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Publications of year 2021

Thesis

  1. Clement 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.
    @phdthesis{abinader:tel-03377153,
    TITLE = {{Modelling and simulating the progression of Alzheimer's disease through the analysis of multi-modal neuroimages and clinical data}},
    AUTHOR = {Abi Nader, Clement},
    url-hal= {https://tel.archives-ouvertes.fr/tel-03377153},
    NUMBER = {2021COAZ4033},
    SCHOOL = {{Universit{\'e} C{\^o}te d'Azur}},
    YEAR = {2021},
    MONTH = Jun,
    KEYWORDS = {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 r{\'e}sonance magn{\'e}tique ; Tomographie par {\'e}mission de positons ; Apprentissage automatique ; Processus gaussiens ; Auto-encodeur variationnel ; Syst{\`e}mes dynamiques},
    TYPE = {Theses},
    PDF = {https://tel.archives-ouvertes.fr/tel-03377153v2/file/2021COAZ4033.pdf},
    HAL_ID = {tel-03377153},
    HAL_VERSION = {v2},
    
    }
    


  2. 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.
    @phdthesis{antelmi:tel-03474169,
    TITLE = {{Statistical learning on heterogeneous medical data with bayesian latent variable models : application to neuroimaging dementia studies}},
    AUTHOR = {Antelmi, Luigi},
    url-hal= {https://tel.archives-ouvertes.fr/tel-03474169},
    NUMBER = {2021COAZ4050},
    SCHOOL = {{Universit{\'e} C{\^o}te d'Azur}},
    YEAR = {2021},
    MONTH = Jul,
    KEYWORDS = {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 r{\'e}sonnance magn{\'e}tique ; Tomographie par {\'e}mission de positrons ; Auto-encodeur variationnel ; Apprentissage multi-t{\^a}che ; Donn{\'e}es de haute dimension ; Donn{\'e}es multimodales},
    TYPE = {Theses},
    PDF = {https://tel.archives-ouvertes.fr/tel-03474169v2/file/2021COAZ4050.pdf},
    HAL_ID = {tel-03474169},
    HAL_VERSION = {v2},
    
    }
    


  3. 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.
    @phdthesis{audelan:tel-03406789,
    TITLE = {{Probabilistic segmentation modelling and deep learning-based lung cancer screening}},
    AUTHOR = {Audelan, Beno{\^i}t},
    url-hal= {https://tel.archives-ouvertes.fr/tel-03406789},
    NUMBER = {2021COAZ4054},
    SCHOOL = {{Universit{\'e} C{\^o}te d'Azur}},
    YEAR = {2021},
    MONTH = Jul,
    KEYWORDS = {Medical imaging ; Image segmentation ; Artificial intelligence ; Machine learning ; Deep learning ; Lung cancer ; Imagerie m{\'e}dicale ; Segmentation d'images ; Intelligence artificielle ; Apprentissage artificiel ; Apprentissage profond ; Cancer du poumon},
    TYPE = {Theses},
    PDF = {https://tel.archives-ouvertes.fr/tel-03406789/file/2021COAZ4054.pdf},
    HAL_ID = {tel-03406789},
    HAL_VERSION = {v1},
    
    }
    


  4. 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.
    @phdthesis{bacoyannis:tel-03621337,
    TITLE = {{Deep probabilistic generative model for the inverse problem of electrocardiography}},
    AUTHOR = {Bacoyannis, Tania},
    url-hal= {https://tel.archives-ouvertes.fr/tel-03621337},
    NUMBER = {2021COAZ4111},
    SCHOOL = {{Universit{\'e} C{\^o}te d'Azur}},
    YEAR = {2021},
    MONTH = Dec,
    KEYWORDS = {Cardiac activation ; Computational modelling ; Data processing ; Deep learning ; Electrocardiography ; Generative model ; Inverse problem ; Activation cardiaque ; Apprentissage profond ; {\'E}lectrocardiographique ; Mod{\'e}lisation num{\'e}rique ; Mod{\`e}le g{\'e}n{\'e}ratif ; Probl{\`e}me inverse ; Traitement de donn{\'e}es},
    TYPE = {Theses},
    PDF = {https://tel.archives-ouvertes.fr/tel-03621337/file/2021COAZ4111.pdf},
    HAL_ID = {tel-03621337},
    HAL_VERSION = {v1},
    
    }
    


  5. 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.
    @phdthesis{banus:tel-03242796,
    TITLE = {{Heart \& Brain. Linking cardiovascular pathologies and neurodegeneration with a combined biophysical and statistical methodology}},
    AUTHOR = {Banus, Jaume},
    url-hal= {https://hal.inria.fr/tel-03242796},
    NUMBER = {2021COAZ4030},
    SCHOOL = {{Universit{\'e} C{\^o}te d'Azur}},
    YEAR = {2021},
    MONTH = May,
    KEYWORDS = {Medical imaging ; Cardiovascular modelling ; Neurodegeneration ; Lumped models ; Machine learning ; Variational autoencoder ; Gaussian process ; Personalisation ; Imagerie m{\'e}dicale ; Mod{\'e}lisation cardiovasculaire ; Neurod{\'e}g{\'e}n{\'e}rescence ; Mod{\`e}les regroup{\'e}s ; Apprentissage automatique ; Autoencodeur variationnel ; Processus Gaussien ; Personnalisation},
    TYPE = {Theses},
    PDF = {https://hal.inria.fr/tel-03242796v2/file/thesis.pdf},
    HAL_ID = {tel-03242796},
    HAL_VERSION = {v2},
    
    }
    


  6. 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.
    @phdthesis{guigui:tel-03563980,
    TITLE = {{Computational methods for statistical estimation on Riemannian manifolds and application to the study of the cardiac deformations}},
    AUTHOR = {Guigui, Nicolas},
    url-hal= {https://tel.archives-ouvertes.fr/tel-03563980},
    NUMBER = {2021COAZ4081},
    SCHOOL = {{Universit{\'e} C{\^o}te d'Azur}},
    YEAR = {2021},
    MONTH = Nov,
    KEYWORDS = {Differential geometry ; Computational anatomy ; Geometric statistics ; G{\'e}om{\'e}trie diff{\'e}rentielle ; Anatomie computationnelle ; Statistiques g{\'e}om{\'e}triques},
    TYPE = {Theses},
    PDF = {https://tel.archives-ouvertes.fr/tel-03563980v2/file/2021COAZ4081.pdf},
    HAL_ID = {tel-03563980},
    HAL_VERSION = {v2},
    
    }
    


  7. Zihao Wang. Deep generative learning for medical data processing, analysis and modeling: application to cochlea ct imaging. Theses, Inria - Sophia Antipolis ; Université côte d'azur, September 2021. Keyword(s): Generative Learning, Bayesian Learning, Stochastic Flow, Deep Learning, Apprentissage génératif, Apprentissage Bayésien, Flux stochastique, Apprentissage Profond.
    @phdthesis{wang:tel-03458058,
    TITLE = {{Deep generative learning for medical data processing, analysis and modeling: application to cochlea ct imaging}},
    AUTHOR = {Wang, Zihao},
    url-hal= {https://hal.inria.fr/tel-03458058},
    SCHOOL = {{Inria - Sophia Antipolis ; Universit{\'e} c{\^o}te d'azur}},
    YEAR = {2021},
    MONTH = Sep,
    KEYWORDS = {Generative Learning ; Bayesian Learning ; Stochastic Flow ; Deep Learning ; Apprentissage g{\'e}n{\'e}ratif ; Apprentissage Bay{\'e}sien ; Flux stochastique ; Apprentissage Profond},
    TYPE = {Theses},
    PDF = {https://hal.inria.fr/tel-03458058/file/PhD_Thesis_Revised_13_Sep_.pdf},
    HAL_ID = {tel-03458058},
    HAL_VERSION = {v1},
    
