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Publications of year 2019

Books and proceedings

  1. Dajiang Zhu, Jingwen Yan, Stanley Durrleman, Stefan Sommer, Heng Huang, Li Shen, Paul M. Thompson, Carl-Fredrik Westin, Xavier Pennec, Sarang Joshi, Mads Nielsen, and Tom Fletcher, editors. Multimodal Brain Image Analysis and Mathematical Foundations of Computational Anatomy, volume 11846 of Lecture Notes in Computer Science (LNCS), October 2019. Springer. Keyword(s): Biomedical imaging, Artificial intelligence, Approximation methods, Statistics of surfaces, Statistical models, Principal component analysis, Neural networks, Machine learning, Imaging genetics, Image segmentation, Image registration, Image reconstruction, Image processing, Computational anatomy, Image fusion.
    @proceedings{zhu:hal-02341877,
    TITLE = {{Multimodal Brain Image Analysis and Mathematical Foundations of Computational Anatomy}},
    AUTHOR = {Zhu, Dajiang and Yan, Jingwen and Huang, Heng and Shen, Li and Thompson, Paul M. and Westin, Carl-Fredrik and Pennec, Xavier and Joshi, Sarang and Nielsen, Mads and Fletcher, Tom and Durrleman, Stanley and Sommer, Stefan},
    url-hal= {https://hal.inria.fr/hal-02341877},
    EDITOR = {Zhu, Dajiang and Yan, Jingwen and Durrleman, Stanley and Sommer, Stefan and Huang, Heng and Shen, Li and Thompson, Paul M. and Westin, Carl-Fredrik and Pennec, Xavier and Joshi, Sarang and Nielsen, Mads and Fletcher, Tom},
    PUBLISHER = {{Springer}},
    SERIES = {Lecture Notes in Computer Science (LNCS)},
    VOLUME = {11846},
    YEAR = {2019},
    MONTH = Oct,
    DOI = {10.1007/978-3-030-33226-6},
    KEYWORDS = {Biomedical imaging ; Artificial intelligence ; Approximation methods ; Statistics of surfaces ; Statistical models ; Principal component analysis ; Neural networks ; Machine learning ; Imaging genetics ; Image segmentation ; Image registration ; Image reconstruction ; Image processing ; Computational anatomy ; Image fusion},
    HAL_ID = {hal-02341877},
    HAL_VERSION = {v1},
    
    }
    


Thesis

  1. Shuman Jia. Population-Based Models of Shape, Structure, and Deformation in Atrial Fibrillation. Theses, Université Côte d'Azur, December 2019. Keyword(s): cardiac image analysis, atrial fibrillation, segmentation, fat, statistical shape analysis, parallel transport, analyse d'images cardiaques, fibrillation auriculaire, segmentation, graisse, analyse statistique des formes, transport parallèle.
    @phdthesis{jia:tel-02428638,
    TITLE = {{Population-Based Models of Shape, Structure, and Deformation in Atrial Fibrillation}},
    AUTHOR = {Jia, Shuman},
    url-hal= {https://hal.inria.fr/tel-02428638},
    SCHOOL = {{Universit{\'e} C{\^o}te d'Azur}},
    YEAR = {2019},
    MONTH = Dec,
    KEYWORDS = {cardiac image analysis ; atrial fibrillation ; segmentation ; fat ; statistical shape analysis ; parallel transport ; analyse d'images cardiaques ; fibrillation auriculaire ; segmentation ; graisse ; analyse statistique des formes ; transport parall{\`e}le},
    TYPE = {Theses},
    PDF = {https://hal.inria.fr/tel-02428638/file/PhD_Thesis___Shuman___2019%281%29.pdf},
    HAL_ID = {tel-02428638},
    HAL_VERSION = {v1},
    
    }
    


  2. Pawel Mlynarski. Deep learning for segmentation of brain tumors and organs at risk in radiotherapy planning. Theses, COMUE Université Côte d'Azur (2015 - 2019), November 2019. Keyword(s): Convolutional Neural Networks, Semi-supervised learning, MRI, Radiotherapy, Brain tumor, Organs at risk, Réseau neuronal convolutif, Apprentissage semi-supervisé, IRM, Radiothérapie, Tumeur cérébrale, Organes à risque.
    @phdthesis{mlynarski:tel-02358374,
    TITLE = {{Deep learning for segmentation of brain tumors and organs at risk in radiotherapy planning}},
    AUTHOR = {Mlynarski, Pawel},
    url-hal= {https://hal.inria.fr/tel-02358374},
    NUMBER = {2019AZUR4084},
    SCHOOL = {{COMUE Universit{\'e} C{\^o}te d'Azur (2015 - 2019)}},
    YEAR = {2019},
    MONTH = Nov,
    KEYWORDS = {Convolutional Neural Networks ; Semi-supervised learning ; MRI ; Radiotherapy ; Brain tumor ; Organs at risk ; R{\'e}seau neuronal convolutif ; Apprentissage semi-supervis{\'e} ; IRM ; Radioth{\'e}rapie ; Tumeur c{\'e}r{\'e}brale ; Organes {\`a} risque},
    TYPE = {Theses},
    PDF = {https://hal.inria.fr/tel-02358374/file/2019AZUR4084.pdf},
    HAL_ID = {tel-02358374},
    HAL_VERSION = {v2},
    
    }
    


  3. Raphaël Sivera. Modeling and measuring the brain morphological evolution using structural MRI in the context of neurodegenerative diseases. Theses, COMUE Université Côte d'Azur (2015 - 2019), November 2019. Keyword(s): Morphometry, Aging, Alzheimer's disease, MRI, Longitudinal models, Multivariate statistical analysis, Morphométrie, Vieillissement, Maladie d'Alzheimer, IRM, Modèles longitudinaux, Statistiques multivariées.
    @phdthesis{sivera:tel-02389924,
    TITLE = {{Modeling and measuring the brain morphological evolution using structural MRI in the context of neurodegenerative diseases}},
    AUTHOR = {Sivera, Raphaël},
    url-hal= {https://tel.archives-ouvertes.fr/tel-02389924},
    NUMBER = {2019AZUR4082},
    SCHOOL = {{COMUE Universit{\'e} C{\^o}te d'Azur (2015 - 2019)}},
    YEAR = {2019},
    MONTH = Nov,
    KEYWORDS = {Morphometry ; Aging ; Alzheimer's disease ; MRI ; Longitudinal models ; Multivariate statistical analysis ; Morphom{\'e}trie ; Vieillissement ; Maladie d'Alzheimer ; IRM ; Mod{\`e}les longitudinaux ; Statistiques multivari{\'e}es},
    TYPE = {Theses},
    PDF = {https://tel.archives-ouvertes.fr/tel-02389924/file/2019AZUR4082.pdf},
    HAL_ID = {tel-02389924},
    HAL_VERSION = {v2},
    
    }
    


  4. Qiao Zheng. Deep learning for robust segmentation and explainable analysis of 3d and dynamic cardiac images. Theses, COMUE Université Côte d'Azur (2015 - 2019), March 2019. Keyword(s): Deep learning, Cardiac segmentation, Cardiac analysis, Cine MRI, Apprentissage profond, Segmentation cardiaque, Analyse cardiaque, Ciné-IRM.
    @phdthesis{zheng:tel-02083415,
    TITLE = {{Deep learning for robust segmentation and explainable analysis of 3d and dynamic cardiac images}},
    AUTHOR = {Zheng, Qiao},
    url-hal= {https://tel.archives-ouvertes.fr/tel-02083415},
    NUMBER = {2019AZUR4013},
    SCHOOL = {{COMUE Universit{\'e} C{\^o}te d'Azur (2015 - 2019)}},
    YEAR = {2019},
    MONTH = Mar,
    KEYWORDS = {Deep learning ; Cardiac segmentation ; Cardiac analysis ; Cine MRI ; Apprentissage profond ; Segmentation cardiaque ; Analyse cardiaque ; Cin{\'e}-IRM},
    TYPE = {Theses},
    PDF = {https://tel.archives-ouvertes.fr/tel-02083415/file/2019AZUR4013.pdf},
    HAL_ID = {tel-02083415},
    HAL_VERSION = {v2},
    
    }
    


Articles in journal, book chapters

  1. Clement Abi Nader, Nicholas Ayache, Philippe Robert, and Marco Lorenzi. Monotonic Gaussian Process for Spatio-Temporal Disease Progression Modeling in Brain Imaging Data. NeuroImage, 2019. Keyword(s): Gaussian Process, Disease progression modeling, Alzheimer's disease, Bayesian modeling, Stochastic variational inference, Clinical trials.
    @article{abinader:hal-02051843,
    TITLE = {{Monotonic Gaussian Process for Spatio-Temporal Disease Progression Modeling in Brain Imaging Data}},
    AUTHOR = {Abi Nader, Clement and Ayache, Nicholas and Robert, Philippe and Lorenzi, Marco},
    url-hal= {https://hal.archives-ouvertes.fr/hal-02051843},
    JOURNAL = {{NeuroImage}},
    PUBLISHER = {{Elsevier}},
    YEAR = {2019},
    KEYWORDS = {Gaussian Process ; Disease progression modeling ; Alzheimer's disease ; Bayesian modeling ; Stochastic variational inference ; Clinical trials},
    PDF = {https://hal.archives-ouvertes.fr/hal-02051843/file/revised_manuscript.pdf},
    HAL_ID = {hal-02051843},
    HAL_VERSION = {v3},
    
