-
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): Stochastic variational inference,
Clinical trials,
Bayesian modeling,
Alzheimer's disease,
Disease progression modeling,
Gaussian Process.
@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.science/hal-02051843},
JOURNAL = {{NeuroImage}},
PUBLISHER = {{Elsevier}},
YEAR = {2019},
KEYWORDS = {Stochastic variational inference ; Clinical trials ; Bayesian modeling ; Alzheimer's disease ; Disease progression modeling ; Gaussian Process},
PDF = {https://hal.science/hal-02051843v3/file/revised_manuscript.pdf},
HAL_ID = {hal-02051843},
HAL_VERSION = {v3},
}
-
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://inria.hal.science/hal-02395747},
JOURNAL = {{Proceedings of Machine Learning Research}},
PUBLISHER = {{PMLR}},
SERIES = {Proceedings of ICML 2019},
NUMBER = {97},
PAGES = {302--311},
YEAR = {2019},
PDF = {https://inria.hal.science/hal-02395747/file/antelmi19.pdf},
HAL_ID = {hal-02395747},
HAL_VERSION = {v1},
}
-
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://inria.hal.science/hal-02404520},
JOURNAL = {{ERCIM News}},
PUBLISHER = {{ERCIM}},
NUMBER = {118},
PAGES = {4-5},
YEAR = {2019},
MONTH = Jul,
HAL_ID = {hal-02404520},
HAL_VERSION = {v1},
}
-
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.science/hal-01835074},
JOURNAL = {{Computational Statistics and Data Analysis}},
PUBLISHER = {{Elsevier}},
VOLUME = {137},
PAGES = {247-270},
YEAR = {2019},
PDF = {https://hal.science/hal-01835074/file/LTBMpaper.pdf},
HAL_ID = {hal-01835074},
HAL_VERSION = {v1},
}
-
Christian Callegari,
Marco Milanesio,
and Pietro Michiardi.
Network level perspective in web sessions troubleshooting.
International Journal of Communication Systems,
32(6):e3908,
April 2019.
@article{callegari:hal-03477646,
TITLE = {{Network level perspective in web sessions troubleshooting}},
AUTHOR = {Callegari, Christian and Milanesio, Marco and Michiardi, Pietro},
url-hal= {https://inria.hal.science/hal-03477646},
JOURNAL = {{International Journal of Communication Systems}},
PUBLISHER = {{Wiley}},
VOLUME = {32},
NUMBER = {6},
PAGES = {e3908},
YEAR = {2019},
MONTH = Apr,
DOI = {10.1002/dac.3908},
HAL_ID = {hal-03477646},
HAL_VERSION = {v1},
}
-
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,
May 2019.
Keyword(s): Molecular,
Glioma,
Neuro-radiology,
Insula,
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://univ-rennes.hal.science/hal-02076599},
JOURNAL = {{Journal of Neuro-Oncology}},
PUBLISHER = {{Springer Verlag}},
VOLUME = {142},
NUMBER = {3},
PAGES = {511-520},
YEAR = {2019},
MONTH = May,
DOI = {10.1007/s11060-019-03122-1},
KEYWORDS = {Molecular ; Glioma ; Neuro-radiology ; Insula ; Perfusion},
HAL_ID = {hal-02076599},
HAL_VERSION = {v1},
}
-
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): Clustering,
Thalamus,
Spatiotemporal geodesic regression,
Parallel transport,
Computational anatomy,
Shape analysis.
@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://inserm.hal.science/inserm-01958916},
JOURNAL = {{NeuroImage}},
PUBLISHER = {{Elsevier}},
VOLUME = {188},
PAGES = {282-290},
YEAR = {2019},
MONTH = Mar,
DOI = {10.1016/j.neuroimage.2018.11.063},
KEYWORDS = {Clustering ; Thalamus ; Spatiotemporal geodesic regression ; Parallel transport ; Computational anatomy ; Shape analysis},
PDF = {https://inserm.hal.science/inserm-01958916/file/Spatio_temporal_analysis_GENFI_lastSub_black.pdf},
HAL_ID = {inserm-01958916},
HAL_VERSION = {v1},
}
-
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.