    }
    


Articles in journal, book chapters

  1. 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.
    @article{abinader:hal-02968724,
    TITLE = {{Simulating the outcome of amyloid treatments in Alzheimer's Disease from multi-modal imaging and clinical data}},
    AUTHOR = {Abi Nader, Cl{\'e}ment and Ayache, Nicholas and Frisoni, Giovanni B and Robert, Philippe and Lorenzi, Marco},
    url-hal= {https://hal.archives-ouvertes.fr/hal-02968724},
    JOURNAL = {{Brain Communications}},
    PUBLISHER = {{Oxford University Press on behalf of the Guarantors of Brain}},
    YEAR = {2021},
    MONTH = Feb,
    DOI = {10.1093/braincomms/fcab091},
    KEYWORDS = {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},
    PDF = {https://hal.archives-ouvertes.fr/hal-02968724v4/file/revised_manuscript.pdf},
    HAL_ID = {hal-02968724},
    HAL_VERSION = {v4},
    
    }
    


  2. 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.
    @article{bacoyannis:hal-03268015,
    TITLE = {{Deep Learning Formulation of ECGI Integrating Image \& Signal Information with Data-driven Regularisation}},
    AUTHOR = {Bacoyannis, Tania and Ly, Buntheng and Cedilnik, Nicolas and Cochet, Hubert and Sermesant, Maxime},
    url-hal= {https://hal.inria.fr/hal-03268015},
    JOURNAL = {{EP-Europace}},
    PUBLISHER = {{Oxford University Press (OUP)}},
    VOLUME = {23},
    NUMBER = {Supplement\_1},
    PAGES = {i55-i62},
    YEAR = {2021},
    MONTH = Mar,
    DOI = {10.1093/europace/euaa391},
    KEYWORDS = {Electrocardiographic Imaging ; Inverse Problem ; Deep learning ; Computational Modelling ; Generative Model},
    PDF = {https://hal.inria.fr/hal-03268015/file/europace_2021.pdf},
    HAL_ID = {hal-03268015},
    HAL_VERSION = {v1},
    
    }
    


  3. 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.
    @article{banus:hal-03231513,
    TITLE = {{Biophysics-based statistical learning: Application to heart and brain interactions}},
    AUTHOR = {Banus, Jaume and Lorenzi, Marco and Camara, Oscar and Sermesant, Maxime},
    url-hal= {https://hal.inria.fr/hal-03231513},
    JOURNAL = {{Medical Image Analysis}},
    PUBLISHER = {{Elsevier}},
    VOLUME = {72},
    YEAR = {2021},
    MONTH = Aug,
    DOI = {10.1016/j.media.2021.102089},
    KEYWORDS = {Lumped model ; Cardiovascular modelling ; Personalisation ; White matter damage ; Atrial fibrillation ; Heart-Brain interaction},
    PDF = {https://hal.inria.fr/hal-03231513/file/main.pdf},
    HAL_ID = {hal-03231513},
    HAL_VERSION = {v1},
    
    }
    


  4. 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.
    @article{blancdurand:inserm-03006852,
    TITLE = {{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}},
    AUTHOR = {Blanc-Durand, Paul and J{\'e}gou, Simon and Kanoun, Salim and Berriolo-Riedinger, Alina and Bodet-Milin, Caroline M and Kraeber-Bod{\'e}r{\'e}, Fran{\c c}oise and Carlier, Thomas and Le Gouill, Steven and Casasnovas, Ren{\'e}-Olivier and Meignan, Michel and Itti, Emmanuel},
    url-hal= {https://www.hal.inserm.fr/inserm-03006852},
    JOURNAL = {{European Journal of Nuclear Medicine and Molecular Imaging}},
    PUBLISHER = {{Springer Verlag (Germany)}},
    SERIES = {48},
    PAGES = {1362-1370},
    YEAR = {2021},
    DOI = {10.1007/s00259-020-05080-7},
    KEYWORDS = {Convolutional neural network ; Deep learning ; Lymphoma ; Positron emission tomography ; Segmentation ; Total metabolic tumour volume ; U-net},
    PDF = {https://www.hal.inserm.fr/inserm-03006852/file/Blanc-Durand2020Eq13.pdf},
    HAL_ID = {inserm-03006852},
    HAL_VERSION = {v1},
    
    }
    


  5. 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.
    @article{casamitjana:hal-03374516,
    TITLE = {{Robust joint registration of multiple stains and MRI for multimodal 3D histology reconstruction: Application to the Allen human brain atlas}},
    AUTHOR = {Casamitjana, Adri{\`a} and Lorenzi, Marco and Ferraris, Sebastiano and Peter, Lo{\"i}c and Modat, Marc and Stevens, Allison and Fischl, Bruce and Vercauteren, Tom and Iglesias, Juan Eugenio},
    url-hal= {https://hal.inria.fr/hal-03374516},
    JOURNAL = {{Medical Image Analysis}},
    PUBLISHER = {{Elsevier}},
    YEAR = {2021},
    MONTH = Oct,
    DOI = {10.1016/j.media.2021.102265},
    KEYWORDS = {nonlinear registration ; 3D reconstruction ; linear programming ; ex vivo MRI ; histology},
    PDF = {https://hal.inria.fr/hal-03374516/file/2104.14873.pdf},
    HAL_ID = {hal-03374516},
    HAL_VERSION = {v1},
    
    }
    


  6. 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.
    @article{deprez:hal-03477486,
    TITLE = {{Decoding genetic markers of multiple phenotypic layers through biologically constrained Genome-to-Phenome Bayesian Sparse Regression}},
    AUTHOR = {Deprez, Marie and Moreira, Julien and Sermesant, Maxime and Lorenzi, Marco},
    url-hal= {https://hal.inria.fr/hal-03477486},
    JOURNAL = {{Frontiers in Molecular Medicine}},
    PUBLISHER = {{Frontiers Media}},
    YEAR = {2021},
    DOI = {10.3389/fmmed.2022.830956},
    KEYWORDS = {Bayesian ; Variational Dropout ; Genome ; Phenome ; Regression ; Biological constraint},
    PDF = {https://hal.inria.fr/hal-03477486/file/G2PSR_hal.pdf},
    HAL_ID = {hal-03477486},
    HAL_VERSION = {v1},
    
    }
    


  7. 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.
    @article{duboc:hal-03477359,
    TITLE = {{NiPTUNE: an automated pipeline for noninvasive prenatal testing in an accurate, integrative and flexible framework}},
    AUTHOR = {Duboc, V{\'e}ronique and Pratella, David and Milanesio, Marco and Boudjarane, John and Descombes, St{\'e}phane and Paquis-Flucklinger, V{\'e}ronique and Bottini, Silvia},
    url-hal= {https://hal.inria.fr/hal-03477359},
    JOURNAL = {{Briefings in Bioinformatics}},
    PUBLISHER = {{Oxford University Press (OUP)}},
    YEAR = {2021},
    MONTH = Sep,
    DOI = {10.1093/bib/bbab380},
    HAL_ID = {hal-03477359},
    HAL_VERSION = {v1},
    
    }
    


  8. 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.
    @article{duchateau:hal-03538132,
    TITLE = {{Direction-dependent decomposition of 3D right ventricular motion: beware of approximations}},
    AUTHOR = {Duchateau, Nicolas and Moceri, Pamela and Sermesant, Maxime},
    url-hal= {https://hal.archives-ouvertes.fr/hal-03538132},
    JOURNAL = {{Journal of The American Society of Echocardiography}},
    PUBLISHER = {{Elsevier}},
    VOLUME = {34},
    NUMBER = {2},
    PAGES = {201-203},
    YEAR = {2021},
    DOI = {10.1016/j.echo.2020.08.023},
    PDF = {https://hal.archives-ouvertes.fr/hal-03538132/file/Duchateau_JASE_2020.pdf},
    HAL_ID = {hal-03538132},
    HAL_VERSION = {v1},
    
    }
    


  9. 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.
    @article{garbarino:hal-03374531,
    TITLE = {{Investigating hypotheses of neurodegeneration by learning dynamical systems of protein propagation in the brain}},
    AUTHOR = {Garbarino, Sara and Lorenzi, Marco},
    url-hal= {https://hal.inria.fr/hal-03374531},
    JOURNAL = {{NeuroImage}},
    PUBLISHER = {{Elsevier}},
    VOLUME = {235},
    PAGES = {117980},
    YEAR = {2021},
    MONTH = Jul,
    DOI = {10.1016/j.neuroimage.2021.117980},
    KEYWORDS = {Neurodegeneration ; Causal model ; Dynamical systems ; Protein propagation ; Gaussian process ; Brain connectivity},
    HAL_ID = {hal-03374531},
    HAL_VERSION = {v1},
    