    }
    


  2. Luigi Antelmi, Nicholas Ayache, Philippe Robert, and Marco Lorenzi. Sparse Multi-Channel Variational Autoencoder for the Joint Analysis of Heterogeneous Data. Proceedings of Machine Learning Research, (97):302-311, 2019.
    @article{antelmi:hal-02395747,
    TITLE = {{Sparse Multi-Channel Variational Autoencoder for the Joint Analysis of Heterogeneous Data}},
    AUTHOR = {Antelmi, Luigi and Ayache, Nicholas and Robert, Philippe and Lorenzi, Marco},
    url-hal= {https://hal.inria.fr/hal-02395747},
    JOURNAL = {{Proceedings of Machine Learning Research}},
    PUBLISHER = {{PMLR}},
    SERIES = {Proceedings of ICML 2019},
    NUMBER = {97},
    PAGES = {302--311},
    YEAR = {2019},
    PDF = {https://hal.inria.fr/hal-02395747/file/antelmi19.pdf},
    HAL_ID = {hal-02395747},
    HAL_VERSION = {v1},
    
    }
    


  3. Nicholas Ayache and Sara Colantonio. The Digital Health Revolution - Introduction to the Special Theme. ERCIM News, (118):4-5, July 2019.
    @article{ayache:hal-02404520,
    TITLE = {{The Digital Health Revolution - Introduction to the Special Theme}},
    AUTHOR = {Ayache, Nicholas and Colantonio, Sara},
    url-hal= {https://hal.inria.fr/hal-02404520},
    JOURNAL = {{ERCIM News}},
    PUBLISHER = {{ERCIM}},
    NUMBER = {118},
    PAGES = {4-5},
    YEAR = {2019},
    MONTH = Jul,
    HAL_ID = {hal-02404520},
    HAL_VERSION = {v1},
    
    }
    


  4. Laurent Bergé, Charles Bouveyron, Marco Corneli, and Pierre Latouche. The Latent Topic Block Model for the Co-Clustering of Textual Interaction Data. Computational Statistics and Data Analysis, 137:247-270, 2019.
    @article{berge:hal-01835074,
    TITLE = {{The Latent Topic Block Model for the Co-Clustering of Textual Interaction Data}},
    AUTHOR = {Berg{\'e}, Laurent and Bouveyron, Charles and Corneli, Marco and Latouche, Pierre},
    url-hal= {https://hal.archives-ouvertes.fr/hal-01835074},
    JOURNAL = {{Computational Statistics and Data Analysis}},
    PUBLISHER = {{Elsevier}},
    VOLUME = {137},
    PAGES = {247-270},
    YEAR = {2019},
    PDF = {https://hal.archives-ouvertes.fr/hal-01835074/file/LTBMpaper.pdf},
    HAL_ID = {hal-01835074},
    HAL_VERSION = {v1},
    
    }
    


  5. Paloma Compes, Emeline Tabouret, Amandine Etcheverry, Carole Colin, Romain Appay, Nicolas Cordier, Jean Mosser, Olivier Chinot, Hervé Delingette, Nadine Girard, Henry Dufour, Philippe Metellus, and Dominique Figarella-Branger. Neuro-radiological characteristics of adult diffuse grade II and III insular gliomas classified according to WHO 2016. Journal of Neuro-Oncology, 142(3):511-520, 2019. Keyword(s): Molecular, Neuro-radiology, Insula, Glioma, Perfusion.
    @article{compes:hal-02076599,
    TITLE = {{Neuro-radiological characteristics of adult diffuse grade II and III insular gliomas classified according to WHO 2016}},
    AUTHOR = {Compes, Paloma and Tabouret, Emeline and Etcheverry, Amandine and Colin, Carole and Appay, Romain and Cordier, Nicolas and Mosser, Jean and Chinot, Olivier and Delingette, Herv{\'e} and Girard, Nadine and Dufour, Henry and Metellus, Philippe and Figarella-Branger, Dominique},
    url-hal= {https://hal-univ-rennes1.archives-ouvertes.fr/hal-02076599},
    JOURNAL = {{Journal of Neuro-Oncology}},
    PUBLISHER = {{Springer Verlag}},
    VOLUME = {142},
    NUMBER = {3},
    PAGES = {511-520},
    YEAR = {2019},
    DOI = {10.1007/s11060-019-03122-1},
    KEYWORDS = {Molecular ; Neuro-radiology ; Insula ; Glioma ; Perfusion},
    HAL_ID = {hal-02076599},
    HAL_VERSION = {v1},
    
    }
    


  6. Claire Cury, Stanley Durrleman, David Cash, Marco Lorenzi, Jennifer M Nicholas, Martina Bocchetta, John C. Van Swieten, Barbara Borroni, Daniela Galimberti, Mario Masellis, Maria Carmela Tartaglia, James Rowe, Caroline Graff, Fabrizio Tagliavini, Giovanni B. Frisoni, Robert Laforce, Elizabeth Finger, Alexandre de Mendonça, Sandro Sorbi, Sébastien Ourselin, Jonathan Rohrer, Marc Modat, Christin Andersson, Silvana Archetti, Andrea Arighi, Luisa Benussi, Sandra Black, Maura Cosseddu, Marie Fallstrm, Carlos G. Ferreira, Chiara Fenoglio, Nick Fox, Morris Freedman, Giorgio Fumagalli, Stefano Gazzina, Robert Ghidoni, Marina Grisoli, Vesna Jelic, Lize Jiskoot, Ron Keren, Gemma Lombardi, Carolina Maruta, Lieke Meeter, Rick van Minkelen, Benedetta Nacmias, Linn Ijerstedt, Alessandro Padovani, Jessica Panman, Michela Pievani, Cristina Polito, Enrico Premi, Sara Prioni, Rosa Rademakers, Veronica Redaelli, Ekaterina Rogaeva, Giacomina Rossi, Martin Rossor, Elio Scarpini, David Tang-Wai, Hakan Thonberg, Pietro Tiraboschi, Ana Verdelho, and Jason Warren. Spatiotemporal analysis for detection of pre-symptomatic shape changes in neurodegenerative diseases: Initial application to the GENFI cohort. NeuroImage, 188:282-290, March 2019. Keyword(s): Spatiotemporal geodesic regression, Parallel transport, Shape analysis, Clustering, Computational anatomy, Thalamus.
    @article{cury:inserm-01958916,
    TITLE = {{Spatiotemporal analysis for detection of pre-symptomatic shape changes in neurodegenerative diseases: Initial application to the GENFI cohort}},
    AUTHOR = {Cury, Claire and Durrleman, Stanley and Cash, David and Lorenzi, Marco and Nicholas, Jennifer M and Bocchetta, Martina and Van Swieten, John C. and Borroni, Barbara and Galimberti, Daniela and Masellis, Mario and Tartaglia, Maria Carmela and Rowe, James and Graff, Caroline and Tagliavini, Fabrizio and Frisoni, Giovanni B. and Laforce, Robert and Finger, Elizabeth and de Mendon{\c c}a, Alexandre and Sorbi, Sandro and Ourselin, S{\'e}bastien and Rohrer, Jonathan and Modat, Marc and Andersson, Christin and Archetti, Silvana and Arighi, Andrea and Benussi, Luisa and Black, Sandra and Cosseddu, Maura and Fallstrm, Marie and Ferreira, Carlos G. and Fenoglio, Chiara and Fox, Nick and Freedman, Morris and Fumagalli, Giorgio and Gazzina, Stefano and Ghidoni, Robert and Grisoli, Marina and Jelic, Vesna and Jiskoot, Lize and Keren, Ron and Lombardi, Gemma and Maruta, Carolina and Meeter, Lieke and van Minkelen, Rick and Nacmias, Benedetta and Ijerstedt, Linn and Padovani, Alessandro and Panman, Jessica and Pievani, Michela and Polito, Cristina and Premi, Enrico and Prioni, Sara and Rademakers, Rosa and Redaelli, Veronica and Rogaeva, Ekaterina and Rossi, Giacomina and Rossor, Martin and Scarpini, Elio and Tang-Wai, David and Thonberg, Hakan and Tiraboschi, Pietro and Verdelho, Ana and Warren, Jason},
    url-hal= {https://www.hal.inserm.fr/inserm-01958916},
    JOURNAL = {{NeuroImage}},
    PUBLISHER = {{Elsevier}},
    VOLUME = {188},
    PAGES = {282-290},
    YEAR = {2019},
    MONTH = Mar,
    DOI = {10.1016/j.neuroimage.2018.11.063},
    KEYWORDS = {Spatiotemporal geodesic regression ; Parallel transport ; Shape analysis ; Clustering ; Computational anatomy ; Thalamus},
    PDF = {https://www.hal.inserm.fr/inserm-01958916/file/Spatio_temporal_analysis_GENFI_lastSub_black.pdf},
    HAL_ID = {inserm-01958916},
    HAL_VERSION = {v1},
    
    }
    


  7. Thomas Demarcy, Isabelle Pélisson, Dan Gnansia, Hervé Delingette, Nicholas Ayache, Charles Raffaelli, Clair Vandersteen, and Nicolas Guevara. Un modèle de reconstruction tridimensionnelle de la cochlée au service de l'implantation cochléaire. Les cahiers de l'audition, 32(4):36-40, July 2019.
    @article{demarcy:hal-02270604,
    TITLE = {{Un mod{\`e}le de reconstruction tridimensionnelle de la cochl{\'e}e au service de l'implantation cochl{\'e}aire}},
    AUTHOR = {Demarcy, Thomas and P{\'e}lisson, Isabelle and Gnansia, Dan and Delingette, Herv{\'e} and Ayache, Nicholas and Raffaelli, Charles and Vandersteen, Clair and Guevara, Nicolas},
    url-hal= {https://hal.inria.fr/hal-02270604},
    JOURNAL = {{Les cahiers de l'audition}},
    PUBLISHER = {{Elsevier}},
    VOLUME = {32},
    NUMBER = {4},
    PAGES = {36-40},
    YEAR = {2019},
    MONTH = Jul,
    HAL_ID = {hal-02270604},
    HAL_VERSION = {v1},
    
