volume Prediction on MRI: Tools, Accuracy and Variability}},
    AUTHOR = {Hamzaoui, Dimitri and Montagne, Sarah and Granger, Benjamin and Allera, Alexandre and Ezziane, Malek and Luzurier, Anna and Quint, Rapha{\"e}lle and Kalai, Mehdi and Ayache, Nicholas and Delingette, Herv{\'e} and Renard-Penna, Rapha{\"e}le},
    url-hal= {https://hal.sorbonne-universite.fr/hal-03888145},
    JOURNAL = {{European Radiology}},
    VOLUME = {32},
    NUMBER = {7},
    PAGES = {5035--5035},
    YEAR = {2022},
    DOI = {10.1007/s00330-022-08688-5},
    HAL_ID = {hal-03888145},
    HAL_VERSION = {v1},
    
    }
    


  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 www.springerlink.com: https://link.springer.com/article/10.1007/s00330-022-08554-4. Keyword(s): Prostate, Magnetic Resonance Imaging, Volume, PSA density, Segmentation.
    @article{hamzaoui:hal-03409262,
    TITLE = {{Prostate volume prediction on MRI: tools, accuracy and variability}},
    AUTHOR = {Hamzaoui, Dimitri and Montagne, Sarah and Granger, Benjamin and Allera, Alexandre and Ezziane, Malek and Luzurier, Anna and Quint, Rapha{\"e}le and Kalai, Mehdi and Ayache, Nicholas and Delingette, Herv{\'e} and Renard-Penna, Raphaele},
    url-hal= {https://hal.archives-ouvertes.fr/hal-03409262},
    NOTE = {The original publication is available at www.springerlink.com: https://link.springer.com/article/10.1007/s00330-022-08554-4},
    JOURNAL = {{European Radiology}},
    PUBLISHER = {{Springer Verlag}},
    YEAR = {2022},
    MONTH = Feb,
    DOI = {10.1007/s00330-022-08554-4},
    KEYWORDS = {Prostate ; Magnetic Resonance Imaging ; Volume ; PSA density ; Segmentation},
    PDF = {https://hal.archives-ouvertes.fr/hal-03409262/file/EURA-D-21-03295_R1-16-47.pdf},
    HAL_ID = {hal-03409262},
    HAL_VERSION = {v1},
    
    }
    


  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.
    @article{hamzaoui:hal-03587074,
    TITLE = {{Automatic Zonal Segmentation of the Prostate from 2D and 3D T2-weighted MRI and Evaluation for Clinical Use}},
    AUTHOR = {Hamzaoui, Dimitri and Montagne, Sarah and Renard-Penna, Raphaele and Ayache, Nicholas and Delingette, Herv{\'e}},
    url-hal= {https://hal.archives-ouvertes.fr/hal-03587074},
    JOURNAL = {{Journal of Medical Imaging}},
    PUBLISHER = {{SPIE Digital Library}},
    VOLUME = {9},
    NUMBER = {2},
    PAGES = {024001},
    YEAR = {2022},
    MONTH = Mar,
    DOI = {10.1117/1.JMI.9.2.024001},
    KEYWORDS = {Prostate ; Segmentation ; Deep Learning ; Lesion ; Magnetic Resonance Imaging ; Inter-rater Variability},
    PDF = {https://hal.archives-ouvertes.fr/hal-03587074v2/file/JMI-21261R_online.pdf},
    HAL_ID = {hal-03587074},
    HAL_VERSION = {v2},
    
    }
    


  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.
    @article{ilie:hal-03621585,
    TITLE = {{Deep learning facilitates distinguishing histologic subtypes of pulmonary neuroendocrine tumors on digital whole-slide images}},
    AUTHOR = {Ilie, Marius and Benzaquen, Jonathan and Tourniaire, Paul and Heeke, Simon and Ayache, Nicholas and Delingette, Herv{\'e} and Long-Mira, Elodie and Lassalle, Sandra and Hamila, Marame and Fayada, Julien and Otto, Josiane and Cohen, Charlotte and Gomez Caro, Abel and Berthet, Jean Philippe and Marquette, Charles Hugo and Hofman, V{\'e}ronique and Bontoux, Christophe and Hofman, Paul},
    url-hal= {https://hal.inria.fr/hal-03621585},
    JOURNAL = {{Cancers}},
    PUBLISHER = {{MDPI}},
    VOLUME = {14},
    NUMBER = {7},
    PAGES = {1740},
    YEAR = {2022},
    MONTH = Mar,
    DOI = {10.3390/cancers14071740},
    KEYWORDS = {lung ; neuroendocrine carcinoma ; deep learning ; CNN ; HALO-AI},
    HAL_ID = {hal-03621585},
    HAL_VERSION = {v1},
    