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://inria.hal.science/hal-02270604},
JOURNAL = {{Cahiers de l'audition}},
PUBLISHER = {{Elsevier}},
VOLUME = {32},
NUMBER = {4},
PAGES = {36-40},
YEAR = {2019},
MONTH = Jul,
HAL_ID = {hal-02270604},
HAL_VERSION = {v1},
}
-
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://inria.hal.science/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},
}
-
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): tumor mutational burden,
FoundationOne assay,
Oncomine TML assay,
lung cancer,
melanoma,
immunotherapy.
@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://inria.hal.science/hal-02381188},
JOURNAL = {{Cancers}},
PUBLISHER = {{MDPI}},
VOLUME = {11},
YEAR = {2019},
DOI = {10.3390/cancers11091271},
KEYWORDS = {tumor mutational burden ; FoundationOne assay ; Oncomine TML assay ; lung cancer ; melanoma ; immunotherapy},
PDF = {https://inria.hal.science/hal-02381188/file/cancers-11-01271-v2%281%29.pdf},
HAL_ID = {hal-02381188},
HAL_VERSION = {v1},
}
-
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://inria.hal.science/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},
PDF = {https://inria.hal.science/hal-02446712/file/S0242649819300197.pdf},
HAL_ID = {hal-02446712},
HAL_VERSION = {v1},
}
-
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): education,
elderly,
optimization,
research,
well-being,
aging,
cancer.
@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://inria.hal.science/hal-02045442},
JOURNAL = {{Cancers}},
PUBLISHER = {{MDPI}},
VOLUME = {11},
NUMBER = {2},
PAGES = {1-11},
YEAR = {2019},
MONTH = Feb,
DOI = {10.3390/cancers11020250},
KEYWORDS = {education ; elderly ; optimization ; research ; well-being ; aging ; cancer},
PDF = {https://inria.hal.science/hal-02045442/file/cancers-11-00250.pdf},
HAL_ID = {hal-02045442},
HAL_VERSION = {v1},
}
-
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): deformable registration,
deformation transport,
latent variable model,
probabilistic encoding,
conditional variational autoencoder,
deep learning.
@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.science/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 = {deformable registration ; deformation transport ; latent variable model ; probabilistic encoding ; conditional variational autoencoder ; deep learning},
PDF = {https://hal.science/hal-01978339/file/author_files.pdf},
HAL_ID = {hal-01978339},
HAL_VERSION = {v1},
}
-
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,
Segmentation,
3D Convolutional Neural Networks,
Ensembles of models.
@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://inria.hal.science/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 ; Segmentation ; 3D Convolutional Neural Networks ; Ensembles of models},
PDF = {https://inria.hal.science/hal-01883716v2/file/Pawel_Mlynarski_segmentation.pdf},
HAL_ID = {hal-01883716},
HAL_VERSION = {v2},
}
-
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): Semi-supervised learning,
tumor,
segmentation,
Convolutional Neural Networks,
Convolutional N...,
Semi-supervised...,
MRI.
@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://inria.hal.science/hal-01952458},
JOURNAL = {{Journal of Medical Imaging}},
PUBLISHER = {{SPIE Digital Library}},
YEAR = {2019},
MONTH = Jul,
DOI = {10.1117/1.JMI.6.3.034002},
KEYWORDS = {Semi-supervised learning ; tumor ; segmentation ; Convolutional Neural Networks ; Convolutional N... ; Semi-supervised... ; MRI},
PDF = {https://inria.hal.science/hal-01952458/file/Pawel_Mlynarski_Mixed_Supervision_ArXiv.pdf},
HAL_ID = {hal-01952458},
HAL_VERSION = {v1},
}
-
Roch Molléro,
Xavier Pennec,
Hervé Delingette,
Nicholas Ayache,
and Maxime Sermesant.