    }
    


  8. Rubén Doste, David Soto-Iglesias, Gabriel Bernardino, Alejandro Alcaine, Rafael Sebastian, Sophie Giffard-Roisin, Maxime Sermesant, Antonio Berruezo, Damian Sanchez-Quintana, and Oscar Camara. A rule-based method to model myocardial fiber orientation in cardiac biventricular geometries with outflow tracts. International Journal for Numerical Methods in Biomedical Engineering, 35(4), March 2019. Keyword(s): Rule-based method, Fiber orientation, Outflow tract, Septum, Electrophysiological simulations, Outflow tract ventricular arrhythmia.
    @article{doste:hal-02128531,
    TITLE = {{A rule-based method to model myocardial fiber orientation in cardiac biventricular geometries with outflow tracts}},
    AUTHOR = {Doste, Rub{\'e}n and Soto-Iglesias, David and Bernardino, Gabriel and Alcaine, Alejandro and Sebastian, Rafael and Giffard-Roisin, Sophie and Sermesant, Maxime and Berruezo, Antonio and Sanchez-Quintana, Damian and Camara, Oscar},
    url-hal= {https://hal.inria.fr/hal-02128531},
    JOURNAL = {{International Journal for Numerical Methods in Biomedical Engineering}},
    PUBLISHER = {{John Wiley and Sons}},
    SERIES = {International Journal for Numerical Methods in Biomedical Engineering},
    VOLUME = {35},
    NUMBER = {4},
    YEAR = {2019},
    MONTH = Mar,
    DOI = {10.1002/cnm.3185},
    KEYWORDS = {Rule-based method ; Fiber orientation ; Outflow tract ; Septum ; Electrophysiological simulations ; Outflow tract ventricular arrhythmia},
    HAL_ID = {hal-02128531},
    HAL_VERSION = {v1},
    
    }
    


  9. Simon Heeke, Jonathan Benzaquen, Elodie Long-Mira, Benoît Audelan, Virginie Lespinet, Olivier Bordone, Salomé Lalvée, Katia Zahaf, Michel Poudenx, Olivier Humbert, Henri Montaudié, Pierre-Michel Dugourd, Madleen Chassang, Thierry Passeron, Hervé Delingette, Charles-Hugo Marquette, Véronique Hofman, Albrecht Stenzinger, Marius Ilié, and Paul Hofman. In-House Implementation of Tumor Mutational Burden Testing to Predict Durable Clinical Benefit in Non-Small Cell Lung Cancer and Melanoma Patients. Cancers, 11, 2019. Keyword(s): lung cancer, melanoma, immunotherapy, tumor mutational burden, FoundationOne assay, Oncomine TML assay.
    @article{heeke:hal-02381188,
    TITLE = {{In-House Implementation of Tumor Mutational Burden Testing to Predict Durable Clinical Benefit in Non-Small Cell Lung Cancer and Melanoma Patients}},
    AUTHOR = {Heeke, Simon and Benzaquen, Jonathan and Long-Mira, Elodie and Audelan, Beno{\^i}t and Lespinet, Virginie and Bordone, Olivier and Lalv{\'e}e, Salom{\'e} and Zahaf, Katia and Poudenx, Michel and Humbert, Olivier and Montaudi{\'e}, Henri and Dugourd, Pierre-Michel and Chassang, Madleen and Passeron, Thierry and Delingette, Herv{\'e} and Marquette, Charles-Hugo and Hofman, V{\'e}ronique and Stenzinger, Albrecht and Ili{\'e}, Marius and Hofman, Paul},
    url-hal= {https://hal.inria.fr/hal-02381188},
    JOURNAL = {{Cancers}},
    PUBLISHER = {{MDPI}},
    VOLUME = {11},
    YEAR = {2019},
    DOI = {10.3390/cancers11091271},
    KEYWORDS = {lung cancer ; melanoma ; immunotherapy ; tumor mutational burden ; FoundationOne assay ; Oncomine TML assay},
    PDF = {https://hal.inria.fr/hal-02381188/file/cancers-11-01271-v2%281%29.pdf},
    HAL_ID = {hal-02381188},
    HAL_VERSION = {v1},
    
    }
    


  10. Simon Heeke, Hervé Delingette, Youta Fanjat, Elodie Long-Mira, Sandra Lassalle, Véronique Hofman, Jonathan Benzaquen, Charles-Hugo Marquette, Paul Hofman, and Marius Ilié. La pathologie cancéreuse pulmonaire à l'heure de l'intelligence artificielle : entre espoir, désespoir et perspectives. Annales de Pathologie, 39(2):130-136, April 2019. Keyword(s): Pathology, Histology, Lung cancer, Artificial intelligence, Convolutional neural networks, Deep learning, Pathologie Apprentissage profond, Histologie, Cancer broncho-pulmonair, Intelligence artificielle, Réseaux de neurones convolutifs, Apprentissage profond.
    @article{heeke:hal-02446712,
    TITLE = {{La pathologie canc{\'e}reuse pulmonaire {\`a} l'heure de l'intelligence artificielle : entre espoir, d{\'e}sespoir et perspectives}},
    AUTHOR = {Heeke, Simon and Delingette, Herv{\'e} and Fanjat, Youta and Long-Mira, Elodie and Lassalle, Sandra and Hofman, V{\'e}ronique and Benzaquen, Jonathan and Marquette, Charles-Hugo and Hofman, Paul and Ili{\'e}, Marius},
    url-hal= {https://hal.inria.fr/hal-02446712},
    JOURNAL = {{Annales de Pathologie}},
    PUBLISHER = {{Elsevier Masson}},
    VOLUME = {39},
    NUMBER = {2},
    PAGES = {130-136},
    YEAR = {2019},
    MONTH = Apr,
    DOI = {10.1016/j.annpat.2019.01.003},
    KEYWORDS = {Pathology ; Histology ; Lung cancer ; Artificial intelligence ; Convolutional neural networks ; Deep learning ; Pathologie Apprentissage profond ; Histologie ; Cancer broncho-pulmonair ; Intelligence artificielle ; R{\'e}seaux de neurones convolutifs ; Apprentissage profond},
    HAL_ID = {hal-02446712},
    HAL_VERSION = {v1},
    
    }
    


  11. Paul Hofman, Nicholas Ayache, Pascal Barbry, Michel Barlaud, Audrey Bel, Philippe Blancou, Frédéric Checler, Sylvie Chevillard, Gael Cristofari, Mathilde Demory, Vincent Esnault, Claire Falandry, Eric Gilson, Olivier Guerin, Nicolas Glaichenhaus, Joël Guigay, Marius I. Ilie, Bernard Mari, Charles-Hugo Marquette, Véronique Paquis-Flucklinger, Frédéric Prate, Pierre Saintigny, Barbara Seitz-Polsky, Taycir Skhiri, Ellen Van Obberghen-Schilling, Emmanuel Van Obberghen, and Laurent Yvan-Charvet. The OncoAge Consortium: Linking Aging and Oncology from Bench to Bedside and Back Again. Cancers, 11(2):1-11, February 2019. Keyword(s): aging, education, research, optimization, well-being, cancer, elderly.
    @article{hofman:hal-02045442,
    TITLE = {{The OncoAge Consortium: Linking Aging and Oncology from Bench to Bedside and Back Again}},
    AUTHOR = {Hofman, Paul and Ayache, Nicholas and Barbry, Pascal and Barlaud, Michel and Bel, Audrey and Blancou, Philippe and Checler, Fr{\'e}d{\'e}ric and Chevillard, Sylvie and Cristofari, Gael and Demory, Mathilde and Esnault, Vincent and Falandry, Claire and Gilson, Eric and Guerin, Olivier and Glaichenhaus, Nicolas and Guigay, Jo{\"e}l and Ilie, Marius I. and Mari, Bernard and Marquette, Charles-Hugo and Paquis-Flucklinger, V{\'e}ronique and Prate, Fr{\'e}d{\'e}ric and Saintigny, Pierre and Seitz-Polsky, Barbara and Skhiri, Taycir and Van Obberghen-Schilling, Ellen and Obberghen, Emmanuel Van and Yvan-Charvet, Laurent},
    url-hal= {https://hal.inria.fr/hal-02045442},
    JOURNAL = {{Cancers}},
    PUBLISHER = {{MDPI}},
    VOLUME = {11},
    NUMBER = {2},
    PAGES = {1-11},
    YEAR = {2019},
    MONTH = Feb,
    DOI = {10.3390/cancers11020250},
    KEYWORDS = {aging ; education ; research ; optimization ; well-being ; cancer ; elderly},
    PDF = {https://hal.inria.fr/hal-02045442/file/cancers-11-00250.pdf},
    HAL_ID = {hal-02045442},
    HAL_VERSION = {v1},
    
    }
    


  12. Julian Krebs, Hervé Delingette, Boris Mailhé, Nicholas Ayache, and Tommaso Mansi. Learning a Probabilistic Model for Diffeomorphic Registration. IEEE Transactions on Medical Imaging, pp 2165-2176, February 2019. Keyword(s): deep learning, probabilistic encoding, conditional variational autoencoder, latent variable model, deformation transport, deformable registration.
    @article{krebs:hal-01978339,
    TITLE = {{Learning a Probabilistic Model for Diffeomorphic Registration}},
    AUTHOR = {Krebs, Julian and Delingette, Herv{\'e} and Mailh{\'e}, Boris and Ayache, Nicholas and Mansi, Tommaso},
    url-hal= {https://hal.archives-ouvertes.fr/hal-01978339},
    JOURNAL = {{IEEE Transactions on Medical Imaging}},
    PUBLISHER = {{Institute of Electrical and Electronics Engineers}},
    PAGES = {2165-2176},
    YEAR = {2019},
    MONTH = Feb,
    DOI = {10.1109/TMI.2019.2897112},
    KEYWORDS = {deep learning ; probabilistic encoding ; conditional variational autoencoder ; latent variable model ; deformation transport ; deformable registration},
    PDF = {https://hal.archives-ouvertes.fr/hal-01978339/file/author_files.pdf},
    HAL_ID = {hal-01978339},
    HAL_VERSION = {v1},
    