    }
    


  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.
    @article{lareyre:hal-03846183,
    TITLE = {{Big Data and Artificial Intelligence in Vascular Surgery: Time for Multidisciplinary Cross-Border Collaboration}},
    AUTHOR = {Lareyre, Fabien and Behrendt, Christian-Alexander and Chaudhuri, Arindam and Ayache, Nicholas and Raffort, Juliette and Delingette, Herv{\'e}},
    url-hal= {https://hal.archives-ouvertes.fr/hal-03846183},
    JOURNAL = {{Angiology}},
    PUBLISHER = {{SAGE Publications}},
    VOLUME = {73},
    NUMBER = {8},
    PAGES = {697-700},
    YEAR = {2022},
    MONTH = Sep,
    DOI = {10.1177/00033197221113146},
    HAL_ID = {hal-03846183},
    HAL_VERSION = {v1},
    
    }
    


  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.
    @article{margeta:hal-03846584,
    TITLE = {{A Web-Based Automated Image Processing Research Platform for Cochlear Implantation-Related Studies}},
    AUTHOR = {Margeta, Jan and Hussain, Raabid and L{\'o}pez Diez, Paula and Morgenstern, Anika and Demarcy, Thomas and Wang, Zihao and Gnansia, Dan and Martinez Manzanera, Octavio and Vandersteen, Clair and Delingette, Herv{\'e} and Buechner, Andreas and Lenarz, Thomas and Patou, Fran{\c c}ois and Guevara, Nicolas},
    url-hal= {https://hal.inria.fr/hal-03846584},
    JOURNAL = {{Journal of Clinical Medicine}},
    PUBLISHER = {{MDPI}},
    VOLUME = {11},
    NUMBER = {22},
    PAGES = {6640},
    YEAR = {2022},
    MONTH = Nov,
    DOI = {10.3390/jcm11226640},
    KEYWORDS = {cochlear implant ; image analysis ; computed tomography ; machine learning ; deep learning ; image segmentation ; 3D model ; tonotopic mapping ; visualization},
    PDF = {https://hal.inria.fr/hal-03846584/file/jcm-11-06640.pdf},
    HAL_ID = {hal-03846584},
    HAL_VERSION = {v1},
    
    }
    


  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.
    @article{merle:hal-03934424,
    TITLE = {{MUSIC: Cardiac Imaging, Modelling and Visualisation Software for Diagnosis and Therapy}},
    AUTHOR = {Merle, Mathilde and Collot, Florent and Castelneau, Julien and Migerditichan, Pauline and Juhoor, Mehdi and Ly, Buntheng and Ozenne, Valery and Quesson, Bruno and Zemzemi, Nejib and Coudi{\`e}re, Yves and Ja{\"i}s, Pierre and Cochet, Hubert and Sermesant, Maxime},
    url-hal= {https://hal.inria.fr/hal-03934424},
    JOURNAL = {{Applied Sciences}},
    PUBLISHER = {{MDPI}},
    VOLUME = {12},
    NUMBER = {12},
    PAGES = {6145},
    YEAR = {2022},
    MONTH = Jun,
    DOI = {10.3390/app12126145},
    HAL_ID = {hal-03934424},
    HAL_VERSION = {v1},
    
    }
    


  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.
    @article{myers:hal-03903044,
    TITLE = {{ICLR 2022 Challenge for Computational Geometry \& Topology: Design and Results}},
    AUTHOR = {Myers, Adele and Utpala, Saiteja and Talbar, Shubham and Sanborn, Sophia and Shewmake, Christian and Donnat, Claire and Mathe, Johan and Lupo, Umberto and Sonthalia, Rishi and Cui, Xinyue and Szwagier, Tom and Pignet, Arthur and Bergsson, Andri and Hauberg, Soren and Nielsen, Dmitriy and Sommer, Stefan and Klindt, David and Hermansen, Erik and Vaupel, Melvin and Dunn, Benjamin and Xiong, Jeffrey and Aharony, Noga and Pe'Er, Itsik and Ambellan, Felix and Hanik, Martin and Nava-Yazdani, Esfandiar and von Tycowicz, Christoph and Miolane, Nina},
    url-hal= {https://hal.science/hal-03903044},
    JOURNAL = {{Proceedings of Machine Learning Research}},
    PUBLISHER = {{PMLR}},
    SERIES = {Topological, Algebraic and Geometric Learning Workshops 2022},
    VOLUME = {196},
    PAGES = {269-276},
    YEAR = {2022},
    MONTH = Nov,
    DOI = {10.5281/zenodo.6554616},
    PDF = {https://hal.science/hal-03903044/file/myers22a%20%281%29.pdf},
    HAL_ID = {hal-03903044},
    HAL_VERSION = {v1},
    