    }
    


  10. 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.
    @article{jia:hal-03650289,
    TITLE = {{Left atrial shape is independent predictor of arrhythmia recurrence after catheter ablation for atrial fibrillation: A shape statistics study}},
    AUTHOR = {Jia, Shuman and Nivet, Hubert and Harrison, Josquin and Pennec, Xavier and Camaioni, Claudia and Ja{\"i}s, Pierre and Cochet, Hubert and Sermesant, Maxime},
    url-hal= {https://hal.inria.fr/hal-03650289},
    JOURNAL = {{Heart Rhythm O2}},
    VOLUME = {2},
    NUMBER = {6},
    PAGES = {622-632},
    YEAR = {2021},
    MONTH = Dec,
    DOI = {10.1016/j.hroo.2021.10.013},
    KEYWORDS = {Atrial fibrillation ; Catheter ablation ; CT ; Left atrial shape ; Recurrence ; Statistical shape modeling},
    PDF = {https://hal.inria.fr/hal-03650289/file/HRO2Paper.pdf},
    HAL_ID = {hal-03650289},
    HAL_VERSION = {v1},
    
    }
    


  11. 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.
    @article{krebs:hal-03126419,
    TITLE = {{Learning a Generative Motion Model from Image Sequences based on a Latent Motion Matrix}},
    AUTHOR = {Krebs, Julian and Delingette, Herv{\'e} and Ayache, Nicholas and Mansi, Tommaso},
    url-hal= {https://hal.archives-ouvertes.fr/hal-03126419},
    JOURNAL = {{IEEE Transactions on Medical Imaging}},
    PUBLISHER = {{Institute of Electrical and Electronics Engineers}},
    YEAR = {2021},
    MONTH = Feb,
    DOI = {10.1109/TMI.2021.3056531},
    KEYWORDS = {motion model ; deformable registration ; conditional variational autoencoder ; gaussian process ; latent variable model ; motion interpolation ; motion simulation ; tracking},
    PDF = {https://hal.archives-ouvertes.fr/hal-03126419/file/krebs_final.pdf},
    HAL_ID = {hal-03126419},
    HAL_VERSION = {v1},
    
    }
    


  12. 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.
    @article{krebs:hal-03444134,
    TITLE = {{CinE caRdiac magneTic resonAnce to predIct veNTricular arrhYthmia (CERTAINTY)}},
    AUTHOR = {Krebs, Julian and Mansi, Tommaso and Delingette, Herv{\'e} and Lou, Bin and Lima, Joao and Tao, Susumu and Ciuffo, Luisa and Norgard, Sanaz and Butcher, Barbara and Lee, Wei and Chamera, Ela and Dickfeld, Timm-Michael and Stillabower, Michael and Marine, Joseph and Weiss, Robert and Tomaselli, Gordon and Halperin, Henry and Wu, Katherine and Ashikaga, Hiroshi},
    url-hal= {https://hal.archives-ouvertes.fr/hal-03444134},
    JOURNAL = {{Scientific Reports}},
    PUBLISHER = {{Nature Publishing Group}},
    VOLUME = {11},
    NUMBER = {1},
    PAGES = {22683},
    YEAR = {2021},
    MONTH = Nov,
    DOI = {10.1038/s41598-021-02111-7},
    KEYWORDS = {Cardiac device therapy ; Ventricular fibrillation ; Ventricular tachycardia},
    HAL_ID = {hal-03444134},
    HAL_VERSION = {v1},
    
    }
    


  13. 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.
    @article{lazaridis:hal-03374545,
    TITLE = {{OCT Signal Enhancement with Deep Learning}},
    AUTHOR = {Lazaridis, Georgios and Lorenzi, Marco and Mohamed-Noriega, Jibran and Aguilar-Munoa, Soledad and Suzuki, Katsuyoshi and Nomoto, Hiroki and Ourselin, Sebastien and Garway-Heath, David and Crabb, David and Bunce, Catey and Amalfitano, Francesca and Anand, Nitin and Azuara-Blanco, Augusto and Bourne, Rupert and Broadway, David and Cunliffe, Ian and Diamond, Jeremy and Fraser, Scott and Ho, Tuan and Martin, Keith and Mcnaught, Andrew and Negi, Anil and Shah, Ameet and Spry, Paul and White, Edward and Wormald, Richard and Xing, Wen and Zeyen, Thierry},
    url-hal= {https://hal.inria.fr/hal-03374545},
    JOURNAL = {{Ophthalmology Glaucoma}},
    PUBLISHER = {{Elsevier}},
    VOLUME = {4},
    NUMBER = {3},
    PAGES = {295-304},
    YEAR = {2021},
    MONTH = May,
    DOI = {10.1016/j.ogla.2020.10.008},
    KEYWORDS = {Deep learning ; Glaucoma ; Image analysis ; OCT ; Visual fields},
    HAL_ID = {hal-03374545},
    HAL_VERSION = {v1},
    
    }
    


  14. 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.
    @article{lazaridis:hal-03374539,
    TITLE = {{Improving statistical power of glaucoma clinical trials using an ensemble of cyclical generative adversarial networks}},
    AUTHOR = {Lazaridis, Georgios and Lorenzi, Marco and Ourselin, Sebastien and Garway-Heath, David},
    url-hal= {https://hal.inria.fr/hal-03374539},
    JOURNAL = {{Medical Image Analysis}},
    PUBLISHER = {{Elsevier}},
    VOLUME = {68},
    PAGES = {101906},
    YEAR = {2021},
    MONTH = Feb,
    DOI = {10.1016/j.media.2020.101906},
    KEYWORDS = {Optical coherence tomography ; Deep learning ; Perceptual loss ; GAN ; Label fusion ; Statistical power ; Clinical trials ; Glaucoma},
    HAL_ID = {hal-03374539},
    HAL_VERSION = {v1},
    
    }
    


  15. 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.
    @article{lebrigant:hal-02671122,
    TITLE = {{Classifying histograms of medical data using information geometry of beta distributions}},
    AUTHOR = {Le Brigant, Alice and Guigui, Nicolas and Rebbah, Sana and Puechmorel, St{\'e}phane},
    url-hal= {https://hal.archives-ouvertes.fr/hal-02671122},
    JOURNAL = {{IFAC-PapersOnLine}},
    PUBLISHER = {{Elsevier}},
    YEAR = {2021},
    MONTH = Jun,
    DOI = {10.1016/j.ifacol.2021.06.110},
    KEYWORDS = {histogram analysis ; clustering ; medical imaging ; Information geometry ; classification},
    PDF = {https://hal.archives-ouvertes.fr/hal-02671122v2/file/info-geom-beta.pdf},
    HAL_ID = {hal-02671122},
    HAL_VERSION = {v2},
    
    }
    


  16. 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.
    @article{moceri:hal-03544765,
    TITLE = {{Additional prognostic value of echocardiographic follow-up in pulmonary hypertension - role of 3D right ventricular area strain}},
    AUTHOR = {Moceri, Pamela and Duchateau, Nicolas and Baudouy, Delphine and Squara, Fabien and Bun, Sok Sithikun and Ferrari, Emile and Sermesant, Maxime},
    url-hal= {https://hal.archives-ouvertes.fr/hal-03544765},
    JOURNAL = {{European Heart Journal - Cardiovascular Imaging}},
    PUBLISHER = {{Oxford UP}},
    YEAR = {2021},
    DOI = {10.1093/ehjci/jeab240},
    KEYWORDS = {Pulmonary hypertension ; right ventricular function ; 3D echocardiography ; myocardial deformation imaging},
    PDF = {https://hal.archives-ouvertes.fr/hal-03544765/file/Moceri_EHJCI_2021.pdf},
    HAL_ID = {hal-03544765},
    HAL_VERSION = {v1},
    