    }
    


  13. Pawel Mlynarski, Hervé Delingette, Antonio Criminisi, and Nicholas Ayache. 3D Convolutional Neural Networks for Tumor Segmentation using Long-range 2D Context. Computerized Medical Imaging and Graphics, 73:60-72, February 2019. Keyword(s): Brain tumor, Multisequence MRI, Ensembles of models, Segmentation, 3D Convolutional Neural Networks.
    @article{mlynarski:hal-01883716,
    TITLE = {{3D Convolutional Neural Networks for Tumor Segmentation using Long-range 2D Context}},
    AUTHOR = {Mlynarski, Pawel and Delingette, Herv{\'e} and Criminisi, Antonio and Ayache, Nicholas},
    url-hal= {https://hal.inria.fr/hal-01883716},
    JOURNAL = {{Computerized Medical Imaging and Graphics}},
    PUBLISHER = {{Elsevier}},
    VOLUME = {73},
    PAGES = {60-72},
    YEAR = {2019},
    MONTH = Feb,
    DOI = {10.1016/j.compmedimag.2019.02.001},
    KEYWORDS = {Brain tumor ; Multisequence MRI ; Ensembles of models ; Segmentation ; 3D Convolutional Neural Networks},
    PDF = {https://hal.inria.fr/hal-01883716/file/Pawel_Mlynarski_segmentation.pdf},
    HAL_ID = {hal-01883716},
    HAL_VERSION = {v2},
    
    }
    


  14. Pawel Mlynarski, Hervé Delingette, Antonio Criminisi, and Nicholas Ayache. Deep Learning with Mixed Supervision for Brain Tumor Segmentation. Journal of Medical Imaging, July 2019. Keyword(s): Convolutional Neural Networks, Semi-supervised learning, segmentation, tumor, MRI, Semi-supervised..., Convolutional N....
    @article{mlynarski:hal-01952458,
    TITLE = {{Deep Learning with Mixed Supervision for Brain Tumor Segmentation}},
    AUTHOR = {Mlynarski, Pawel and Delingette, Herv{\'e} and Criminisi, Antonio and Ayache, Nicholas},
    url-hal= {https://hal.inria.fr/hal-01952458},
    JOURNAL = {{Journal of Medical Imaging}},
    PUBLISHER = {{SPIE Digital Library}},
    YEAR = {2019},
    MONTH = Jul,
    DOI = {10.1117/1.JMI.6.3.034002},
    KEYWORDS = {Convolutional Neural Networks ; Semi-supervised learning ; segmentation ; tumor ; MRI ; Semi-supervised... ; Convolutional N...},
    PDF = {https://hal.inria.fr/hal-01952458/file/Pawel_Mlynarski_Mixed_Supervision_ArXiv.pdf},
    HAL_ID = {hal-01952458},
    HAL_VERSION = {v1},
    
    }
    


  15. Fanny Orlhac, Charles Bouveyron, and Nicholas Ayache. Radiomics: How to Make Medical Images Speak?. ERCIM News, (118):7-8, July 2019.
    @article{orlhac:hal-02404530,
    TITLE = {{Radiomics: How to Make Medical Images Speak?}},
    AUTHOR = {Orlhac, Fanny and Bouveyron, Charles and Ayache, Nicholas},
    url-hal= {https://hal.inria.fr/hal-02404530},
    JOURNAL = {{ERCIM News}},
    PUBLISHER = {{ERCIM}},
    NUMBER = {118},
    PAGES = {7-8},
    YEAR = {2019},
    MONTH = Jul,
    HAL_ID = {hal-02404530},
    HAL_VERSION = {v1},
    
    }
    


  16. Fanny Orlhac, Frédérique Frouin, Christophe Nioche, Nicholas Ayache, and Irène Buvat. Validation of A Method to Compensate Multicenter Effects Affecting CT Radiomics. Radiology, 291(1):53-59, April 2019.
    @article{orlhac:hal-02401340,
    TITLE = {{Validation of A Method to Compensate Multicenter Effects Affecting CT Radiomics}},
    AUTHOR = {Orlhac, Fanny and Frouin, Fr{\'e}d{\'e}rique and Nioche, Christophe and Ayache, Nicholas and Buvat, Ir{\`e}ne},
    url-hal= {https://hal.archives-ouvertes.fr/hal-02401340},
    JOURNAL = {{Radiology}},
    PUBLISHER = {{Radiological Society of North America}},
    VOLUME = {291},
    NUMBER = {1},
    PAGES = {53-59},
    YEAR = {2019},
    MONTH = Apr,
    DOI = {10.1148/radiol.2019182023},
    PDF = {https://hal.archives-ouvertes.fr/hal-02401340/file/radiol.2019182023.pdf},
    HAL_ID = {hal-02401340},
    HAL_VERSION = {v1},
    
    }
    


  17. Maxime Sermesant. Improving Cardiac Arrhythmia Therapy with Medical Imaging. ERCIM News, (118):10-11, July 2019.
    @article{sermesant:hal-02404534,
    TITLE = {{Improving Cardiac Arrhythmia Therapy with Medical Imaging}},
    AUTHOR = {Sermesant, Maxime},
    url-hal= {https://hal.inria.fr/hal-02404534},
    JOURNAL = {{ERCIM News}},
    PUBLISHER = {{ERCIM}},
    NUMBER = {118},
    PAGES = {10-11},
    YEAR = {2019},
    MONTH = Jul,
    HAL_ID = {hal-02404534},
    HAL_VERSION = {v1},
    
    }
    


  18. Raphaël Sivera, Hervé Delingette, Marco Lorenzi, Xavier Pennec, and Nicholas Ayache. A model of brain morphological changes related to aging and Alzheimer's disease from cross-sectional assessments. NeuroImage, 198:255-270, September 2019. Keyword(s): Deformations, Aging, Alzheimer's disease, Imaging biomarkers, Spatio-temporal model, Brain morphology.
    @article{sivera:hal-01948174,
    TITLE = {{A model of brain morphological changes related to aging and Alzheimer's disease from cross-sectional assessments}},
    AUTHOR = {Sivera, Rapha{\"e}l and Delingette, Herv{\'e} and Lorenzi, Marco and Pennec, Xavier and Ayache, Nicholas},
    url-hal= {https://hal.inria.fr/hal-01948174},
    JOURNAL = {{NeuroImage}},
    PUBLISHER = {{Elsevier}},
    VOLUME = {198},
    PAGES = {255-270},
    YEAR = {2019},
    MONTH = Sep,
    DOI = {10.1016/j.neuroimage.2019.05.040},
    KEYWORDS = {Deformations ; Aging ; Alzheimer's disease ; Imaging biomarkers ; Spatio-temporal model ; Brain morphology},
    PDF = {https://hal.inria.fr/hal-01948174/file/paper-stripped.pdf},
    HAL_ID = {hal-01948174},
    HAL_VERSION = {v3},
    
    }
    


  19. Masateru Takigawa, Josselin Duchateau, Frederic Sacher, Ruairidh Martin, Konstantinos Vlachos, Takeshi Kitamura, Maxime Sermesant, Nicolas Cedilnik, Ghassen Cheniti, Antonio Frontera, Nathaniel Thompson, Calire Martin, Grégoire Massoullié, Felix Bourier, Anna Lam, Michael Wolf, William Escande, Clémentine André, Thomas Pambrun, Arnaud Denis, Nicolas Derval, Mélèze Hocini, Michel Haïssaguerre, Hubert Cochet, and Pierre Jaïs. Are wall thickness channels defined by computed tomography predictive of isthmuses of postinfarction ventricular tachycardia?. Heart Rhythm, 16(11):1661-1668, June 2019. Keyword(s): Isthmus, High-resolution mapping, Contrart-enhanced multidetector computed tomography, MUSIC, Myocardial infarction, Ventricular tachycardia, Wall thickness.
    @article{takigawa:hal-02181776,
    TITLE = {{Are wall thickness channels defined by computed tomography predictive of isthmuses of postinfarction ventricular tachycardia?}},
    AUTHOR = {Takigawa, Masateru and Duchateau, Josselin and Sacher, Frederic and Martin, Ruairidh and Vlachos, Konstantinos and Kitamura, Takeshi and Sermesant, Maxime and Cedilnik, Nicolas and Cheniti, Ghassen and Frontera, Antonio and Thompson, Nathaniel and Martin, Calire and Massoulli{\'e}, Gr{\'e}goire and Bourier, Felix and Lam, Anna and Wolf, Michael and Escande, William and Andr{\'e}, Cl{\'e}mentine and Pambrun, Thomas and Denis, Arnaud and Derval, Nicolas and Hocini, M{\'e}l{\`e}ze and Ha{\"i}ssaguerre, Michel and Cochet, Hubert and Ja{\"i}s, Pierre},
    url-hal= {https://hal.inria.fr/hal-02181776},
    JOURNAL = {{Heart Rhythm}},
    PUBLISHER = {{Elsevier}},
    SERIES = {Heart Rhythm},
    VOLUME = {16},
    NUMBER = {11},
    PAGES = {1661-1668},
    YEAR = {2019},
    MONTH = Jun,
    DOI = {10.1016/j.hrthm.2019.06.012},
    KEYWORDS = {Isthmus ; High-resolution mapping ; Contrart-enhanced multidetector computed tomography ; MUSIC ; Myocardial infarction ; Ventricular tachycardia ; Wall thickness},
    HAL_ID = {hal-02181776},
    HAL_VERSION = {v1},
    