    }
    


  19. M Nuñez-Garcia, S Finsterbach, Buntheng Ly, Marco Lorenzi, H Cochet, and M 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.
    @article{nunezgarcia:hal-03909887,
    TITLE = {{Long-term remodelling and arrhythmogenicity after myocardial infarction using a novel image-based estimator: the Scar Maturation Score}},
    AUTHOR = {Nu{\~n}ez-Garcia, M and Finsterbach, S and Ly, Buntheng and Lorenzi, Marco and Cochet, H and Sermesant, M},
    url-hal= {https://hal.inria.fr/hal-03909887},
    JOURNAL = {{EP-Europace}},
    PUBLISHER = {{Oxford University Press (OUP)}},
    VOLUME = {24},
    NUMBER = {Supplement\_1},
    YEAR = {2022},
    MONTH = May,
    DOI = {10.1093/europace/euac053.042},
    HAL_ID = {hal-03909887},
    HAL_VERSION = {v1},
    
    }
    


  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.
    @article{rodriguezpadilla:hal-03902767,
    TITLE = {{Impact of intraventricular septal fiber orientation on cardiac electromechanical function}},
    AUTHOR = {Rodr{\'i}guez-Padilla, Jairo and Petras, Argyrios and Magat, Julie and Bayer, Jason and Bihan-Poudec, Yann and El Hamrani, Dounia and Ramlugun, Girish and Neic, Aurel and Augustin, Christoph and Vaillant, Fanny and Constantin, Marion and Benoist, David and Pourtau, Line and Dubes, Virginie and Rogier, Julien and Labrousse, Louis and Bernus, Olivier and Quesson, Bruno and Ha{\"i}ssaguerre, Michel and Gsell, Matthias and Plank, Gernot and Ozenne, Val{\'e}ry and Vigmond, Edward},
    url-hal= {https://hal.inria.fr/hal-03902767},
    JOURNAL = {{AJP - Heart and Circulatory Physiology}},
    PUBLISHER = {{American Physiological Society}},
    VOLUME = {322},
    NUMBER = {6},
    PAGES = {H936-H952},
    YEAR = {2022},
    MONTH = Jun,
    DOI = {10.1152/ajpheart.00050.2022},
    HAL_ID = {hal-03902767},
    HAL_VERSION = {v1},
    
    }
    


  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.
    @article{schmidtmengin:hal-03836922,
    TITLE = {{Online hard example mining vs. fixed oversampling strategy for segmentation of new multiple sclerosis lesions from longitudinal FLAIR MRI}},
    AUTHOR = {Schmidt- Mengin, Marius and Soulier, Th{\'e}odore and Hamzaoui, Mariem and Yazdan-Panah, Arya and Bodini, Benedetta and Ayache, Nicholas and Stankoff, Bruno and Colliot, Olivier},
    url-hal= {https://hal.archives-ouvertes.fr/hal-03836922},
    JOURNAL = {{Frontiers in Neuroscience}},
    PUBLISHER = {{Frontiers}},
    VOLUME = {16},
    PAGES = {100405},
    YEAR = {2022},
    DOI = {10.3389/fnins.2022.1004050},
    KEYWORDS = {New lesions segmentation ; Deep learning ; Hard example mining ; Multiple sclerosis ; MRI},
    PDF = {https://hal.archives-ouvertes.fr/hal-03836922/file/fnins-16-1004050.pdf},
    HAL_ID = {hal-03836922},
    HAL_VERSION = {v1},
    
    }
    


  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.
    @article{thanwerdas:hal-03414887,
    TITLE = {{The geometry of mixed-Euclidean metrics on symmetric positive definite matrices}},
    AUTHOR = {Thanwerdas, Yann and Pennec, Xavier},
    url-hal= {https://hal.archives-ouvertes.fr/hal-03414887},
    JOURNAL = {{Differential Geometry and its Applications}},
    PUBLISHER = {{Elsevier}},
    VOLUME = {81},
    NUMBER = {101867},
    YEAR = {2022},
    MONTH = Apr,
    DOI = {10.1016/j.difgeo.2022.101867},
    KEYWORDS = {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},
    PDF = {https://hal.archives-ouvertes.fr/hal-03414887/file/main.pdf},
    HAL_ID = {hal-03414887},
    HAL_VERSION = {v1},
    
    }
    


  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.
    @article{thanwerdas:hal-03527072,
    TITLE = {{Theoretically and computationally convenient geometries on full-rank correlation matrices}},
    AUTHOR = {Thanwerdas, Yann and Pennec, Xavier},
    url-hal= {https://hal.archives-ouvertes.fr/hal-03527072},
    JOURNAL = {{SIAM Journal on Matrix Analysis and Applications}},
    PUBLISHER = {{Society for Industrial and Applied Mathematics}},
    VOLUME = {43},
    NUMBER = {4},
    PAGES = {1851-1872},
    YEAR = {2022},
    MONTH = Dec,
    DOI = {10.1137/22M1471729},
    KEYWORDS = {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},
    PDF = {https://hal.archives-ouvertes.fr/hal-03527072v2/file/SIMAX_YT_XP_Convenient_geometries_correlation_HAL.pdf},
    HAL_ID = {hal-03527072},
    HAL_VERSION = {v2},
    