    }
    


  17. 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.
    @article{moceri:hal-03544761,
    TITLE = {{Value of 3D right ventricular function over 2D assessment in acute pulmonary embolism}},
    AUTHOR = {Moceri, Pamela and Duchateau, Nicolas and Sartre, Benjamin and Baudouy, Delphine and Squara, Fabien and Sermesant, Maxime and Ferrari, Emile},
    url-hal= {https://hal.archives-ouvertes.fr/hal-03544761},
    JOURNAL = {{Echocardiography}},
    PUBLISHER = {{Wiley}},
    YEAR = {2021},
    DOI = {10.1111/echo.15167},
    KEYWORDS = {pulmonary embolism ; right ventricular function ; 3D echocardiography ; speckle-tracking},
    PDF = {https://hal.archives-ouvertes.fr/hal-03544761/file/Moceri_ECHO_2021.pdf},
    HAL_ID = {hal-03544761},
    HAL_VERSION = {v1},
    
    }
    


  18. 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.
    @article{montagne:hal-03221227,
    TITLE = {{Challenge of prostate MRI segmentation on T2-weighted images: inter-observer variability and impact of prostate morphology}},
    AUTHOR = {Montagne, Sarah and Hamzaoui, Dimitri 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-03221227},
    JOURNAL = {{Insights into Imaging}},
    PUBLISHER = {{Springer}},
    VOLUME = {12},
    NUMBER = {1},
    YEAR = {2021},
    MONTH = Jun,
    DOI = {10.1186/s13244-021-01010-9},
    KEYWORDS = {Prostate ; MRI ; Segmentation ; Zones ; Atlas},
    PDF = {https://hal.archives-ouvertes.fr/hal-03221227/file/s13244-021-01010-9.pdf},
    HAL_ID = {hal-03221227},
    HAL_VERSION = {v1},
    
    }
    


  19. 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.
    @article{nir:hal-03241929,
    TITLE = {{Association of Immunosuppression and Viral Load With Subcortical Brain Volume in an International Sample of People Living With HIV}},
    AUTHOR = {Nir, Talia M and Fouche, Jean-Paul and Ananworanich, Jintanat and Ances, Beau M and Boban, Jasmina and Brew, Bruce J and Chaganti, Joga R and Chang, Linda and Ching, Christopher R K and Cysique, Lucette A and Ernst, Thomas and Faskowitz, Joshua and Gupta, Vikash and Harezlak, Jaroslaw and Heaps-Woodruff, Jodi M and Hinkin, Charles H and Hoare, Jacqueline and Joska, John A and Kallianpur, Kalpana J and Kuhn, Taylor and Lam, Hei y and Law, Meng and Lebrun-Fr{\'e}nay, Christine and Levine, Andrew J and Mondot, Lydiane and Nakamoto, Beau K and Navia, Bradford A and Pennec, Xavier and Porges, Eric C and Salminen, Lauren E and Shikuma, Cecilia M and Surento, Wesley and Thames, April D and Valcour, Victor and Vassallo, Matteo and Woods, Adam J and Thompson, Paul M and Cohen, Ronald A and Paul, Robert and Stein, Dan J and Jahanshad, Neda},
    url-hal= {https://hal.inria.fr/hal-03241929},
    JOURNAL = {{JAMA Network Open}},
    PUBLISHER = {{American Medical Association}},
    VOLUME = {4},
    NUMBER = {1},
    PAGES = {e2031190},
    YEAR = {2021},
    MONTH = Jan,
    DOI = {10.1001/jamanetworkopen.2020.31190},
    PDF = {https://hal.inria.fr/hal-03241929/file/nir_2021_oi_200975_1610549581.70404%282%29.pdf},
    HAL_ID = {hal-03241929},
    HAL_VERSION = {v1},
    
    }
    


  20. 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.
    @article{sermesant:hal-03171141,
    TITLE = {{Applications of artificial intelligence in cardiovascular imaging}},
    AUTHOR = {Sermesant, Maxime and Delingette, Herv{\'e} and Cochet, Hubert and Ja{\"i}s, Pierre and Ayache, Nicholas},
    url-hal= {https://hal.inria.fr/hal-03171141},
    JOURNAL = {{Nature Reviews Cardiology}},
    PUBLISHER = {{Nature Publishing Group}},
    VOLUME = {18},
    PAGES = {600-609},
    YEAR = {2021},
    MONTH = Mar,
    DOI = {10.1038/s41569-021-00527-2},
    KEYWORDS = {Cardiology ; Machine learning ; Medical imaging},
    HAL_ID = {hal-03171141},
    HAL_VERSION = {v1},
    
    }
    


  21. 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.
    @article{wang:hal-03372777,
    TITLE = {{Bayesian Logistic Shape Model Inference: application to cochlear image segmentation}},
    AUTHOR = {Wang, Zihao and Demarcy, Thomas and Vandersteen, Clair and Gnansia, Dan and Raffaelli, Charles and Guevara, Nicolas and Delingette, Herv{\'e}},
    url-hal= {https://hal.inria.fr/hal-03372777},
    JOURNAL = {{Medical Image Analysis}},
    PUBLISHER = {{Elsevier}},
    VOLUME = {75},
    PAGES = {102268},
    YEAR = {2021},
    MONTH = Oct,
    DOI = {10.1016/j.media.2021.102268},
    KEYWORDS = {Bayesian Inference ; Image Segmentation ; Shape Modeling},
    PDF = {https://hal.inria.fr/hal-03372777/file/2105.02045.pdf},
    HAL_ID = {hal-03372777},
    HAL_VERSION = {v1},
    
    }
    


  22. 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.
    @article{wang:hal-03351225,
    TITLE = {{Inner-ear Augmented Metal Artifact Reduction with Simulation-based 3D Generative Adversarial Networks}},
    AUTHOR = {Wang, Zihao and Vandersteen, Clair and Demarcy, Thomas and Gnansia, Dan and Raffaelli, Charles and Guevara, Nicolas and Delingette, Herv{\'e}},
    url-hal= {https://hal.inria.fr/hal-03351225},
    JOURNAL = {{Computerized Medical Imaging and Graphics}},
    PUBLISHER = {{Elsevier}},
    VOLUME = {93},
    PAGES = {101990},
    YEAR = {2021},
    MONTH = Oct,
    DOI = {10.1016/j.compmedimag.2021.101990},
    KEYWORDS = {Artifact Reduction ; Deep Learning ; GAN},
    PDF = {https://hal.inria.fr/hal-03351225/file/Margan_Clean_Latex%20%281%29.pdf},
    HAL_ID = {hal-03351225},
    HAL_VERSION = {v1},
    
    }
    


  23. 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.
    @article{xu:hal-03219748,
    TITLE = {{Jitter Aware Economic PDN Optimization with a Genetic Algorithm}},
    AUTHOR = {Xu, Zhifei and Wang, Zihao and Sun, Yin and Hwang, Chulsoon and Delingette, Herv{\'e} and Fan, Jun},
    url-hal= {https://hal.archives-ouvertes.fr/hal-03219748},
    NOTE = {Corresponding authors: Zihao Wang; Chulsoon Hwang.},
    JOURNAL = {{IEEE Transactions on Microwave Theory and Techniques}},
    PUBLISHER = {{Institute of Electrical and Electronics Engineers}},
    YEAR = {2021},
    MONTH = Jun,
    DOI = {10.1109/TMTT.2021.3087188},
    KEYWORDS = {PDN ; Jitter ; PSIJ ; Decoupling capacitor ; Genetic algorithm ; Power integrity},
    PDF = {https://hal.archives-ouvertes.fr/hal-03219748/file/IEEE_Journal_Submission_JItter_aware_PDN_study%20%283%29.pdf},
    HAL_ID = {hal-03219748},
    HAL_VERSION = {v1},
    
    }
    


  24. 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.
    @article{zhou:hal-03375000,
    TITLE = {{Deep reinforcement learning in medical imaging: A literature review}},
    AUTHOR = {Zhou, Kevin and Le, Hoang Ngan and Luu, Khoa and van Nguyen, Hien and Ayache, Nicholas},
    url-hal= {https://hal.inria.fr/hal-03375000},
    JOURNAL = {{Medical Image Analysis}},
    PUBLISHER = {{Elsevier}},
    VOLUME = {73},
    PAGES = {102193},
    YEAR = {2021},
    MONTH = Oct,
    DOI = {10.1016/j.media.2021.102193},
    HAL_ID = {hal-03375000},
    HAL_VERSION = {v1},
    