    }
    


  20. Wen Wei, Emilie Poirion, Benedetta Bodini, Stanley Durrleman, Nicholas Ayache, Bruno Stankoff, and Olivier Colliot. Predicting PET-derived Demyelination from Multimodal MRI using Sketcher-Refiner Adversarial Training for Multiple Sclerosis. Medical Image Analysis, 2019. Keyword(s): Adversarial Training, Multiple Sclerosis, PET Imaging, Multimodal MRI.
    @article{wei:hal-02276634,
    TITLE = {{Predicting PET-derived Demyelination from Multimodal MRI using Sketcher-Refiner Adversarial Training for Multiple Sclerosis}},
    AUTHOR = {Wei, Wen and Poirion, Emilie and Bodini, Benedetta and Durrleman, Stanley and Ayache, Nicholas and Stankoff, Bruno and Colliot, Olivier},
    url-hal= {https://hal.archives-ouvertes.fr/hal-02276634},
    JOURNAL = {{Medical Image Analysis}},
    PUBLISHER = {{Elsevier}},
    YEAR = {2019},
    DOI = {10.1016/j.media.2019.101546},
    KEYWORDS = {Adversarial Training ; Multiple Sclerosis ; PET Imaging ; Multimodal MRI},
    PDF = {https://hal.archives-ouvertes.fr/hal-02276634/file/medima-hal_version.pdf},
    HAL_ID = {hal-02276634},
    HAL_VERSION = {v1},
    
    }
    


  21. Wen Wei, Emilie Poirion, Benedetta Bodini, Stanley Durrleman, Olivier Colliot, Bruno Stankoff, and Nicholas Ayache. Fluid-attenuated inversion recovery MRI synthesis from multisequence MRI using three-dimensional fully convolutional networks for multiple sclerosis. Journal of Medical Imaging, 6(01), February 2019. Keyword(s): MR Images, FLAIR Synthesis, 3D Fully Convolutional Networks, Multiple Sclerosis, Deep Learning.
    @article{wei:hal-02042526,
    TITLE = {{Fluid-attenuated inversion recovery MRI synthesis from multisequence MRI using three-dimensional fully convolutional networks for multiple sclerosis}},
    AUTHOR = {Wei, Wen and Poirion, Emilie and Bodini, Benedetta and Durrleman, Stanley and Colliot, Olivier and Stankoff, Bruno and Ayache, Nicholas},
    url-hal= {https://hal.inria.fr/hal-02042526},
    JOURNAL = {{Journal of Medical Imaging}},
    PUBLISHER = {{SPIE Digital Library}},
    VOLUME = {6},
    NUMBER = {01},
    YEAR = {2019},
    MONTH = Feb,
    DOI = {10.1117/1.JMI.6.1.014005},
    KEYWORDS = {MR Images ; FLAIR Synthesis ; 3D Fully Convolutional Networks ; Multiple Sclerosis ; Deep Learning},
    PDF = {https://hal.inria.fr/hal-02042526/file/article.pdf},
    HAL_ID = {hal-02042526},
    HAL_VERSION = {v2},
    
    }
    


  22. Wilhelm Wimmer, Lukas Anschuetz, Stefan Weder, Franca Wagner, Hervé Delingette, and Marco Caversaccio. Human bony labyrinth dataset: Co-registered CT and micro-CT images, surface models and anatomical landmarks. Data in Brief, 27:104782, December 2019. Keyword(s): Vestibule, Semicircular canals, Morphology, Anatomy, Cochlea, Inner ear.
    @article{wimmer:hal-02402404,
    TITLE = {{Human bony labyrinth dataset: Co-registered CT and micro-CT images, surface models and anatomical landmarks}},
    AUTHOR = {Wimmer, Wilhelm and Anschuetz, Lukas and Weder, Stefan and Wagner, Franca and Delingette, Herv{\'e} and Caversaccio, Marco},
    url-hal= {https://hal.inria.fr/hal-02402404},
    JOURNAL = {{Data in Brief}},
    PUBLISHER = {{Elsevier}},
    VOLUME = {27},
    PAGES = {104782},
    YEAR = {2019},
    MONTH = Dec,
    DOI = {10.1016/j.dib.2019.104782},
    KEYWORDS = {Vestibule ; Semicircular canals ; Morphology ; Anatomy ; Cochlea ; Inner ear},
    HAL_ID = {hal-02402404},
    HAL_VERSION = {v1},
    
    }
    


  23. Qiao Zheng, Hervé Delingette, and Nicholas Ayache. Explainable cardiac pathology classification on cine MRI with motion characterization by semi-supervised learning of apparent flow. Medical Image Analysis, 56:80-95, 2019. Keyword(s): Classifi-cation, Motion, Cine MRI, Deep learn- ing, Semi-supervised learning, Neural network, Cardiac pathology, Classifi- cation, Apparent flow, Deep learn-ing.
    @article{zheng:hal-01975880,
    TITLE = {{Explainable cardiac pathology classification on cine MRI with motion characterization by semi-supervised learning of apparent flow}},
    AUTHOR = {Zheng, Qiao and Delingette, Herv{\'e} and Ayache, Nicholas},
    url-hal= {https://hal.inria.fr/hal-01975880},
    JOURNAL = {{Medical Image Analysis}},
    PUBLISHER = {{Elsevier}},
    VOLUME = {56},
    PAGES = {80-95},
    YEAR = {2019},
    DOI = {10.1016/j.media.2019.06.001},
    KEYWORDS = {Classifi-cation ; Motion ; Cine MRI ; Deep learn- ing ; Semi-supervised learning ; Neural network ; Cardiac pathology ; Classifi- cation ; Apparent flow ; Deep learn-ing},
    PDF = {https://hal.inria.fr/hal-01975880/file/1811.03433.pdf},
    HAL_ID = {hal-01975880},
    HAL_VERSION = {v2},
    
    }
    


Conference articles

  1. Luigi Antelmi, Nicholas Ayache, Philippe Robert, and Marco Lorenzi. Sparse Multi-Channel Variational Autoencoder for the Joint Analysis of Heterogeneous Data. In ICML 2019 - 36th International Conference on Machine Learning, Long Beach, United States, June 2019.
    @inproceedings{antelmi:hal-02154181,
    TITLE = {{Sparse Multi-Channel Variational Autoencoder for the Joint Analysis of Heterogeneous Data}},
    AUTHOR = {Antelmi, Luigi and Ayache, Nicholas and Robert, Philippe and Lorenzi, Marco},
    url-hal= {https://hal.inria.fr/hal-02154181},
    BOOKTITLE = {{ICML 2019 - 36th International Conference on Machine Learning}},
    ADDRESS = {Long Beach, United States},
    YEAR = {2019},
    MONTH = Jun,
    PDF = {https://hal.inria.fr/hal-02154181/file/antelmi19a.pdf},
    HAL_ID = {hal-02154181},
    HAL_VERSION = {v1},
    
    }
    


  2. Benoît Audelan and Hervé Delingette. Unsupervised Quality Control of Image Segmentation based on Bayesian Learning. In MICCAI 2019 - 22nd International Conference on Medical Image Computing and Computer Assisted Intervention, Shenzhen, China, pages 21-29, October 2019. Keyword(s): image segmentation, Bayesian learning, Quality control.
    @inproceedings{audelan:hal-02265131,
    TITLE = {{Unsupervised Quality Control of Image Segmentation based on Bayesian Learning}},
    AUTHOR = {Audelan, Beno{\^i}t and Delingette, Herv{\'e}},
    url-hal= {https://hal.inria.fr/hal-02265131},
    BOOKTITLE = {{MICCAI 2019 - 22nd International Conference on Medical Image Computing and Computer Assisted Intervention}},
    ADDRESS = {Shenzhen, China},
    PAGES = {21-29},
    YEAR = {2019},
    MONTH = Oct,
    KEYWORDS = {image segmentation ; Bayesian learning ; Quality control},
    PDF = {https://hal.inria.fr/hal-02265131/file/paper2106.pdf},
    HAL_ID = {hal-02265131},
    HAL_VERSION = {v1},
    
    }
    


  3. Nicholas Ayache. AI and Healthcare: towards a Digital Twin?. In MCA 2019 - 5th International Symposium on Multidiscplinary Computational Anatomy, Fukuoka, Japan, March 2019.
    @inproceedings{ayache:hal-02063234,
    TITLE = {{AI and Healthcare: towards a Digital Twin?}},
    AUTHOR = {Ayache, Nicholas},
    url-hal= {https://hal.inria.fr/hal-02063234},
    BOOKTITLE = {{MCA 2019 - 5th International Symposium on Multidiscplinary Computational Anatomy}},
    ADDRESS = {Fukuoka, Japan},
    YEAR = {2019},
    MONTH = Mar,
    HAL_ID = {hal-02063234},
    HAL_VERSION = {v1},
    
    }
    


  4. Ibrahim Ayed, Nicolas Cedilnik, Patrick Gallinari, and Maxime Sermesant. EP-Net: Learning Cardiac Electrophysiology Models for Physiology-based Constraints in Data-Driven Predictions. In FIMH 2019 - 10th International Conference on Functional Imaging of the Hearth, Bordeaux, France, pages 55-63, June 2019. Springer.
    @inproceedings{ayed:hal-02106618,
    TITLE = {{EP-Net: Learning Cardiac Electrophysiology Models for Physiology-based Constraints in Data-Driven Predictions}},
    AUTHOR = {Ayed, Ibrahim and Cedilnik, Nicolas and Gallinari, Patrick and Sermesant, Maxime},
    url-hal= {https://hal.inria.fr/hal-02106618},
    BOOKTITLE = {{FIMH 2019 - 10th International Conference on Functional Imaging of the Hearth}},
    ADDRESS = {Bordeaux, France},
    PUBLISHER = {{Springer}},
    PAGES = {55-63},
    YEAR = {2019},
    MONTH = Jun,
    PDF = {https://hal.inria.fr/hal-02106618/file/LearningModel_FIMH_2019%285%29.pdf},
    HAL_ID = {hal-02106618},
    HAL_VERSION = {v1},
    