    }
    


  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, Artificial intelligence, Deep learning, Magnetic resonance imaging, Prostate cancer.
    @article{wu:hal-03923997,
    TITLE = {{Automatic segmentation of prostate zonal anatomy on MRI: a systematic review of the literature}},
    AUTHOR = {Wu, Carine and Montagne, Sarah and Hamzaoui, Dimitri and Ayache, Nicholas and Delingette, Herv{\'e} and Renard-Penna, Rapha{\"e}le},
    url-hal= {https://hal.science/hal-03923997},
    JOURNAL = {{Insights into Imaging}},
    PUBLISHER = {{Springer}},
    VOLUME = {13},
    NUMBER = {1},
    PAGES = {202},
    YEAR = {2022},
    MONTH = Dec,
    DOI = {10.1186/s13244-022-01340-2},
    KEYWORDS = {Artificial intelligence Deep learning Magnetic resonance imaging Prostate cancer ; Artificial intelligence ; Deep learning ; Magnetic resonance imaging ; Prostate cancer},
    HAL_ID = {hal-03923997},
    HAL_VERSION = {v1},
    
    }
    


  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.
    @incollection{guigui:hal-03684811,
    TITLE = {{Parallel transport, a central tool in geometric statistics for computational anatomy: Application to cardiac motion modeling}},
    AUTHOR = {Guigui, Nicolas and Pennec, Xavier},
    url-hal= {https://hal.inria.fr/hal-03684811},
    BOOKTITLE = {{Geometry and Statistics}},
    EDITOR = {Frank Nielsen and Arni S.R. Srinivasa Rao and C.R. Rao},
    PUBLISHER = {{Elsevier}},
    SERIES = {Handbook of Statistics},
    VOLUME = {46},
    PAGES = {285-326},
    YEAR = {2022},
    MONTH = May,
    DOI = {10.1016/bs.host.2022.03.006},
    KEYWORDS = {Parallel transport ; longitudinal studies ; mean trajectory ; cardiac motion analysis ; Schild's ladder ; pole ladder ; Riemannian manifolds},
    PDF = {https://hal.inria.fr/hal-03684811/file/H0S_ParallelTransport.pdf},
    HAL_ID = {hal-03684811},
    HAL_VERSION = {v1},
    
    }
    


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.
    @inproceedings{fraboni:hal-03500307,
    TITLE = {{A General Theory for Client Sampling in Federated Learning}},
    AUTHOR = {Fraboni, Yann and Vidal, Richard and Kameni, Laetitia and Lorenzi, Marco},
    url-hal= {https://hal.archives-ouvertes.fr/hal-03500307},
    BOOKTITLE = {{International Workshop on Trustworthy Federated Learning in Conjunction with IJCAI 2022 (FL-IJCAI'22)}},
    ADDRESS = {Vienna, Austria},
    YEAR = {2022},
    MONTH = Jul,
    PDF = {https://hal.archives-ouvertes.fr/hal-03500307v2/file/A_General_Theory_for_Client_Sampling_in_Federated_Learning.pdf},
    HAL_ID = {hal-03500307},
    HAL_VERSION = {v2},
    
    }
    


  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.
    @inproceedings{hamzaoui:hal-03775967,
    TITLE = {{MOrphologically-aware Jaccard-based ITerative Optimization (MOJITO) for Consensus Segmentation}},
    AUTHOR = {Hamzaoui, Dimitri and Montagne, Sarah and Renard-Penna, Raphaele and Ayache, Nicholas and Delingette, Herv{\'e}},
    url-hal= {https://hal.science/hal-03775967},
    BOOKTITLE = {{MICCAI Workshop UNSURE 2022: Uncertainty for Safe Utilization of Machine Learning in Medical Imaging}},
    ADDRESS = {Singapore, Singapore},
    YEAR = {2022},
    MONTH = Sep,
    KEYWORDS = {Consensus Algorithm ; Segmentation 2D et 3D ; Jaccard distance ; STAPLE},
    PDF = {https://hal.science/hal-03775967/file/JaccardConsensus__Anonymized_%285%29.pdf},
    HAL_ID = {hal-03775967},
    HAL_VERSION = {v1},
    
    }
    


  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.
    @inproceedings{kashtanova:hal-03687596,
    TITLE = {{Deep Learning for Model Correction in Cardiac Electrophysiological Imaging}},
    AUTHOR = {Kashtanova, Victoriya and Ayed, Ibrahim and Arrieula, Andony and Potse, Mark and Gallinari, Patrick and Sermesant, Maxime},
    url-hal= {https://hal.science/hal-03687596},
    BOOKTITLE = {{MIDL 2022 - Medical Imaging with Deep Learning}},
    ADDRESS = {Zurich, Switzerland},
    YEAR = {2022},
    MONTH = Jul,
    KEYWORDS = {Electrophysiology ; Deep learning ; Simulations ; Physics-based learning},
    PDF = {https://hal.science/hal-03687596/file/Kashtanova_MIDL22_Camera_Ready.pdf},
    HAL_ID = {hal-03687596},
    HAL_VERSION = {v1},
    