Population-based priors in cardiac model personalisation for consistent parameter estimation in heterogeneous databases.
International Journal for Numerical Methods in Biomedical Engineering,
35(2):e3158,
February 2019.
Keyword(s): Cardiac Electromechanical Modeling,
Parameter Estimation,
Personalised modeling,
Parameter Selection.
@article{mollero:hal-01922719,
TITLE = {{Population-based priors in cardiac model personalisation for consistent parameter estimation in heterogeneous databases}},
AUTHOR = {Moll{\'e}ro, Roch and Pennec, Xavier and Delingette, Herv{\'e} and Ayache, Nicholas and Sermesant, Maxime},
url-hal= {https://inria.hal.science/hal-01922719},
JOURNAL = {{International Journal for Numerical Methods in Biomedical Engineering}},
PUBLISHER = {{John Wiley and Sons}},
VOLUME = {35},
NUMBER = {2},
PAGES = {e3158},
YEAR = {2019},
MONTH = Feb,
DOI = {10.1002/cnm.3158},
KEYWORDS = {Cardiac Electromechanical Modeling ; Parameter Estimation ; Personalised modeling ; Parameter Selection},
PDF = {https://inria.hal.science/hal-01922719/file/Special_Issue___Longitudinal_with_Priors_Refactoring-3.pdf},
HAL_ID = {hal-01922719},
HAL_VERSION = {v1},
}
-
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://inria.hal.science/hal-02404530},
JOURNAL = {{ERCIM News}},
PUBLISHER = {{ERCIM}},
NUMBER = {118},
PAGES = {7-8},
YEAR = {2019},
MONTH = Jul,
HAL_ID = {hal-02404530},
HAL_VERSION = {v1},
}
-
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.science/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.science/hal-02401340/file/radiol.2019182023.pdf},
HAL_ID = {hal-02401340},
HAL_VERSION = {v1},
}
-
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://inria.hal.science/hal-02404534},
JOURNAL = {{ERCIM News}},
PUBLISHER = {{ERCIM}},
NUMBER = {118},
PAGES = {10-11},
YEAR = {2019},
MONTH = Jul,
HAL_ID = {hal-02404534},
HAL_VERSION = {v1},
}
-
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): Imaging biomarkers,
Aging,
Spatio-temporal model,
Brain morphology,
Deformations,
Alzheimer's disease.
@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://inria.hal.science/hal-01948174},
JOURNAL = {{NeuroImage}},
PUBLISHER = {{Elsevier}},
VOLUME = {198},
PAGES = {255-270},
YEAR = {2019},
MONTH = Sep,
DOI = {10.1016/j.neuroimage.2019.05.040},
KEYWORDS = {Imaging biomarkers ; Aging ; Spatio-temporal model ; Brain morphology ; Deformations ; Alzheimer's disease},
PDF = {https://inria.hal.science/hal-01948174v3/file/paper-stripped.pdf},
HAL_ID = {hal-01948174},
HAL_VERSION = {v3},
}
-
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): Wall thickness,
Isthmus,
High-resolution mapping,
Contrart-enhanced multidetector computed tomography,
MUSIC,
Myocardial infarction,
Ventricular tachycardia.
@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://inria.hal.science/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 = {Wall thickness ; Isthmus ; High-resolution mapping ; Contrart-enhanced multidetector computed tomography ; MUSIC ; Myocardial infarction ; Ventricular tachycardia},
PDF = {https://inria.hal.science/hal-02181776/file/S1547527119305570.pdf},
HAL_ID = {hal-02181776},
HAL_VERSION = {v1},
}
-
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,
58(101546),
December 2019.
Keyword(s): Multimodal MRI,
PET Imaging,
Adversarial Training,
Multiple Sclerosis.