    }
    


  5. Tania Bacoyannis, Julian Krebs, Nicolas Cedilnik, Hubert Cochet, and Maxime Sermesant. Deep Learning Formulation of ECGI for Data-driven Integration of Spatiotemporal Correlations and Imaging Information. In FIMH 2019 - 10th International Conference on Functional Imaging and Modeling of the Heart, volume LNCS 11504, Bordeaux, France, pages 20-28, June 2019. Springer. Keyword(s): Simulation, Generative Model, Deep learning, ECGI.
    @inproceedings{bacoyannis:hal-02108958,
    TITLE = {{Deep Learning Formulation of ECGI for Data-driven Integration of Spatiotemporal Correlations and Imaging Information}},
    AUTHOR = {Bacoyannis, Tania and Krebs, Julian and Cedilnik, Nicolas and Cochet, Hubert and Sermesant, Maxime},
    url-hal= {https://hal.inria.fr/hal-02108958},
    BOOKTITLE = {{FIMH 2019 - 10th International Conference on Functional Imaging and Modeling of the Heart}},
    ADDRESS = {Bordeaux, France},
    PUBLISHER = {{Springer}},
    VOLUME = {LNCS 11504},
    PAGES = {20-28},
    YEAR = {2019},
    MONTH = Jun,
    KEYWORDS = {Simulation ; Generative Model ; Deep learning ; ECGI},
    PDF = {https://hal.inria.fr/hal-02108958/file/tania_fimh.pdf},
    HAL_ID = {hal-02108958},
    HAL_VERSION = {v2},
    
    }
    


  6. Jaume Banus, Marco Lorenzi, Oscar Camara, and Maxime Sermesant. Large Scale Cardiovascular Model Personalisation for Mechanistic Analysis of Heart and Brain Interactions. In FIMH 2019 - 10th International Conference on Functional Imaging and Modeling of the Heart, Bordeaux, France, pages 285-293, June 2019.
    @inproceedings{banus:hal-02361466,
    TITLE = {{Large Scale Cardiovascular Model Personalisation for Mechanistic Analysis of Heart and Brain Interactions}},
    AUTHOR = {Banus, Jaume and Lorenzi, Marco and Camara, Oscar and Sermesant, Maxime},
    url-hal= {https://hal.inria.fr/hal-02361466},
    BOOKTITLE = {{FIMH 2019 - 10th International Conference on Functional Imaging and Modeling of the Heart}},
    ADDRESS = {Bordeaux, France},
    PAGES = {285-293},
    YEAR = {2019},
    MONTH = Jun,
    DOI = {10.1007/978-3-030-21949-9\_31},
    PDF = {https://hal.inria.fr/hal-02361466/file/FIMH_Jaume_2019_Updated.pdf},
    HAL_ID = {hal-02361466},
    HAL_VERSION = {v1},
    
    }
    


  7. Nicolas Cedilnik, Josselin Duchateau, Frederic Sacher, Pierre Jaïs, Hubert Cochet, and Maxime Sermesant. Fully Automated Electrophysiological Model Personalisation Framework from CT Imaging. In FIMH 2019 - 10th International Conference on Functional Imaging and Modeling of the Heart, Bordeaux, France, pages 325-333, June 2019. Keyword(s): Model Personalisation, Deep learning, Segmentation, Imaging.
    @inproceedings{cedilnik:hal-02106609,
    TITLE = {{Fully Automated Electrophysiological Model Personalisation Framework from CT Imaging}},
    AUTHOR = {Cedilnik, Nicolas and Duchateau, Josselin and Sacher, Frederic and Ja{\"i}s, Pierre and Cochet, Hubert and Sermesant, Maxime},
    url-hal= {https://hal.inria.fr/hal-02106609},
    BOOKTITLE = {{FIMH 2019 - 10th International Conference on Functional Imaging and Modeling of the Heart}},
    ADDRESS = {Bordeaux, France},
    PAGES = {325-333},
    YEAR = {2019},
    MONTH = Jun,
    KEYWORDS = {Model Personalisation ; Deep learning ; Segmentation ; Imaging},
    PDF = {https://hal.inria.fr/hal-02106609/file/cedilnik_fimh2019%287%29.pdf},
    HAL_ID = {hal-02106609},
    HAL_VERSION = {v1},
    
    }
    


  8. Nicolas Cedilnik, Shuman Jia, Pierre Jaïs, Hubert Cochet, and Maxime Sermesant. Automatic non-invasive substrate analysis from CT images in post-infarction VT. In EHRA 2019 - European Heart Rhythm Association, volume 21, Lisbonne, Portugal, pages 720-739, March 2019.
    @inproceedings{cedilnik:hal-02181793,
    TITLE = {{Automatic non-invasive substrate analysis from CT images in post-infarction VT}},
    AUTHOR = {Cedilnik, Nicolas and Jia, Shuman and Ja{\"i}s, Pierre and Cochet, Hubert and Sermesant, Maxime},
    url-hal= {https://hal.inria.fr/hal-02181793},
    BOOKTITLE = {{EHRA 2019 - European Heart Rhythm Association}},
    ADDRESS = {Lisbonne, Portugal},
    VOLUME = {21},
    NUMBER = {2},
    PAGES = {720-739},
    YEAR = {2019},
    MONTH = Mar,
    DOI = {10.1093/europace/euz105},
    HAL_ID = {hal-02181793},
    HAL_VERSION = {v1},
    
    }
    


  9. Nicolas Cedilnik and Maxime Sermesant. Eikonal Model Personalisation using Invasive Data to Predict Cardiac Resynchronisation Therapy Electrophysiological Response. In STACOM 2019 - 10th Workshop on Statistical Atlases and Computational Modelling of the Heart, Shenzen, China, October 2019. Keyword(s): Cardiac resynchronisation therapy, Electrophysiology, Computer model, Personalisation.
    @inproceedings{cedilnik:hal-02368288,
    TITLE = {{Eikonal Model Personalisation using Invasive Data to Predict Cardiac Resynchronisation Therapy Electrophysiological Response}},
    AUTHOR = {Cedilnik, Nicolas and Sermesant, Maxime},
    url-hal= {https://hal.inria.fr/hal-02368288},
    BOOKTITLE = {{STACOM 2019 - 10th Workshop on Statistical Atlases and Computational Modelling of the Heart}},
    ADDRESS = {Shenzen, China},
    YEAR = {2019},
    MONTH = Oct,
    KEYWORDS = {Cardiac resynchronisation therapy ; Electrophysiology ; Computer model ; Personalisation},
    PDF = {https://hal.inria.fr/hal-02368288/file/cedilnik_stacom2019.pdf},
    HAL_ID = {hal-02368288},
    HAL_VERSION = {v1},
    
    }
    


  10. Gaëtan Desrues, Hervé Delingette, and Maxime Sermesant. Towards Hyper-Reduction of Cardiac Models using Poly-Affine Deformation. In STACOM 2019: Statistical Atlases and Computational Models of the Heart, Shenzhen, China, October 2019.
    @inproceedings{desrues:hal-02429678,
    TITLE = {{Towards Hyper-Reduction of Cardiac Models using Poly-Affine Deformation}},
    AUTHOR = {Desrues, Ga{\"e}tan and Delingette, Herv{\'e} and Sermesant, Maxime},
    url-hal= {https://hal.inria.fr/hal-02429678},
    BOOKTITLE = {{STACOM 2019: Statistical Atlases and Computational Models of the Heart}},
    ADDRESS = {Shenzhen, China},
    YEAR = {2019},
    MONTH = Oct,
    PDF = {https://hal.inria.fr/hal-02429678/file/STACOM_FinalVersion.pdf},
    HAL_ID = {hal-02429678},
    HAL_VERSION = {v1},
    
    }
    


  11. Sara Garbarino and Marco Lorenzi. Modeling and Inference of Spatio-Temporal Protein Dynamics Across Brain Networks. In IPMI 2019 - 26th International Conference on Information Processing in Medical Imaging, volume 11492 of LNCS, Hong-Kong, China, pages 57-69, June 2019. Springer. Keyword(s): Disease progression model., Spatio--temporal model, Bayesian non--parametric model, Gaussian process, Dynamical systems, Protein propagation, Alzheimer's disease.
    @inproceedings{garbarino:hal-02165021,
    TITLE = {{Modeling and Inference of Spatio-Temporal Protein Dynamics Across Brain Networks}},
    AUTHOR = {Garbarino, Sara and Lorenzi, Marco},
    url-hal= {https://hal.inria.fr/hal-02165021},
    BOOKTITLE = {{IPMI 2019 - 26th International Conference on Information Processing in Medical Imaging}},
    ADDRESS = {Hong-Kong, China},
    PUBLISHER = {{Springer}},
    SERIES = {LNCS},
    VOLUME = {11492},
    PAGES = {57-69},
    YEAR = {2019},
    MONTH = Jun,
    KEYWORDS = {Disease progression model. ; Spatio--temporal model ; Bayesian non--parametric model ; Gaussian process ; Dynamical systems ; Protein propagation ; Alzheimer's disease},
    PDF = {https://hal.inria.fr/hal-02165021/file/IPMI_01-10-2018.pdf},
    HAL_ID = {hal-02165021},
    HAL_VERSION = {v1},
    