    }
    


  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.
    @inproceedings{kashtanova:hal-03894974,
    TITLE = {{APHYN-EP: Physics-based deep learning framework to learn and forecast cardiac electrophysiology dynamics}},
    AUTHOR = {Kashtanova, Victoriya and Pop, Mihaela and Ayed, Ibrahim and Gallinari, Patrick and Sermesant, Maxime},
    url-hal= {https://hal.inria.fr/hal-03894974},
    BOOKTITLE = {{STACOM 2022 - 13th Workhop on Statistical Atlases and Computational Modelling of the Heart}},
    ADDRESS = {Singapore, Singapore},
    YEAR = {2022},
    MONTH = Sep,
    KEYWORDS = {Physics-based learning Deep Learning Electrophysiology Simulations ; Physics-based learning ; Deep Learning ; Electrophysiology ; Simulations},
    PDF = {https://hal.inria.fr/hal-03894974/file/STACOM2022_Workshop-ready.pdf},
    HAL_ID = {hal-03894974},
    HAL_VERSION = {v1},
    
    }
    


  5. Huiyu Li, Nicholas Ayache, and Hervé Delingette. Data Stealing Attack on Medical Images: Is it Safe to Export Networks from Data Lakes?. In MICCAI Workshop on Distributed, Collaborative and Federated Learning, Singapore, Singapore, September 2022. Note: Best Paper Award. Keyword(s): Data Stealing Attack, Privacy, Medical Images.
    @inproceedings{li:hal-03775940,
    TITLE = {{Data Stealing Attack on Medical Images: Is it Safe to Export Networks from Data Lakes?}},
    AUTHOR = {Li, Huiyu and Ayache, Nicholas and Delingette, Herv{\'e}},
    url-hal= {https://hal.inria.fr/hal-03775940},
    NOTE = {Best Paper Award},
    BOOKTITLE = {{MICCAI Workshop on Distributed, Collaborative and Federated Learning}},
    ADDRESS = {Singapore, Singapore},
    YEAR = {2022},
    MONTH = Sep,
    KEYWORDS = {Data Stealing Attack ; Privacy ; Medical Images},
    PDF = {https://hal.inria.fr/hal-03775940/file/Paper.pdf},
    HAL_ID = {hal-03775940},
    HAL_VERSION = {v1},
    
    }
    


  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.
    @inproceedings{ly:hal-03829609,
    TITLE = {{Interpretable Prediction of Post-Infarct Ventricular Arrhythmia using Graph Convolutional Network}},
    AUTHOR = {Ly, Buntheng and Finsterbach, Sonny and Nu{\~n}ez-Garcia, Marta and Ja{\"i}s, Pierre and Garreau, Damien and Cochet, Hubert and Sermesant, Maxime},
    url-hal= {https://hal.inria.fr/hal-03829609},
    BOOKTITLE = {{STACOM 2022 - 13th Workhop on Statistical Atlases and Computational Modelling of the Heart}},
    ADDRESS = {Singapore, Singapore},
    YEAR = {2022},
    MONTH = Sep,
    KEYWORDS = {Graph Neural Network ; Ventricular Arrhythmia ; Interpretable AI ; Cardiac CT},
    PDF = {https://hal.inria.fr/hal-03829609/file/STACOM2022_Graph_Learning_Paper_camready.pdf},
    HAL_ID = {hal-03829609},
    HAL_VERSION = {v1},
    
    }
    


  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.
    @inproceedings{taiello:hal-03697446,
    TITLE = {{Privacy Preserving Image Registration}},
    AUTHOR = {Taiello, Riccardo and {\"O}nen, Melek and Humbert, Olivier and Lorenzi, Marco},
    url-hal= {https://hal.inria.fr/hal-03697446},
    BOOKTITLE = {{MICCAI 2022 - Medical Image Computing and Computer Assisted Intervention}},
    ADDRESS = {Singapore, Singapore},
    YEAR = {2022},
    MONTH = Sep,
    KEYWORDS = {Image Registration ; Privacy enhancing technologies ; Trustworthiness},
    PDF = {https://hal.inria.fr/hal-03697446v3/file/Privacy_Preserving_Image_Registration.pdf},
    HAL_ID = {hal-03697446},
    HAL_VERSION = {v3},
    