    }
    


  25. 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.
    @incollection{ayache:hal-03374760,
    TITLE = {{Foreword}},
    AUTHOR = {Ayache, Nicholas},
    url-hal= {https://hal.inria.fr/hal-03374760},
    BOOKTITLE = {{Digital Anatomy - Applications of Virtual, Mixed and Augmented Reality}},
    EDITOR = {Jean-Fran{\c c}ois Uhl and Joaquim Jorge and Daniel Simoes Lopes and Pedro F Campos},
    PUBLISHER = {{Springer Nature}},
    SERIES = {Human--Computer Interaction Series},
    YEAR = {2021},
    MONTH = May,
    DOI = {10.1007/978-3-030-61905-3},
    PDF = {https://hal.inria.fr/hal-03374760/file/Foreword%20-%20Digital%20Anatomy.pdf},
    HAL_ID = {hal-03374760},
    HAL_VERSION = {v1},
    
    }
    


  26. 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.
    @incollection{pennec:hal-02925156,
    TITLE = {{Statistical analysis of organs' shapes and deformations: the Riemannian and the affine settings in computational anatomy}},
    AUTHOR = {Pennec, Xavier},
    url-hal= {https://hal.inria.fr/hal-02925156},
    BOOKTITLE = {{Digital Anatomy - Applications of Virtual, Mixed and Augmented Reality}},
    EDITOR = {Jean-Fran{\c c}ois Uhl and Joaquim Jorge and Daniel Simoes Lopes and Pedro F Campos},
    PUBLISHER = {{Springer Nature}},
    SERIES = {Human--Computer Interaction Series},
    YEAR = {2021},
    MONTH = May,
    DOI = {10.1007/978-3-030-61905-3\_9},
    PDF = {https://hal.inria.fr/hal-02925156/file/2020_CompAnat_Pennec.pdf},
    HAL_ID = {hal-02925156},
    HAL_VERSION = {v1},
    
    }
    


Conference articles

  1. 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.
    @inproceedings{audelan:hal-03538729,
    TITLE = {{Validation of lung nodule detection a year before diagnosis in NLST dataset based on a deep learning system}},
    AUTHOR = {Audelan, Beno{\^i}t and St{\'e}phanie, Lopez and Fillard, Pierre and Diascorn, yann and Padovani, Bernard and Delingette, Herv{\'e}},
    url-hal= {https://hal.archives-ouvertes.fr/hal-03538729},
    BOOKTITLE = {{ERS 2021 - European Respiratory Society International Congress}},
    ADDRESS = {Virtual, United Kingdom},
    YEAR = {2021},
    MONTH = Sep,
    DOI = {10.1183/13993003.congress-2021.OA4317},
    HAL_ID = {hal-03538729},
    HAL_VERSION = {v1},
    
    }
    


  2. 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.
    @inproceedings{balelli:hal-03152886,
    TITLE = {{A 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.archives-ouvertes.fr/hal-03152886},
    BOOKTITLE = {{International Conference on Information Processing in Medical Imaging}},
    ADDRESS = {Bornholm, Denmark},
    SERIES = {Information processing in medical imaging: proceedings of the 27th International Conference, IPMI 2021},
    YEAR = {2021},
    MONTH = Jun,
    KEYWORDS = {Federated Learning ; Hierarchical Generative Model ; Heterogeneity},
    PDF = {https://hal.archives-ouvertes.fr/hal-03152886v2/file/Balelli_IPMI2021_CameraReady.pdf},
    HAL_ID = {hal-03152886},
    HAL_VERSION = {v2},
    
    }
    


  3. 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.
    @inproceedings{burgosfernandez:hal-03513023,
    TITLE = {{Automatic classification of multispectral eye fundus images using deep learning}},
    AUTHOR = {Burgos-Fern{\'a}ndez, 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-03513023},
    BOOKTITLE = {{Libro de Res{\'u}menes RNO2021}},
    ADDRESS = {Online, Spain},
    YEAR = {2021},
    MONTH = Nov,
    PDF = {https://hal.inria.fr/hal-03513023/file/RNO2021_FranciscoJBurgos.pdf},
    HAL_ID = {hal-03513023},
    HAL_VERSION = {v1},
    
    }
    


  4. 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.
    @inproceedings{dadoun:hal-03127809,
    TITLE = {{Combining Bayesian and Deep Learning Methods for the Delineation of the Fan in Ultrasound Images}},
    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-03127809},
    BOOKTITLE = {{ISBI 2021 - 18th IEEE International Symposium on Biomedical Imaging}},
    ADDRESS = {Nice, France},
    YEAR = {2021},
    MONTH = Apr,
    DOI = {10.1109/ISBI48211.2021.9434112},
    KEYWORDS = {Ultrasound imaging ; Deep Learning ; Ultrasound fan area detection ; pre-processing},
    PDF = {https://hal.inria.fr/hal-03127809/file/root.pdf},
    HAL_ID = {hal-03127809},
    HAL_VERSION = {v1},
    
    }
    


  5. 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.
    @inproceedings{desrues:hal-03369345,
    TITLE = {{Personal-by-design: a 3D Electromechanical Model of the Heart Tailored for Personalisation}},
    AUTHOR = {Desrues, Ga{\"e}tan and Feuerstein, Delphine and Legay, Thierry and Cazeau, Serge and Sermesant, Maxime},
    url-hal= {https://hal.inria.fr/hal-03369345},
    BOOKTITLE = {{FIMH 2021 - 11th International Conference on Functional Imaging and Modeling of the Heart}},
    ADDRESS = {Stanford, CA, United States},
    YEAR = {2021},
    MONTH = Jun,
    DOI = {10.1007/978-3-030-78710-3\_43},
    KEYWORDS = {Personalisation ; Digital twin ; Cardiac electromechanical model ; Electrophysiology ; Electrocardiogram},
    PDF = {https://hal.inria.fr/hal-03369345/file/fimh_2021.pdf},
    HAL_ID = {hal-03369345},
    HAL_VERSION = {v1},
    
    }
    


  6. 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.
    @inproceedings{difolco:hal-03203378,
    TITLE = {{Investigation of the impact of normalization on the study of interactions between myocardial shape and deformation}},
    AUTHOR = {Di Folco, Maxime and Guigui, Nicolas and Clarysse, Patrick and Moceri, Pamela and Duchateau, Nicolas},
    url-hal= {https://hal.archives-ouvertes.fr/hal-03203378},
    BOOKTITLE = {{FIMH 2021 - 11th International Conference on Functional Imaging and Modeling of the Heart}},
    ADDRESS = {Stanford, United States},
    PUBLISHER = {{Springer}},
    SERIES = {Lectune notes in computer science (LNCS)},
    VOLUME = {12738},
    PAGES = {223--231},
    YEAR = {2021},
    MONTH = Jun,
    DOI = {10.1007/978-3-030-78710-3\_22},
    KEYWORDS = {Cardiac imaging ; manifold learning ; myocardial strain ; heart shape},
    PDF = {https://hal.archives-ouvertes.fr/hal-03203378/file/Difolco_FIMH_2021.pdf},
    HAL_ID = {hal-03203378},
    HAL_VERSION = {v1},
    
    }
    


  7. 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.
    @inproceedings{fraboni:hal-03232421,
    TITLE = {{Clustered Sampling: Low-Variance and Improved Representativity for Clients Selection in Federated Learning}},
    AUTHOR = {Fraboni, Yann and Vidal, Richard and Kameni, Laetitia and Lorenzi, Marco},
    url-hal= {https://hal.archives-ouvertes.fr/hal-03232421},
    BOOKTITLE = {{ICML 2021 - 38th International Conference on Machine Learning}},
    ADDRESS = {online, United States},
    YEAR = {2021},
    MONTH = Jul,
    KEYWORDS = {Client sampling ; federated learning ; sampling variance ; data representativity},
    PDF = {https://hal.archives-ouvertes.fr/hal-03232421/file/ICML_clustered_sampling.pdf},
    HAL_ID = {hal-03232421},
    HAL_VERSION = {v1},
    