    }
    


  12. Nicolas Guigui, Shuman Jia, Maxime Sermesant, and Xavier Pennec. Symmetric Algorithmic Components for Shape Analysis with Diffeomorphisms. In GSI 2019 - 4th conference on Geometric Science of Information, volume Lecture Notes in Computer Science 11712 of Proceedings of Geometric Science of Information, Toulouse, France, pages 759-768, August 2019. F. Nielsen and F. Barbaresco, Springer. Keyword(s): Shape Registration, Parallel Transport, Symmetric Spaces.
    @inproceedings{guigui:hal-02148832,
    TITLE = {{Symmetric Algorithmic Components for Shape Analysis with Diffeomorphisms}},
    AUTHOR = {Guigui, Nicolas and Jia, Shuman and Sermesant, Maxime and Pennec, Xavier},
    url-hal= {https://hal.inria.fr/hal-02148832},
    BOOKTITLE = {{GSI 2019 - 4th conference on Geometric Science of Information}},
    ADDRESS = {Toulouse, France},
    ORGANIZATION = {{F. Nielsen and F. Barbaresco}},
    PUBLISHER = {{Springer}},
    SERIES = {Proceedings of Geometric Science of Information},
    VOLUME = {Lecture Notes in Computer Science 11712},
    PAGES = {759--768},
    YEAR = {2019},
    MONTH = Aug,
    DOI = {10.1007/978-3-030-26980-7\_79},
    KEYWORDS = {Shape Registration ; Parallel Transport ; Symmetric Spaces},
    PDF = {https://hal.inria.fr/hal-02148832/file/55-Guigui.pdf},
    HAL_ID = {hal-02148832},
    HAL_VERSION = {v1},
    
    }
    


  13. Julian Krebs, Tommaso Mansi, Nicholas Ayache, and Hervé Delingette. Probabilistic Motion Modeling from Medical Image Sequences: Application to Cardiac Cine-MRI. In STACOM 2019 - 10th Workshop on Statistical Atlases and Computational Modelling of the Heart, Shenzhen, China, October 2019. Note: Probabilistic Motion Model, Motion Tracking, Temporal Super-Resolution, Diffeomorphic Registration, Temporal Variational Autoencoder.
    @inproceedings{krebs:hal-02239318,
    TITLE = {{Probabilistic Motion Modeling from Medical Image Sequences: Application to Cardiac Cine-MRI}},
    AUTHOR = {Krebs, Julian and Mansi, Tommaso and Ayache, Nicholas and Delingette, Herv{\'e}},
    url-hal= {https://hal.inria.fr/hal-02239318},
    NOTE = {Probabilistic Motion Model, Motion Tracking, Temporal Super-Resolution, Diffeomorphic Registration, Temporal Variational Autoencoder},
    BOOKTITLE = {{STACOM 2019 - 10th Workshop on Statistical Atlases and Computational Modelling of the Heart}},
    ADDRESS = {Shenzhen, China},
    YEAR = {2019},
    MONTH = Oct,
    PDF = {https://hal.inria.fr/hal-02239318/file/stacom_2019_final.pdf},
    HAL_ID = {hal-02239318},
    HAL_VERSION = {v2},
    
    }
    


  14. Buntheng Ly, Hubert Cochet, and Maxime Sermesant. Style Data Augmentation for Robust Segmentation of Multi-Modality Cardiac MRI. In Statistical Atlases and Computational Modelling of the Heart, Shenzhen, China, October 2019. Keyword(s): Deep Learning, image segmentation, Cardiac Magnetic Resonance Imaging, Multi-modality, Late Gadolinium Enhanced.
    @inproceedings{ly:hal-02401643,
    TITLE = {{Style Data Augmentation for Robust Segmentation of Multi-Modality Cardiac MRI}},
    AUTHOR = {Ly, Buntheng and Cochet, Hubert and Sermesant, Maxime},
    url-hal= {https://hal.inria.fr/hal-02401643},
    BOOKTITLE = {{Statistical Atlases and Computational Modelling of the Heart}},
    ADDRESS = {Shenzhen, China},
    YEAR = {2019},
    MONTH = Oct,
    KEYWORDS = {Deep Learning ; image segmentation ; Cardiac Magnetic Resonance Imaging ; Multi-modality ; Late Gadolinium Enhanced},
    PDF = {https://hal.inria.fr/hal-02401643/file/miccai_ms_seg_hal.pdf},
    HAL_ID = {hal-02401643},
    HAL_VERSION = {v2},
    
    }
    


  15. Pamela Moceri, Nicolas Duchateau, Delphine Baudouy, Céline Sanfiorenzo, Fabien Squara, Emile Ferrari, and Maxime Sermesant. Incremental prognostic value of changes in 3D right ventricular function in pulmonary hypertension. In JE SFC 2019 - 29es Journées Européennes de la Société Française de Cardiologie, Paris, France, January 2019.
    @inproceedings{moceri:hal-02161692,
    TITLE = {{Incremental prognostic value of changes in 3D right ventricular function in pulmonary hypertension}},
    AUTHOR = {Moceri, Pamela and Duchateau, Nicolas and Baudouy, Delphine and Sanfiorenzo, C{\'e}line and Squara, Fabien and Ferrari, Emile and Sermesant, Maxime},
    url-hal= {https://hal.archives-ouvertes.fr/hal-02161692},
    BOOKTITLE = {{JE SFC 2019 - 29es Journ{\'e}es Europ{\'e}ennes de la Soci{\'e}t{\'e} Fran{\c c}aise de Cardiologie}},
    ADDRESS = {Paris, France},
    YEAR = {2019},
    MONTH = Jan,
    HAL_ID = {hal-02161692},
    HAL_VERSION = {v1},
    
    }
    


  16. Pamela Moceri, Nicolas Duchateau, Delphine Baudouy, Fabien Squara, Emile Ferrari, and Maxime Sermesant. 3D right ventricular strain and shape in volume overload: comparative analysis of Tetralogy of Fallot and atrial septal defect patients. In JE SFC 2019 - 29es Journées Européennes de la Société Française de Cardiologie, Paris, France, January 2019.
    @inproceedings{moceri:hal-02161694,
    TITLE = {{3D right ventricular strain and shape in volume overload: comparative analysis of Tetralogy of Fallot and atrial septal defect patients}},
    AUTHOR = {Moceri, Pamela and Duchateau, Nicolas and Baudouy, Delphine and Squara, Fabien and Ferrari, Emile and Sermesant, Maxime},
    url-hal= {https://hal.archives-ouvertes.fr/hal-02161694},
    BOOKTITLE = {{JE SFC 2019 - 29es Journ{\'e}es Europ{\'e}ennes de la Soci{\'e}t{\'e} Fran{\c c}aise de Cardiologie}},
    ADDRESS = {Paris, France},
    YEAR = {2019},
    MONTH = Jan,
    HAL_ID = {hal-02161694},
    HAL_VERSION = {v1},
    
    }
    


  17. Yann Thanwerdas and Xavier Pennec. Exploration of Balanced Metrics on Symmetric Positive Definite Matrices. In GSI 2019 - 4th conference on Geometric Science of Information, volume Lecture Notes in Computer Science 11712 of Proceedings of Geometric Science of Information, Toulouse, France, pages 484-493, August 2019. Springer. Keyword(s): Information geometry, SPD matrices, Dually flat connections.
    @inproceedings{thanwerdas:hal-02158525,
    TITLE = {{Exploration of Balanced Metrics on Symmetric Positive Definite Matrices}},
    AUTHOR = {Thanwerdas, Yann and Pennec, Xavier},
    url-hal= {https://hal.archives-ouvertes.fr/hal-02158525},
    BOOKTITLE = {{GSI 2019 - 4th conference on Geometric Science of Information}},
    ADDRESS = {Toulouse, France},
    PUBLISHER = {{Springer}},
    SERIES = {Proceedings of Geometric Science of Information},
    VOLUME = {Lecture Notes in Computer Science 11712},
    PAGES = {484--493},
    YEAR = {2019},
    MONTH = Aug,
    DOI = {10.1007/978-3-030-26980-7\_50},
    KEYWORDS = {Information geometry ; SPD matrices ; Dually flat connections},
    PDF = {https://hal.archives-ouvertes.fr/hal-02158525/file/Thanwerdas_GSI19_Balanced%20metrics.pdf},
    HAL_ID = {hal-02158525},
    HAL_VERSION = {v1},
    
    }
    


  18. Yann Thanwerdas and Xavier Pennec. Is affine invariance well defined on SPD matrices? A principled continuum of metrics. In GSI 2019 - 4th conference on Geometric Science of Information, volume Lecture Notes in Computer Science 11712 of Proceedings of Geometric Science of Information, Toulouse, France, pages 502-510, August 2019. Springer. Keyword(s): Riemannian symmetric spaces, SPD matrices.
    @inproceedings{thanwerdas:hal-02147020,
    TITLE = {{Is affine invariance well defined on SPD matrices? A principled continuum of metrics}},
    AUTHOR = {Thanwerdas, Yann and Pennec, Xavier},
    url-hal= {https://hal.archives-ouvertes.fr/hal-02147020},
    BOOKTITLE = {{GSI 2019 - 4th conference on Geometric Science of Information}},
    ADDRESS = {Toulouse, France},
    PUBLISHER = {{Springer}},
    SERIES = {Proceedings of Geometric Science of Information},
    VOLUME = {Lecture Notes in Computer Science 11712},
    PAGES = {502-510},
    YEAR = {2019},
    MONTH = Aug,
    DOI = {10.1007/978-3-030-26980-7\_52},
    KEYWORDS = {Riemannian symmetric spaces ; SPD matrices},
    PDF = {https://hal.archives-ouvertes.fr/hal-02147020/file/main.pdf},
    HAL_ID = {hal-02147020},
    HAL_VERSION = {v1},
    
    }
    


  19. Zihao Wang, Clair Vandersteen, Thomas Demarcy, Dan Gnansia, Charles Raffaelli, Nicolas Guevara, and Hervé Delingette. Deep Learning based Metal Artifacts Reduction in post-operative Cochlear Implant CT Imaging. In MICCAI 2019 - 22nd International Conference on Medical Image Computing and Computer Assisted Intervention, Shenzhen, China, pages 121-129, October 2019. Keyword(s): Metal Artifacts Reduction, Generative adversarial networks.
    @inproceedings{wang:hal-02196557,
    TITLE = {{Deep Learning based Metal Artifacts Reduction in post-operative Cochlear Implant CT Imaging}},
    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-02196557},
    BOOKTITLE = {{MICCAI 2019 - 22nd International Conference on Medical Image Computing and Computer Assisted Intervention}},
    ADDRESS = {Shenzhen, China},
    PAGES = {121-129},
    YEAR = {2019},
    MONTH = Oct,
    KEYWORDS = {Metal Artifacts Reduction ; Generative adversarial networks},
    PDF = {https://hal.inria.fr/hal-02196557/file/paper2371.pdf},
    HAL_ID = {hal-02196557},
    HAL_VERSION = {v1},
    