@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.science/hal-02276634},
JOURNAL = {{Medical Image Analysis}},
PUBLISHER = {{Elsevier}},
VOLUME = {58},
NUMBER = {101546},
YEAR = {2019},
MONTH = Dec,
DOI = {10.1016/j.media.2019.101546},
KEYWORDS = {Multimodal MRI ; PET Imaging ; Adversarial Training ; Multiple Sclerosis},
PDF = {https://hal.science/hal-02276634/file/medima-hal_version.pdf},
HAL_ID = {hal-02276634},
HAL_VERSION = {v1},
}
-
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://inria.hal.science/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://inria.hal.science/hal-02042526v2/file/article.pdf},
HAL_ID = {hal-02042526},
HAL_VERSION = {v2},
}
-
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): Anatomy,
Cochlea,
Inner ear,
Morphology,
Semicircular canals,
Vestibule.
@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://inria.hal.science/hal-02402404},
JOURNAL = {{Data in Brief}},
PUBLISHER = {{Elsevier}},
VOLUME = {27},
PAGES = {104782},
YEAR = {2019},
MONTH = Dec,
DOI = {10.1016/j.dib.2019.104782},
KEYWORDS = {Anatomy ; Cochlea ; Inner ear ; Morphology ; Semicircular canals ; Vestibule},
HAL_ID = {hal-02402404},
HAL_VERSION = {v1},
}
-
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): Deep learn- ing,
Cine MRI,
Classifi-cation,
Motion,
Semi-supervised learning,
Deep learn-ing,
Cardiac pathology,
Neural network,
Apparent flow,
Classifi- cation.
@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://inria.hal.science/hal-01975880},
JOURNAL = {{Medical Image Analysis}},
PUBLISHER = {{Elsevier}},
VOLUME = {56},
PAGES = {80-95},
YEAR = {2019},
DOI = {10.1016/j.media.2019.06.001},
KEYWORDS = {Deep learn- ing ; Cine MRI ; Classifi-cation ; Motion ; Semi-supervised learning ; Deep learn-ing ; Cardiac pathology ; Neural network ; Apparent flow ; Classifi- cation},
PDF = {https://inria.hal.science/hal-01975880v2/file/1811.03433.pdf},
HAL_ID = {hal-01975880},
HAL_VERSION = {v2},
}
-
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://inria.hal.science/hal-02154181},
BOOKTITLE = {{ICML 2019 - 36th International Conference on Machine Learning}},
ADDRESS = {Long Beach, United States},
YEAR = {2019},
MONTH = Jun,
PDF = {https://inria.hal.science/hal-02154181/file/antelmi19a.pdf},
HAL_ID = {hal-02154181},
HAL_VERSION = {v1},
}
-
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,
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://inria.hal.science/hal-02265131},
BOOKTITLE = {{MICCAI 2019 - 22nd International Conference on Medical Image Computing and Computer Assisted Intervention}},
ADDRESS = {Shenzhen, China},
YEAR = {2019},
MONTH = Oct,
KEYWORDS = {Image segmentation ; Bayesian learning ; Quality control},
PDF = {https://inria.hal.science/hal-02265131/file/paper2106.pdf},
HAL_ID = {hal-02265131},
HAL_VERSION = {v1},
}
-
Nicholas Ayache.
AI and Healthcare: towards a Digital Twin?.
In 5th International Symposium on Multidiscplinary Computational Anatomy,
Fukuoka, Japan,
March 2019.
Note: Talk given by M. Nicholas Ayache at the MCA 2019.