    }
    


  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.
    @inproceedings{terrail:hal-03900026,
    TITLE = {{FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings}},
    AUTHOR = {Terrail, Jean Ogier Du and Ayed, Samy-Safwan and Cyffers, Edwige and Grimberg, Felix and He, Chaoyang and Loeb, Regis and Mangold, Paul and Marchand, Tanguy and Marfoq, Othmane and Mushtaq, Erum and Muzellec, Boris and Philippenko, Constantin and Silva, Santiago and Tele{\'n}czuk, Maria and Albarqouni, Shadi and Avestimehr, Salman and Bellet, Aur{\'e}lien and Dieuleveut, Aymeric and Jaggi, Martin and Karimireddy, Sai Praneeth and Lorenzi, Marco and Neglia, Giovanni and Tommasi, Marc and Andreux, Mathieu},
    url-hal= {https://hal.science/hal-03900026},
    BOOKTITLE = {{NeurIPS 2022 - Thirty-sixth Conference on Neural Information Processing Systems}},
    ADDRESS = {New Orleans, United States},
    SERIES = {Proceedings of NeurIPS},
    YEAR = {2022},
    MONTH = Nov,
    HAL_ID = {hal-03900026},
    HAL_VERSION = {v1},
    
    }
    


  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.
    @inproceedings{wang:hal-03792276,
    TITLE = {{Unsupervised Echocardiography Registration through Patch-based MLPs and Transformers}},
    AUTHOR = {Wang, Zihao and Yang, Yingyu and Sermesant, Maxime and Delingette, Herv{\'e}},
    url-hal= {https://hal.inria.fr/hal-03792276},
    BOOKTITLE = {{STACOM 2022 - 13th workshop on Statistical Atlases and Computational Models of the Heart}},
    ADDRESS = {Singapore, Singapore},
    YEAR = {2022},
    MONTH = Sep,
    KEYWORDS = {Unsupervised Registration ; MLP ; Transformer ; Echocardiography},
    PDF = {https://hal.inria.fr/hal-03792276/file/REG_STACOM2022.pdf},
    HAL_ID = {hal-03792276},
    HAL_VERSION = {v1},
    
    }
    


  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, ECG analysis, Reconstruction, Explainable ML, Myocardial infarction classification.
    @inproceedings{yang:hal-03888791,
    TITLE = {{Explainable Electrocardiogram Analysis with Wave Decomposition: Application to Myocardial Infarction Detection}},
    AUTHOR = {Yang, Yingyu and Rocher, Marie and Moceri, Pamela and Sermesant, Maxime},
    url-hal= {https://hal.inria.fr/hal-03888791},
    BOOKTITLE = {{STACOM 2022 - 13th workshop on Statistical Atlases and Computational Models of the Heart}},
    ADDRESS = {Singapore, Singapore},
    YEAR = {2022},
    MONTH = Sep,
    KEYWORDS = {ECG analysis Reconstruction Explainable ML Myocardial infarction classification ; ECG analysis ; Reconstruction ; Explainable ML ; Myocardial infarction classification},
    PDF = {https://hal.inria.fr/hal-03888791/file/ECG_STACOM2022.pdf},
    HAL_ID = {hal-03888791},
    HAL_VERSION = {v1},
    
    }
    


Miscellaneous

  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.
    @misc{burgosfernandez:hal-03695867,
    TITLE = {{Deep learning for eye fundus diagnosis based on multispectral imaging}},
    AUTHOR = {Burgos-Fernandez, Francisco J and Ly, Buntheng and D{\'i}az-Dout{\'o}n, Fernando and Vilaseca, Meritxell and Pujol, Jaume and Sermesant, Maxime},
    url-hal= {https://hal.inria.fr/hal-03695867},
    NOTE = {Poster},
    HOWPUBLISHED = {{ARVO 2022 - Annual meeting of the Association for Research in Vision and Ophthalmology}},
    YEAR = {2022},
    MONTH = May,
    PDF = {https://hal.inria.fr/hal-03695867/file/ARVO2022_Abstract_FranciscoJBurgos.pdf},
    HAL_ID = {hal-03695867},
    HAL_VERSION = {v1},
    
    }
    


  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.
    @misc{maignant:hal-03909427,
    TITLE = {{Looking for invariance in Locally Linear Embedding}},
    AUTHOR = {Maignant, Elodie and Pennec, Xavier and Trouv{\'e}, Alain},
    url-hal= {https://hal.archives-ouvertes.fr/hal-03909427},
    NOTE = {Poster},
    HOWPUBLISHED = {{Curves and Surfaces 2022}},
    ORGANIZATION = {{SMAI-SIGMA}},
    YEAR = {2022},
    MONTH = Jun,
    KEYWORDS = {Locally linear embedding},
    PDF = {https://hal.archives-ouvertes.fr/hal-03909427/file/Maignant_CS2022.pdf},
    HAL_ID = {hal-03909427},
    HAL_VERSION = {v1},
    