    }
    


  20. Wilhelm Wimmer, Clair Vandersteen, Nicolas Guevara, Marco Caversaccio, and Hervé Delingette. Robust Cochlear Modiolar Axis Detection in CT. In MICCAI 2019 - 22nd International Conference on Medical Image Computing and Computer Assisted Intervention, Medical Image Computing and Computer Assisted Intervention -- MICCAI 2019. MICCAI 2019. Lecture Notes in Computer Science, Shenzhen, China, pages 3-10, October 2019. Keyword(s): Approximate maximum like-lihood, Natural growth, Kinematic surface recognition.
    @inproceedings{wimmer:hal-02402475,
    TITLE = {{Robust Cochlear Modiolar Axis Detection in CT}},
    AUTHOR = {Wimmer, Wilhelm and Vandersteen, Clair and Guevara, Nicolas and Caversaccio, Marco and Delingette, Herv{\'e}},
    url-hal= {https://hal.inria.fr/hal-02402475},
    BOOKTITLE = {{MICCAI 2019 - 22nd International Conference on Medical Image Computing and Computer Assisted Intervention}},
    ADDRESS = {Shenzhen, China},
    SERIES = {Medical Image Computing and Computer Assisted Intervention -- MICCAI 2019. MICCAI 2019. Lecture Notes in Computer Science},
    PAGES = {3-10},
    YEAR = {2019},
    MONTH = Oct,
    DOI = {10.1007/978-3-030-32254-0\_1},
    KEYWORDS = {Approximate maximum like-lihood ; Natural growth ; Kinematic surface recognition},
    HAL_ID = {hal-02402475},
    HAL_VERSION = {v1},
    
    }
    


  21. Yingyu Yang, Stephane Gillon, Jaume Banus, Pamela Moceri, and Maxime Sermesant. Non-Invasive Pressure Estimation in Patients with Pulmonary Arterial Hypertension: Data-driven or Model-based?. In STACOM 2019 - 10th Workshop on Statistical Atlases and Computational Modelling of the Heart, Shenzhen, China, October 2019. Keyword(s): Cardiac modelling, Machine learning, Pulmonary hypertension.
    @inproceedings{yang:hal-02382941,
    TITLE = {{Non-Invasive Pressure Estimation in Patients with Pulmonary Arterial Hypertension: Data-driven or Model-based?}},
    AUTHOR = {Yang, Yingyu and Gillon, Stephane and Banus, Jaume and Moceri, Pamela and Sermesant, Maxime},
    url-hal= {https://hal.inria.fr/hal-02382941},
    BOOKTITLE = {{STACOM 2019 - 10th Workshop on Statistical Atlases and Computational Modelling of the Heart}},
    ADDRESS = {Shenzhen, China},
    YEAR = {2019},
    MONTH = Oct,
    KEYWORDS = {Cardiac modelling ; Machine learning ; Pulmonary hypertension},
    PDF = {https://hal.inria.fr/hal-02382941/file/stacom_2019.pdf},
    HAL_ID = {hal-02382941},
    HAL_VERSION = {v1},
    
    }
    


Patents, standards

  1. Julian Krebs, Hervé Delingette, Nicholas Ayache, Tommaso Mansi, and Shun Miao. Medical Imaging Diffeomorphic Registration based on Machine Learning. US 2019/0205766 A1, United States, July 2019.
    @patent{krebs:hal-02185900,
    TITLE = {{Medical Imaging Diffeomorphic Registration based on Machine Learning}},
    AUTHOR = {Krebs, Julian and Delingette, Herv{\'e} and Ayache, Nicholas and Mansi, Tommaso and Miao, Shun},
    url-hal= {https://hal.inria.fr/hal-02185900},
    NUMBER = {US 2019/0205766 A1},
    ADDRESS = {United States},
    YEAR = {2019},
    MONTH = Jul,
    HAL_ID = {hal-02185900},
    HAL_VERSION = {v1},
    
    }
    


Miscellaneous

  1. Valeria Manera, Luigi Antelmi, Radia Zeghari, Nicholas Ayache, Marco Lorenzi, and Philippe Robert. Prevalence of lack of interest and anhedonia in the general population of the UK Biobank. AAIC 2019 - Alzheimer's Association International Conference, July 2019. Note: Poster.
    @misc{manera:hal-02174565,
    TITLE = {{Prevalence of lack of interest and anhedonia in the general population of the UK Biobank}},
    AUTHOR = {Manera, Valeria and Antelmi, Luigi and Zeghari, Radia and Ayache, Nicholas and Lorenzi, Marco and Robert, Philippe},
    url-hal= {https://hal.inria.fr/hal-02174565},
    NOTE = {Poster},
    HOWPUBLISHED = {{AAIC 2019 - Alzheimer's Association International Conference}},
    YEAR = {2019},
    MONTH = Jul,
    PDF = {https://hal.inria.fr/hal-02174565/file/UKB-V2.pdf},
    HAL_ID = {hal-02174565},
    HAL_VERSION = {v1},
    
    }
    


  2. Radia Zeghari, Philippe Robert, Valeria Manera, Marco Lorenzi, and Alexandra König. Towards a Multidimensional Assessment of Apathy in Neurocognitive Disorders. AAIC 2019 - Alzheimer's Association International Conference, July 2019. Note: Poster.
    @misc{zeghari:hal-02339152,
    TITLE = {{Towards a Multidimensional Assessment of Apathy in Neurocognitive Disorders}},
    AUTHOR = {Zeghari, Radia and Robert, Philippe and Manera, Valeria and Lorenzi, Marco and K{\"o}nig, Alexandra},
    url-hal= {https://hal.archives-ouvertes.fr/hal-02339152},
    NOTE = {Poster},
    HOWPUBLISHED = {{AAIC 2019 - Alzheimer's Association International Conference}},
    VOLUME = {15},
    NUMBER = {7},
    PAGES = {569},
    YEAR = {2019},
    MONTH = Jul,
    DOI = {10.1016/j.jalz.2019.06.4514},
    HAL_ID = {hal-02339152},
    HAL_VERSION = {v1},
    
    }
    


  3. Nina Miolane, Johan Mathe, Claire Donnat, Mikael Jorda, and Xavier Pennec. geomstats: a Python Package for Riemannian Geometry in Machine Learning. Note: Preprint NIPS2018, January 2019.
    @unpublished{miolane:hal-01974572,
    TITLE = {{geomstats: a Python Package for Riemannian Geometry in Machine Learning}},
    AUTHOR = {Miolane, Nina and Mathe, Johan and Donnat, Claire and Jorda, Mikael and Pennec, Xavier},
    url-hal= {https://hal.inria.fr/hal-01974572},
    NOTE = {Preprint NIPS2018},
    YEAR = {2019},
    MONTH = Jan,
    HAL_ID = {hal-01974572},
    HAL_VERSION = {v1},
    
    }
    


  4. Xavier Pennec. Curvature effects on the empirical mean in Riemannian and affine Manifolds: a non-asymptotic high concentration expansion in the small-sample regime. Note: Working paper or preprint, June 2019. Keyword(s): empirical mean, affine connection manifold, non-asymptotic estimation, Fréchet means, curvature, Riemannian manifold.
    @unpublished{pennec:hal-02157952,
    TITLE = {{Curvature effects on the empirical mean in Riemannian and affine Manifolds: a non-asymptotic high concentration expansion in the small-sample regime}},
    AUTHOR = {Pennec, Xavier},
    url-hal= {https://hal.inria.fr/hal-02157952},
    NOTE = {working paper or preprint},
    YEAR = {2019},
    MONTH = Jun,
    KEYWORDS = {empirical mean ; affine connection manifold ; non-asymptotic estimation ; Fr{\'e}chet means ; curvature ; Riemannian manifold},
    PDF = {https://hal.inria.fr/hal-02157952/file/CurvatureAndEmpiricalFrechetMean.pdf},
    HAL_ID = {hal-02157952},
    HAL_VERSION = {v1},
    
    }
    


  5. Qiao Zheng, Hervé Delingette, Kenneth Fung, Steffen E Petersen, and Nicholas Ayache. Unsupervised shape and motion analysis of 3822 cardiac 4D MRIs of UK Biobank. Note: Working paper or preprint, February 2019. Keyword(s): Cardiac pathology, Cardiac motion, Cluster analysis, UK Biobank, Feature extraction, Gaussian mixture model, Cine MRI.
    @unpublished{zheng:hal-02043380,
    TITLE = {{Unsupervised shape and motion analysis of 3822 cardiac 4D MRIs of UK Biobank}},
    AUTHOR = {Zheng, Qiao and Delingette, Herv{\'e} and Fung, Kenneth and Petersen, Steffen E and Ayache, Nicholas},
    url-hal= {https://hal.inria.fr/hal-02043380},
    NOTE = {working paper or preprint},
    YEAR = {2019},
    MONTH = Feb,
    KEYWORDS = {Cardiac pathology ; Cardiac motion ; Cluster analysis ; UK Biobank ; Feature extraction ; Gaussian mixture model ; Cine MRI},
    PDF = {https://hal.inria.fr/hal-02043380/file/1902.05811.pdf},
    HAL_ID = {hal-02043380},
    HAL_VERSION = {v1},
    
    }
    



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Last modified: Fri Aug 7 12:30:04 2020
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