@inproceedings{ayache:hal-02063234,
TITLE = {{AI and Healthcare: towards a Digital Twin?}},
AUTHOR = {Ayache, Nicholas},
url-hal= {https://inria.hal.science/hal-02063234},
NOTE = {Talk given by M. Nicholas Ayache at the MCA 2019},
BOOKTITLE = {{5th International Symposium on Multidiscplinary Computational Anatomy}},
ADDRESS = {Fukuoka, Japan},
YEAR = {2019},
MONTH = Mar,
PDF = {https://inria.hal.science/hal-02063234/file/Ayache_invited_talk_MCA_FY2019.pdf},
HAL_ID = {hal-02063234},
HAL_VERSION = {v1},
}
-
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://inria.hal.science/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://inria.hal.science/hal-02106618/file/LearningModel_FIMH_2019%285%29.pdf},
HAL_ID = {hal-02106618},
HAL_VERSION = {v1},
}
-
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): ECGI,
Deep learning,
Generative Model,
Simulation.
@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://inria.hal.science/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 = {ECGI ; Deep learning ; Generative Model ; Simulation},
PDF = {https://inria.hal.science/hal-02108958v2/file/tania_fimh.pdf},
HAL_ID = {hal-02108958},
HAL_VERSION = {v2},
}
-
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://inria.hal.science/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://inria.hal.science/hal-02361466/file/FIMH_Jaume_2019_Updated.pdf},
HAL_ID = {hal-02361466},
HAL_VERSION = {v1},
}
-
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,
Segmentation,
Deep learning,
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://inria.hal.science/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 ; Segmentation ; Deep learning ; Imaging},
PDF = {https://inria.hal.science/hal-02106609/file/cedilnik_fimh2019%287%29.pdf},
HAL_ID = {hal-02106609},
HAL_VERSION = {v1},
}
-
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://inria.hal.science/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},
}
-
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): Electrophysiology,
Computer model,
Personalisation,
Cardiac resynchronisation therapy.
@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://inria.hal.science/hal-02368288},
BOOKTITLE = {{STACOM 2019 - 10th Workshop on Statistical Atlases and Computational Modelling of the Heart}},
ADDRESS = {Shenzen, China},
YEAR = {2019},
MONTH = Oct,
KEYWORDS = {Electrophysiology ; Computer model ; Personalisation ; Cardiac resynchronisation therapy},
PDF = {https://inria.hal.science/hal-02368288/file/cedilnik_stacom2019.pdf},
HAL_ID = {hal-02368288},
HAL_VERSION = {v1},
}
-
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://inria.hal.science/hal-02429678},
BOOKTITLE = {{STACOM 2019: Statistical Atlases and Computational Models of the Heart}},
ADDRESS = {Shenzhen, China},
YEAR = {2019},
MONTH = Oct,
PDF = {https://inria.hal.science/hal-02429678/file/STACOM_FinalVersion.pdf},
HAL_ID = {hal-02429678},
HAL_VERSION = {v1},
}
-
Sara Garbarino and Marco Lorenzi.
Modeling and inference of spatio-temporal protein dynamics across brain networks.
In IPMI 2019 - International Conference on Information Processing in Medical Imaging,
volume 11492 of Lecture Notes in Computer Science book series,
Hong Kong, Hong Kong SAR China,
pages 57-69,
June 2019.
springer.
Note: Bayesian non--parametric model, protein propagation, Alzheimer'sdisease, Gaussian process, dynamical systems, spatio--temporal model, disease progression modeling.
@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://inria.hal.science/hal-02165021},
NOTE = {Bayesian non--parametric model, protein propagation, Alzheimer'sdisease, Gaussian process, dynamical systems, spatio--temporal model, disease progression modeling},
BOOKTITLE = {{IPMI 2019 - International Conference on Information Processing in Medical Imaging}},
ADDRESS = {Hong Kong, Hong Kong SAR China},
PUBLISHER = {{springer}},
SERIES = {Lecture Notes in Computer Science book series},
VOLUME = {11492},
PAGES = {57-69},
YEAR = {2019},
MONTH = Jun,
PDF = {https://inria.hal.science/hal-02165021/file/IPMI_01-10-2018.pdf},
HAL_ID = {hal-02165021},
HAL_VERSION = {v1},
}
-
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): Symmetric Spaces,
Parallel Transport,
Shape Registration.