    }
    


  3. James Benn, Anna Calissano, Stephen Marsland, and Xavier Pennec. The Currents Space of Graphs. Note: Working paper or preprint, December 2022.
    @unpublished{benn:hal-03910825,
    TITLE = {{The Currents Space of Graphs}},
    AUTHOR = {Benn, James and Calissano, Anna and Marsland, Stephen and Pennec, Xavier},
    url-hal= {https://hal.inria.fr/hal-03910825},
    NOTE = {working paper or preprint},
    YEAR = {2022},
    MONTH = Dec,
    PDF = {https://hal.inria.fr/hal-03910825/file/Benn_HALTemplate-1.pdf},
    HAL_ID = {hal-03910825},
    HAL_VERSION = {v1},
    
    }
    


  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.
    @unpublished{calissano:hal-03910761,
    TITLE = {{Graph Alignment Exploiting the Spatial Organisation Improves the Similarity of Brain Networks}},
    AUTHOR = {Calissano, Anna and Papadopoulo, Th{\'e}odore and Pennec, Xavier and Deslauriers-Gauthier, Samuel},
    url-hal= {https://hal.inria.fr/hal-03910761},
    NOTE = {working paper or preprint},
    YEAR = {2022},
    MONTH = Dec,
    PDF = {https://hal.inria.fr/hal-03910761/file/BrainMatching-2.pdf},
    HAL_ID = {hal-03910761},
    HAL_VERSION = {v1},
    
    }
    


  5. 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. Note: Working paper or preprint, December 2022. Keyword(s): Dynamic population models, Ordinary differential equations, Optimal control theory, Clinical trial analysis.
    @unpublished{clairon:hal-03335826,
    TITLE = {{Parameter estimation in nonlinear mixed effect models based on ordinary differential equations: An optimal control approach}},
    AUTHOR = {Clairon, Quentin and Pasin, Chlo{\'e} and Balelli, Irene and Thi{\'e}baut, Rodolphe and Prague, M{\'e}lanie},
    url-hal= {https://hal.science/hal-03335826},
    NOTE = {working paper or preprint},
    YEAR = {2022},
    MONTH = Dec,
    KEYWORDS = {Dynamic population models ; Ordinary differential equations ; Optimal control theory ; Clinical trial analysis},
    PDF = {https://hal.science/hal-03335826v1/file/Manuscript_JSPI.pdf},
    HAL_ID = {hal-03335826},
    HAL_VERSION = {v1},
    
    }
    


  6. Hind Dadoun, Hervé Delingette, Anne-Laure Rousseau, Eric de Kerviler, and Nicholas Ayache. Deep Clustering for Abdominal Organ Classification in US imaging. Note: Working paper or preprint, June 2022. Keyword(s): ultrasound imaging, representation learning, deep clustering, semi-supervised learning.
    @unpublished{dadoun:hal-03773082,
    TITLE = {{Deep Clustering for Abdominal Organ Classification in US imaging}},
    AUTHOR = {Dadoun, Hind and Delingette, Herv{\'e} and Rousseau, Anne-Laure and de Kerviler, Eric and Ayache, Nicholas},
    url-hal= {https://hal.inria.fr/hal-03773082},
    NOTE = {working paper or preprint},
    YEAR = {2022},
    MONTH = Jun,
    KEYWORDS = {ultrasound imaging ; representation learning ; deep clustering ; semi-supervised learning},
    PDF = {https://hal.inria.fr/hal-03773082v3/file/soumission_jmi_dadoun_vf.pdf},
    HAL_ID = {hal-03773082},
    HAL_VERSION = {v3},
    
    }
    


  7. 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.
    @unpublished{fraboni:hal-03720629,
    TITLE = {{A General Theory for Federated Optimization with Asynchronous and Heterogeneous Clients Updates}},
    AUTHOR = {Fraboni, Yann and Vidal, Richard and Kameni, Laetitia and Lorenzi, Marco},
    url-hal= {https://hal.archives-ouvertes.fr/hal-03720629},
    NOTE = {working paper or preprint},
    YEAR = {2022},
    MONTH = Jul,
    PDF = {https://hal.archives-ouvertes.fr/hal-03720629/file/A_General_Theory_for_Federated_Optimization_with_Delayed_Gradients_and_Heterogeneous_Data.pdf},
    HAL_ID = {hal-03720629},
    HAL_VERSION = {v1},
    
    }
    


  8. 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.
    @unpublished{fraboni:hal-03910848,
    TITLE = {{Sequential Informed Federated Unlearning: Efficient and Provable Client Unlearning in Federated Optimization}},
    AUTHOR = {Fraboni, Yann and Vidal, Richard and Kameni, Laetitia and Lorenzi, Marco},
    url-hal= {https://hal.archives-ouvertes.fr/hal-03910848},
    NOTE = {working paper or preprint},
    YEAR = {2022},
    MONTH = Dec,
    PDF = {https://hal.archives-ouvertes.fr/hal-03910848/file/Sequential_Informed_Federated_Unlearning.pdf},
    HAL_ID = {hal-03910848},
    HAL_VERSION = {v1},
    