    }
    


  8. 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.
    @inproceedings{fraboni:hal-03123638,
    TITLE = {{Free-rider Attacks on Model Aggregation in Federated Learning}},
    AUTHOR = {Fraboni, Yann and Vidal, Richard and Lorenzi, Marco},
    url-hal= {https://hal.archives-ouvertes.fr/hal-03123638},
    BOOKTITLE = {{AISTATS 2021 - 24th International Conference on Artificial Intelligence and Statistics}},
    ADDRESS = {San Diego, United States},
    YEAR = {2021},
    MONTH = Apr,
    PDF = {https://hal.archives-ouvertes.fr/hal-03123638/file/free_riding_AISTATS_vf.pdf},
    HAL_ID = {hal-03123638},
    HAL_VERSION = {v1},
    
    }
    


  9. 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.
    @inproceedings{guigui:hal-03160677,
    TITLE = {{Parallel Transport on Kendall Shape Spaces}},
    AUTHOR = {Guigui, Nicolas and Maignant, Elodie and Trouv{\'e}, Alain and Pennec, Xavier},
    url-hal= {https://hal.inria.fr/hal-03160677},
    BOOKTITLE = {{GSI 2021 - 5th conference on Geometric Science of Information}},
    ADDRESS = {Paris, France},
    PUBLISHER = {{Springer}},
    SERIES = {Lecture Notes in Computer Science},
    VOLUME = {12829},
    PAGES = {103-110},
    YEAR = {2021},
    MONTH = Jul,
    DOI = {10.1007/978-3-030-80209-7\_12},
    PDF = {https://hal.inria.fr/hal-03160677/file/parallel_transport_shape.pdf},
    HAL_ID = {hal-03160677},
    HAL_VERSION = {v1},
    
    }
    


  10. 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.
    @inproceedings{guigui:hal-03142196,
    TITLE = {{Cardiac Motion Modeling with Parallel Transport and Shape Splines}},
    AUTHOR = {Guigui, Nicolas and Moceri, Pamela and Sermesant, Maxime and Pennec, Xavier},
    url-hal= {https://hal.inria.fr/hal-03142196},
    BOOKTITLE = {{ISBI 2021 - 18th IEEE International Symposium on Biomedical Imaging}},
    ADDRESS = {Nice, France},
    PUBLISHER = {{IEEE}},
    SERIES = {IEEE 18th International Symposium on Biomedical Imaging (ISBI), 2021},
    PAGES = {pp. 1394-1397},
    YEAR = {2021},
    MONTH = Apr,
    DOI = {10.1109/ISBI48211.2021.9433887},
    KEYWORDS = {LDDMM ; Cardiac Modelling ; Shape Analysis},
    PDF = {https://hal.inria.fr/hal-03142196/file/root.pdf},
    HAL_ID = {hal-03142196},
    HAL_VERSION = {v1},
    
    }
    


  11. 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.
    @inproceedings{guigui:hal-03154318,
    TITLE = {{A reduced parallel transport equation on Lie Groups with a left-invariant metric}},
    AUTHOR = {Guigui, Nicolas and Pennec, Xavier},
    url-hal= {https://hal.inria.fr/hal-03154318},
    BOOKTITLE = {{GSI 2021 - 5th conference on Geometric Science of Information}},
    ADDRESS = {Paris, France},
    PUBLISHER = {{Springer, Cham}},
    SERIES = {Lecture Notes in Computer Science},
    VOLUME = {12829},
    PAGES = {119-126},
    YEAR = {2021},
    MONTH = Jul,
    DOI = {10.1007/978-3-030-80209-7\_14},
    PDF = {https://hal.inria.fr/hal-03154318v2/file/parallel_transport_lie_group.pdf},
    HAL_ID = {hal-03154318},
    HAL_VERSION = {v2},
    
    }
    


  12. 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.
    @inproceedings{harrison:hal-03375871,
    TITLE = {{Phase-independent Latent Representation for Cardiac Shape Analysis}},
    AUTHOR = {Harrison, Josquin and Lorenzi, Marco and Legghe, Benoit and Iriart, Xavier and Cochet, Hubert and Sermesant, Maxime},
    url-hal= {https://hal.archives-ouvertes.fr/hal-03375871},
    BOOKTITLE = {{MICCAI 2021 - 24th International Conference on Medical Image Computing and Computer Assisted Intervention}},
    ADDRESS = {Strasbourg, France},
    SERIES = {LNCS - Lecture Notes in Computer Science},
    VOLUME = {12906},
    YEAR = {2021},
    MONTH = Sep,
    DOI = {10.1007/978-3-030-87231-1\_52},
    KEYWORDS = {Shape Analysis ; Atrial Fibrillation ; Thrombosis ; Graph Representation ; Latent Space Model ; Multi-Task Learning ; Meta-Learning},
    PDF = {https://hal.archives-ouvertes.fr/hal-03375871/file/paper1929.pdf},
    HAL_ID = {hal-03375871},
    HAL_VERSION = {v1},
    
    }
    


  13. 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.
    @inproceedings{jousse:hal-03500440,
    TITLE = {{Geodesic squared exponential kernel for non-rigid shape registration}},
    AUTHOR = {Jousse, Florent and Pennec, Xavier and Delingette, Herv{\'e} and Gonzalez, Matilde},
    url-hal= {https://hal.inria.fr/hal-03500440},
    BOOKTITLE = {{FG 2021 - IEEE International Conference on Automatic Face and Gesture Recognition}},
    ADDRESS = {JODHPUR, India},
    YEAR = {2021},
    MONTH = Dec,
    DOI = {10.1109/FG52635.2021.9666997},
    PDF = {https://hal.inria.fr/hal-03500440/file/sample_FG2021.pdf},
    HAL_ID = {hal-03500440},
    HAL_VERSION = {v1},
    
    }
    


  14. 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.
    @inproceedings{kashtanova:hal-03369201,
    TITLE = {{EP-Net 2.0: Out-of-Domain Generalisation for Deep Learning Models of Cardiac Electrophysiology}},
    AUTHOR = {Kashtanova, Victoriya and Ayed, Ibrahim and Cedilnik, Nicolas and Gallinari, Patrick and Sermesant, Maxime},
    url-hal= {https://hal.inria.fr/hal-03369201},
    BOOKTITLE = {{FIMH 2021 - 11th International Conference on Functional Imaging and Modeling of the Heart}},
    ADDRESS = {Stanford, CA (virtual), United States},
    PUBLISHER = {{Springer International Publishing}},
    SERIES = {Lecture Notes in Computer Science},
    VOLUME = {12738},
    PAGES = {482-492},
    YEAR = {2021},
    MONTH = Jun,
    DOI = {10.1007/978-3-030-78710-3\_46},
    KEYWORDS = {Electrophysiology ; Deep learning ; Simulation},
    PDF = {https://hal.inria.fr/hal-03369201/file/FIMH_2021_final.pdf},
    HAL_ID = {hal-03369201},
    HAL_VERSION = {v1},
    
    }
    


  15. 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.
    @inproceedings{ly:hal-03378951,
    TITLE = {{Scar-Related Ventricular Arrhythmia Prediction from Imaging Using Explainable Deep Learning}},
    AUTHOR = {Ly, Buntheng and Finsterbach, Sonny and Nu{\~n}ez-Garcia, Marta and Cochet, Hubert and Sermesant, Maxime},
    url-hal= {https://hal.inria.fr/hal-03378951},
    BOOKTITLE = {{FIMH 2021 - 11th International Conference on Functional Imaging and Modeling of the Heart}},
    ADDRESS = {Stanford, United States},
    PUBLISHER = {{Springer International Publishing}},
    SERIES = {Lecture Notes in Computer Science},
    VOLUME = {12738},
    PAGES = {461-470},
    YEAR = {2021},
    MONTH = Jun,
    DOI = {10.1007/978-3-030-78710-3\_44},
    KEYWORDS = {Conditional-VAE ; Sustained Ventricular Arrhythmia ; CTcardiac imaging ; Myocardium thickness ; Image Classification},
    PDF = {https://hal.inria.fr/hal-03378951/file/scar_related_va_pred__fimh2021_buntheng%20%281%29.pdf},
    HAL_ID = {hal-03378951},
    HAL_VERSION = {v1},
    