@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://inria.hal.science/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 = {Symmetric Spaces ; Parallel Transport ; Shape Registration},
PDF = {https://inria.hal.science/hal-02148832/file/55-Guigui.pdf},
HAL_ID = {hal-02148832},
HAL_VERSION = {v1},
}
-
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://inria.hal.science/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://inria.hal.science/hal-02239318v2/file/stacom_2019_final.pdf},
HAL_ID = {hal-02239318},
HAL_VERSION = {v2},
}
-
Georgios Lazaridis,
Marco Lorenzi,
Sebastien Ourselin,
and David Garway-Heath.
Enhancing OCT Signal by Fusion of GANs: Improving Statistical Power of Glaucoma Clinical Trials.
In MICAI 2019 - 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention,
volume LNCS. LNIP - 11764 of Medical Image Computing and Computer Assisted Intervention -- MICCAI 2019,
Shenzhen, China,
pages 3-11,
October 2019.
Springer International Publishing.
@inproceedings{lazaridis:hal-03374557,
TITLE = {{Enhancing OCT Signal by Fusion of GANs: Improving Statistical Power of Glaucoma Clinical Trials}},
AUTHOR = {Lazaridis, Georgios and Lorenzi, Marco and Ourselin, Sebastien and Garway-Heath, David},
url-hal= {https://inria.hal.science/hal-03374557},
BOOKTITLE = {{MICAI 2019 - 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention}},
ADDRESS = {Shenzhen, China},
PUBLISHER = {{Springer International Publishing}},
SERIES = {Medical Image Computing and Computer Assisted Intervention -- MICCAI 2019},
VOLUME = {LNCS. LNIP - 11764},
PAGES = {3-11},
YEAR = {2019},
MONTH = Oct,
DOI = {10.1007/978-3-030-32239-7\_1},
HAL_ID = {hal-03374557},
HAL_VERSION = {v1},
}
-
Alexandre Legay,
Thomas Tiennot,
Jean-François Gelly,
Maxime Sermesant,
and Jean Bulté.
End-to-end Cardiac Ultrasound Simulation for a Better Understanding of Image Quality.
In STACOM 2019 - 10th International Workshop on Statistical Atlases and Computational Models of the Heart: Atrial Segmentation and LV Quantification Challenges,
volume LNCS. LNIP - 12009 of Statistical Atlases and Computational Models of the Heart. Multi-Sequence CMR Segmentation, CRT-EPiggy and LV Full Quantification Challenges,
Shenzhen, China,
pages 167-175,
October 2019.
Springer International Publishing.
Keyword(s): Ultrasound,
Cardiac Modelling,
Probe Design,
Image Quality.
@inproceedings{legay:hal-03687459,
TITLE = {{End-to-end Cardiac Ultrasound Simulation for a Better Understanding of~Image Quality}},
AUTHOR = {Legay, Alexandre and Tiennot, Thomas and Gelly, Jean-Fran{\c c}ois and Sermesant, Maxime and Bult{\'e}, Jean},
url-hal= {https://inria.hal.science/hal-03687459},
BOOKTITLE = {{STACOM 2019 - 10th International Workshop on Statistical Atlases and Computational Models of the Heart: Atrial Segmentation and LV Quantification Challenges}},
ADDRESS = {Shenzhen, China},
PUBLISHER = {{Springer International Publishing}},
SERIES = {Statistical Atlases and Computational Models of the Heart. Multi-Sequence CMR Segmentation, CRT-EPiggy and LV Full Quantification Challenges},
VOLUME = {LNCS. LNIP - 12009},
PAGES = {167-175},
YEAR = {2019},
MONTH = Oct,
DOI = {10.1007/978-3-030-39074-7\_18},
KEYWORDS = {Ultrasound ; Cardiac Modelling ; Probe Design ; Image Quality},
PDF = {https://inria.hal.science/hal-03687459/file/Article_STACOM_authors_version.pdf},
HAL_ID = {hal-03687459},
HAL_VERSION = {v1},
}
-
Buntheng Ly,
Hubert Cochet,
and Maxime Sermesant.