    }
    


  9. Etrit Haxholli and Marco Lorenzi. Augmented Neural ODE Flows. Note: Working paper or preprint, December 2022.
    @unpublished{haxholli:hal-03911870,
    TITLE = {{Augmented Neural ODE Flows}},
    AUTHOR = {Haxholli, Etrit and Lorenzi, Marco},
    url-hal= {https://hal.inria.fr/hal-03911870},
    NOTE = {working paper or preprint},
    YEAR = {2022},
    MONTH = Dec,
    PDF = {https://hal.inria.fr/hal-03911870/file/Augmented_Neural_ODE_Flows__AISTATS_final_.pdf},
    HAL_ID = {hal-03911870},
    HAL_VERSION = {v1},
    
    }
    


  10. 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.
    @unpublished{haxholli:hal-03911884,
    TITLE = {{On Tail Decay Rate Estimation of Loss Function Distributions}},
    AUTHOR = {Haxholli, Etrit and Lorenzi, Marco},
    url-hal= {https://hal.inria.fr/hal-03911884},
    NOTE = {working paper or preprint},
    YEAR = {2022},
    MONTH = Dec,
    KEYWORDS = {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},
    PDF = {https://hal.inria.fr/hal-03911884/file/Tails_Presub_JMLR__Final_Submission_.pdf},
    HAL_ID = {hal-03911884},
    HAL_VERSION = {v1},
    
    }
    


  11. Dimbihery Rabenoro and Xavier Pennec. A geometric framework for asymptotic inference of principal subspaces in PCA. Note: Working paper or preprint, November 2022.
    @unpublished{rabenoro:hal-03842125,
    TITLE = {{A geometric framework for asymptotic inference of principal subspaces in PCA}},
    AUTHOR = {Rabenoro, Dimbihery and Pennec, Xavier},
    url-hal= {https://hal.inria.fr/hal-03842125},
    NOTE = {working paper or preprint},
    YEAR = {2022},
    MONTH = Nov,
    PDF = {https://hal.inria.fr/hal-03842125/file/Geometric_Asymptotic_Inference_Subspace_PCA.pdf},
    HAL_ID = {hal-03842125},
    HAL_VERSION = {v1},
    
    }
    


  12. Yann Thanwerdas. Permutation-invariant log-Euclidean geometries on full-rank correlation matrices. Note: Working paper or preprint, November 2022. Keyword(s): SPD matrices, elliptope, correlation matrices, log-Euclidean metric, permutationinvariant, cor-inversion, off-log metric, log-scaled metric, quotient-affine metric AMS subject classifications., 15A63, 53B20, 53C22, 58D17, 53-08, 53A04, 62H20, 15B48.
    @unpublished{thanwerdas:hal-03878729,
    TITLE = {{Permutation-invariant log-Euclidean geometries on full-rank correlation matrices}},
    AUTHOR = {Thanwerdas, Yann},
    url-hal= {https://hal.archives-ouvertes.fr/hal-03878729},
    NOTE = {working paper or preprint},
    YEAR = {2022},
    MONTH = Nov,
    KEYWORDS = {SPD matrices ; elliptope ; correlation matrices ; log-Euclidean metric ; permutationinvariant ; cor-inversion ; off-log metric ; log-scaled metric ; quotient-affine metric AMS subject classifications. ; 15A63 ; 53B20 ; 53C22 ; 58D17 ; 53-08 ; 53A04 ; 62H20 ; 15B48},
    PDF = {https://hal.archives-ouvertes.fr/hal-03878729/file/SIMAX_YT_Permutation_invariant_log_Euclidean_correlation_HAL.pdf},
    HAL_ID = {hal-03878729},
    HAL_VERSION = {v1},
    
    }
    


  13. Yann Thanwerdas and Xavier Pennec. Bures-Wasserstein minimizing geodesics between covariance matrices of different ranks. Note: Working paper or preprint, April 2022. Keyword(s): Covariance matrices, PSD matrices, Bures-Wasserstein, Orbit space, Geodesics, Injection domain, 15B48, 15A63, 53B20, 53C22, 58D17, 53-08, 53A04, 54E50, 58A35.
    @unpublished{thanwerdas:hal-03647321,
    TITLE = {{Bures-Wasserstein minimizing geodesics between covariance matrices of different ranks}},
    AUTHOR = {Thanwerdas, Yann and Pennec, Xavier},
    url-hal= {https://hal.archives-ouvertes.fr/hal-03647321},
    NOTE = {working paper or preprint},
    YEAR = {2022},
    MONTH = Apr,
    KEYWORDS = {Covariance matrices ; PSD matrices ; Bures-Wasserstein ; Orbit space ; Geodesics ; Injection domain ; 15B48 ; 15A63 ; 53B20 ; 53C22 ; 58D17 ; 53-08 ; 53A04 ; 54E50 ; 58A35},
    PDF = {https://hal.archives-ouvertes.fr/hal-03647321/file/main.pdf},
    HAL_ID = {hal-03647321},
    HAL_VERSION = {v1},
    
    }
    



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