    }
    


  16. 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.
    @inproceedings{thanwerdas:hal-03157992,
    TITLE = {{Geodesics and Curvature of the Quotient-Affine Metrics on Full-Rank Correlation Matrices}},
    AUTHOR = {Thanwerdas, Yann and Pennec, Xavier},
    url-hal= {https://hal.archives-ouvertes.fr/hal-03157992},
    BOOKTITLE = {{GSI 2021 - 5th conference on Geometric Science of Information}},
    ADDRESS = {Paris, France},
    PUBLISHER = {{Springer, Cham}},
    SERIES = {Proceedings of Geometric Science of Information},
    VOLUME = {12829},
    PAGES = {93-102},
    YEAR = {2021},
    MONTH = Jul,
    DOI = {10.1007/978-3-030-80209-7\_11},
    KEYWORDS = {Correlation matrices ; SPD matrices ; Quotient manifold ; Quotient-affine metric ; Riemannian geometry},
    PDF = {https://hal.archives-ouvertes.fr/hal-03157992v3/file/main.pdf},
    HAL_ID = {hal-03157992},
    HAL_VERSION = {v3},
    
    }
    


  17. 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.
    @inproceedings{tourniaire:hal-03342963,
    TITLE = {{Attention-based Multiple Instance Learning with Mixed Supervision on the Camelyon16 Dataset}},
    AUTHOR = {Tourniaire, Paul and Ilie, Marius and Hofman, Paul and Ayache, Nicholas and Delingette, Herv{\'e}},
    url-hal= {https://hal.archives-ouvertes.fr/hal-03342963},
    BOOKTITLE = {{MICCAI 2021 - Workshop on Computational Pathology}},
    ADDRESS = {Strasbourg, France},
    PUBLISHER = {{PMLR}},
    SERIES = {Proceedings of Machine Learning Research},
    VOLUME = {156},
    PAGES = {216-226},
    YEAR = {2021},
    MONTH = Sep,
    KEYWORDS = {Attention Mechanism ; Mixed Supervision ; Histopathology},
    PDF = {https://hal.archives-ouvertes.fr/hal-03342963/file/Compay_hal.pdf},
    HAL_ID = {hal-03342963},
    HAL_VERSION = {v1},
    
    }
    


  18. 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.
    @inproceedings{wang:hal-03024759,
    TITLE = {{One-shot Learning Landmarks Detection}},
    AUTHOR = {Wang, Zihao and Vandersteen, Clair and Raffaelli, Charles and Guevara, Nicolas and Patou, Fran{\c c}ois and Delingette, Herv{\'e}},
    url-hal= {https://hal.inria.fr/hal-03024759},
    BOOKTITLE = {{MICCAI 2021 - Workshop on Data Augmentation, Labeling, and Imperfections}},
    ADDRESS = {strasbourg, France},
    PUBLISHER = {{Springer}},
    SERIES = {Lecture Notes in Computer Science (LNCS)},
    VOLUME = {13003},
    PAGES = {163-172},
    YEAR = {2021},
    MONTH = Oct,
    DOI = {10.1007/978-3-030-88210-5\_15},
    PDF = {https://hal.inria.fr/hal-03024759v2/file/Camera_Ready__MICCAI2021_Workshop_Landmarks_Detection.pdf},
    HAL_ID = {hal-03024759},
    HAL_VERSION = {v2},
    
    }
    


  19. 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.
    @inproceedings{yang:hal-03371358,
    TITLE = {{Shape Constraints in Deep Learning for Robust 2D Echocardiography Analysis}},
    AUTHOR = {yang, yingyu and Sermesant, Maxime},
    url-hal= {https://hal.archives-ouvertes.fr/hal-03371358},
    BOOKTITLE = {{FIMH 2021 - 11th International Conference on Functional Imaging and Modeling of the Heart}},
    ADDRESS = {Stanford, United States},
    YEAR = {2021},
    MONTH = Jun,
    DOI = {10.1007/978-3-030-78710-3\_3},
    KEYWORDS = {Segmentation ; Deep Learning ; Deformation ; Echocardiography},
    PDF = {https://hal.archives-ouvertes.fr/hal-03371358/file/FIMH_2021_YingyuYANG.pdf},
    HAL_ID = {hal-03371358},
    HAL_VERSION = {v1},
    
    }
    


Patents, standards

  1. Julian Krebs, Hiroshi Ashikaga, Tommaso Mansi, Bin Lou, Katherine Chih-Ching Wu, and Henry Halperin. Risk prediction for sudden cardiac death from image derived cardiac motion and structure features. US20210059612A1, United States, March 2021.
    @patent{krebs:hal-03198828,
    TITLE = {{Risk prediction for sudden cardiac death from image derived cardiac motion and structure features}},
    AUTHOR = {Krebs, Julian and Ashikaga, Hiroshi and Mansi, Tommaso and Lou, Bin and Chih-Ching Wu, Katherine and Halperin, Henry},
    url-hal= {https://hal.archives-ouvertes.fr/hal-03198828},
    NUMBER = {US20210059612A1},
    ADDRESS = {United States},
    YEAR = {2021},
    MONTH = Mar,
    HAL_ID = {hal-03198828},
    HAL_VERSION = {v1},
    
    }
    


  2. Julian Krebs, Tommaso Mansi, and Bin Lou. Patient specific risk prediction of cardiac events from image-derived cardiac function features. US20210057104A1, United States, February 2021.
    @patent{krebs:hal-03198820,
    TITLE = {{Patient specific risk prediction of cardiac events from image-derived cardiac function features}},
    AUTHOR = {Krebs, Julian and Mansi, Tommaso and Lou, Bin},
    url-hal= {https://hal.archives-ouvertes.fr/hal-03198820},
    NUMBER = {US20210057104A1},
    ADDRESS = {United States},
    YEAR = {2021},
    MONTH = Feb,
    HAL_ID = {hal-03198820},
    HAL_VERSION = {v1},
    
    }
    


Miscellaneous

  1. Anna Calissano, Aasa Feragen, and Simone Vantini. Graph-Valued Models for Dimensionality Reduction and Regression. JSM 2021 - Joint Statistical Meeting, August 2021.
    @misc{calissano:hal-03518747,
    TITLE = {{Graph-Valued Models for Dimensionality Reduction and Regression}},
    AUTHOR = {Calissano, Anna and Feragen, Aasa and Vantini, Simone},
    url-hal= {https://hal.inria.fr/hal-03518747},
    HOWPUBLISHED = {{JSM 2021 - Joint Statistical Meeting}},
    YEAR = {2021},
    MONTH = Aug,
    PDF = {https://hal.inria.fr/hal-03518747/file/JSM_Calissano.pdf},
    HAL_ID = {hal-03518747},
    HAL_VERSION = {v1},
    
    }
    


  2. Luigi Antelmi, Nicholas Ayache, Philippe Robert, Federica Ribaldi, Valentina Garibotto, Giovanni B Frisoni, and Marco Lorenzi. Combining Multi-Task Learning and Multi-Channel Variational Auto-Encoders to Exploit Datasets with Missing Observations -Application to Multi-Modal Neuroimaging Studies in Dementia. Note: Working paper or preprint, May 2021. Keyword(s): Multi Task Learning, Missing Data, Variational Autoencoders, Multimodal Data Analysis, OPAL-Meso.
    @unpublished{antelmi:hal-03114888,
    TITLE = {{Combining Multi-Task Learning and Multi-Channel Variational Auto-Encoders to Exploit Datasets with Missing Observations -Application to Multi-Modal Neuroimaging Studies in Dementia}},
    AUTHOR = {Antelmi, Luigi and Ayache, Nicholas and Robert, Philippe and Ribaldi, Federica and Garibotto, Valentina and Frisoni, Giovanni B and Lorenzi, Marco},
    url-hal= {https://hal.inria.fr/hal-03114888},
    NOTE = {working paper or preprint},
    YEAR = {2021},
    MONTH = May,
    KEYWORDS = {Multi Task Learning ; Missing Data ; Variational Autoencoders ; Multimodal Data Analysis ; OPAL-Meso},
    PDF = {https://hal.inria.fr/hal-03114888v2/file/elsarticle-template-harv.pdf},
    HAL_ID = {hal-03114888},
    HAL_VERSION = {v2},
    
    }
    


  3. 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, September 2021. 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.archives-ouvertes.fr/hal-03335826},
    NOTE = {working paper or preprint},
    YEAR = {2021},
    MONTH = Sep,
    KEYWORDS = {Dynamic population models ; Ordinary differential equations ; Optimal control theory ; Clinical trial analysis},
    PDF = {https://hal.archives-ouvertes.fr/hal-03335826/file/Manuscript_JSPI.pdf},
    HAL_ID = {hal-03335826},
    HAL_VERSION = {v1},
    