Style Data Augmentation for Robust Segmentation of Multi-Modality Cardiac MRI.
In STACOM 2019 - 10th Workhop on 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://inria.hal.science/hal-02401643},
BOOKTITLE = {{STACOM 2019 - 10th Workhop on 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://inria.hal.science/hal-02401643v3/file/stacom_ms_seg_hal.pdf},
HAL_ID = {hal-02401643},
HAL_VERSION = {v3},
}
-
R azvan Marinescu,
Marco Lorenzi,
Stefano Blumberg,
Alexandra Young,
Pere Planell-Morell,
Neil Oxtoby,
Arman Eshaghi,
Keir Yong,
Sebastian Crutch,
Polina Golland,
and Daniel Alexander.
Disease Knowledge Transfer Across Neurodegenerative Diseases.
In MICCAI 2019 - 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention,
volume LNCS. LNIP - 11765 of Medical Image Computing and Computer Assisted Intervention -- MICCAI 2019,
Shenzhen, China,
pages 860-868,
October 2019.
Springer International Publishing.
@inproceedings{marinescu:hal-03374569,
TITLE = {{Disease Knowledge Transfer Across Neurodegenerative Diseases}},
AUTHOR = {Marinescu, R{\u a}zvan and Lorenzi, Marco and Blumberg, Stefano and Young, Alexandra and Planell-Morell, Pere and Oxtoby, Neil and Eshaghi, Arman and Yong, Keir and Crutch, Sebastian and Golland, Polina and Alexander, Daniel},
url-hal= {https://inria.hal.science/hal-03374569},
BOOKTITLE = {{MICCAI 2019 - 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention}},
ADDRESS = {Shenzhen, China},
PUBLISHER = {{Springer International Publishing}},
SERIES = {Medical Image Computing and Computer Assisted Intervention -- MICCAI 2019},
VOLUME = {LNCS. LNIP - 11765},
PAGES = {860-868},
YEAR = {2019},
MONTH = Oct,
DOI = {10.1007/978-3-030-32245-8\_95},
HAL_ID = {hal-03374569},
HAL_VERSION = {v1},
}
-
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.science/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},
}
-
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.science/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},
}
-
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): Dually flat connections,
SPD matrices,
Information geometry.
@inproceedings{thanwerdas:hal-02158525,
TITLE = {{Exploration of Balanced Metrics on Symmetric Positive Definite Matrices}},
AUTHOR = {Thanwerdas, Yann and Pennec, Xavier},
url-hal= {https://hal.science/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 = {Dually flat connections ; SPD matrices ; Information geometry},
PDF = {https://hal.science/hal-02158525/file/Thanwerdas_GSI19_Balanced%20metrics.pdf},
HAL_ID = {hal-02158525},
HAL_VERSION = {v1},
}
-
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): SPD matrices,
Riemannian symmetric spaces.
@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.science/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 = {SPD matrices ; Riemannian symmetric spaces},
PDF = {https://hal.science/hal-02147020/file/main.pdf},
HAL_ID = {hal-02147020},
HAL_VERSION = {v1},
}
-
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://inria.hal.science/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://inria.hal.science/hal-02196557/file/paper2371.pdf},
HAL_ID = {hal-02196557},
HAL_VERSION = {v1},
}
-
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://inria.hal.science/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},
}
-
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://inria.hal.science/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://inria.hal.science/hal-02382941/file/stacom_2019.pdf},
HAL_ID = {hal-02382941},
HAL_VERSION = {v1},
}