    }
    


  4. Nina Miolane, Matteo Caorsi, Umberto Lupo, Marius Guerard, Nicolas Guigui, Johan Mathe, Yann Cabanes, Wojciech Reise, Thomas Davies, António Leitão, Somesh Mohapatra, Saiteja Utpala, Shailja Shailja, Gabriele Corso, Guoxi Liu, Federico Iuricich, Andrei Manolache, Mihaela Nistor, Matei Bejan, Armand Mihai Nicolicioiu, Bogdan-Alexandru Luchian, Mihai-Sorin Stupariu, Florent Michel, Khanh Dao Duc, Bilal Abdulrahman, Maxim Beketov, Elodie Maignant, Zhiyuan Liu, Marek Cerny, Martin Bauw, Santiago Velasco-Forero, Jesus Angulo, and Yanan Long. ICLR 2021 Challenge for Computational Geometry & Topology: Design and Results. Note: Working paper or preprint, December 2021.
    @unpublished{miolane:hal-03505132,
    TITLE = {{ICLR 2021 Challenge for Computational Geometry \& Topology: Design and Results}},
    AUTHOR = {Miolane, Nina and Caorsi, Matteo and Lupo, Umberto and Guerard, Marius and Guigui, Nicolas and Mathe, Johan and Cabanes, Yann and Reise, Wojciech and Davies, Thomas and Leit{\~a}o, Ant{\'o}nio and Mohapatra, Somesh and Utpala, Saiteja and Shailja, Shailja and Corso, Gabriele and Liu, Guoxi and Iuricich, Federico and Manolache, Andrei and Nistor, Mihaela and Bejan, Matei and Nicolicioiu, Armand Mihai and Luchian, Bogdan-Alexandru and Stupariu, Mihai-Sorin and Michel, Florent and Duc, Khanh Dao and Abdulrahman, Bilal and Beketov, Maxim and Maignant, Elodie and Liu, Zhiyuan and {\v C}ern{\'y}, Marek and Bauw, Martin and Velasco-Forero, Santiago and Angulo, Jesus and Long, Yanan},
    url-hal= {https://hal.inria.fr/hal-03505132},
    NOTE = {working paper or preprint},
    YEAR = {2021},
    MONTH = Dec,
    HAL_ID = {hal-03505132},
    HAL_VERSION = {v1},
    
    }
    


  5. Talia Nir, Jean-Paul Fouche, Jintanat Ananworanich, Beau Ances, Jasmina Boban, Bruce Brew, Linda Chang, Joga Chaganti, Christopher R.K. Ching, Lucette Cysique, Thomas Ernst, Joshua Faskowitz, Vikash Gupta, Jaroslaw Harezlak, Jodi Heaps-Woodruff, Charles Hinkin, Jacqueline Hoare, John Joska, Kalpana Kallianpur, Taylor Kuhn, Hei Lam, Meng Law, Christine Lebrun-Frenay, Andrew Levine, Lydiane Mondot, Beau Nakamoto, Bradford Navia, Xavier Pennec, Eric Porges, Cecilia Shikuma, April Thames, Victor Valcour, Matteo Vassallo, Adam Woods, Paul Thompson, Ronald Cohen, Robert Paul, Dan Stein, and Neda Jahanshad. Smaller limbic structures are associated with greater immunosuppression in over 1000 HIV-infected adults across five continents: Findings from the ENIGMA-HIV Working Group. Note: Working paper or preprint, January 2021.
    @unpublished{nir:hal-03063822,
    TITLE = {{Smaller limbic structures are associated with greater immunosuppression in over 1000 HIV-infected adults across five continents: Findings from the ENIGMA-HIV Working Group}},
    AUTHOR = {Nir, Talia and Fouche, Jean-Paul and Ananworanich, Jintanat and Ances, Beau and Boban, Jasmina and Brew, Bruce and Chang, Linda and Chaganti, Joga and Ching, Christopher R.K. and Cysique, Lucette and Ernst, Thomas and Faskowitz, Joshua and Gupta, Vikash and Harezlak, Jaroslaw and Heaps-Woodruff, Jodi and Hinkin, Charles and Hoare, Jacqueline and Joska, John and Kallianpur, Kalpana and Kuhn, Taylor and Lam, Hei and Law, Meng and Lebrun-Frenay, Christine and Levine, Andrew and Mondot, Lydiane and Nakamoto, Beau and Navia, Bradford and Pennec, Xavier and Porges, Eric and Shikuma, Cecilia and Thames, April and Valcour, Victor and Vassallo, Matteo and Woods, Adam and Thompson, Paul and Cohen, Ronald and Paul, Robert and Stein, Dan and Jahanshad, Neda},
    url-hal= {https://hal.inria.fr/hal-03063822},
    NOTE = {working paper or preprint},
    YEAR = {2021},
    MONTH = Jan,
    DOI = {10.1101/724583},
    PDF = {https://hal.inria.fr/hal-03063822/file/724583v1.full.pdf},
    HAL_ID = {hal-03063822},
    HAL_VERSION = {v1},
    
    }
    


  6. Yann Thanwerdas and Xavier Pennec. O(n)-invariant Riemannian metrics on SPD matrices. Note: Working paper or preprint, September 2021. Keyword(s): Log-Euclidean metric, Affine-invariant metric, Bures-Wasserstein metric, Kernel metrics, 58D17, 53C22, 15A63, 53B20, Symmetric Positive Definite matrices, Riemannian geometry, Invariance under orthogonal transformations, Families of metrics.
    @unpublished{thanwerdas:hal-03338601,
    TITLE = {{O(n)-invariant Riemannian metrics on SPD matrices}},
    AUTHOR = {Thanwerdas, Yann and Pennec, Xavier},
    url-hal= {https://hal.archives-ouvertes.fr/hal-03338601},
    NOTE = {working paper or preprint},
    YEAR = {2021},
    MONTH = Sep,
    KEYWORDS = {Log-Euclidean metric ; Affine-invariant metric ; Bures-Wasserstein metric ; Kernel metrics ; 58D17 ; 53C22 ; 15A63 ; 53B20 ; Symmetric Positive Definite matrices ; Riemannian geometry ; Invariance under orthogonal transformations ; Families of metrics},
    PDF = {https://hal.archives-ouvertes.fr/hal-03338601v2/file/main.pdf},
    HAL_ID = {hal-03338601},
    HAL_VERSION = {v2},
    
    }
    


  7. Zihao Wang and Hervé Delingette. Attention for Image Registration (AiR): an unsupervised Transformer approach. Note: Working paper or preprint, May 2021. Keyword(s): Transformer, Images Registration, Deep Learning.
    @unpublished{wang:hal-03202230,
    TITLE = {{Attention for Image Registration (AiR): an unsupervised Transformer approach}},
    AUTHOR = {Wang, Zihao and Delingette, Herv{\'e}},
    url-hal= {https://hal.inria.fr/hal-03202230},
    NOTE = {working paper or preprint},
    YEAR = {2021},
    MONTH = May,
    KEYWORDS = {Transformer ; Images Registration ; Deep Learning},
    PDF = {https://hal.inria.fr/hal-03202230v3/file/DRAFT__Attention_for_Image_Registration__A_Transformer%20%283%29.pdf},
    HAL_ID = {hal-03202230},
    HAL_VERSION = {v3},
    
    }
    


  8. Zihao Wang and Hervé Delingette. Quasi-Symplectic Langevin Variational Autoencoder. Note: Working paper or preprint, June 2021.
    @unpublished{wang:hal-03024748,
    TITLE = {{Quasi-Symplectic Langevin Variational Autoencoder}},
    AUTHOR = {Wang, Zihao and Delingette, Herv{\'e}},
    url-hal= {https://hal.inria.fr/hal-03024748},
    NOTE = {working paper or preprint},
    YEAR = {2021},
    MONTH = Jun,
    PDF = {https://hal.inria.fr/hal-03024748v4/file/V2_Langevin_VAE_Revision__Copy_.pdf},
    HAL_ID = {hal-03024748},
    HAL_VERSION = {v4},
    
    }
    



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