-
Vincenzo Carbone,
Irene Balelli,
Yves Coudière,
Oscar Camara,
Beatriz Trenor,
Michèle Barbier,
and Maxime Sermesant.
A cloud-based platform for seamless digital testing of cardiac medical devices and drugs.
The Project Repository Journal,
24(1):144-148,
August 2025.
@article{carbone:hal-05400535,
TITLE = {{A cloud-based platform for seamless digital testing of cardiac medical devices and drugs}},
AUTHOR = {Carbone, Vincenzo and Balelli, Irene and Coudi{\`e}re, Yves and Camara, Oscar and Trenor, Beatriz and Barbier, Mich{\`e}le and Sermesant, Maxime},
url-hal= {https://inria.hal.science/hal-05400535},
JOURNAL = {{The Project Repository Journal}},
PUBLISHER = {{EDMA}},
VOLUME = {24},
NUMBER = {1},
PAGES = {144-148},
YEAR = {2025},
MONTH = Aug,
DOI = {10.54050/PRJ2423681},
PDF = {https://inria.hal.science/hal-05400535v1/file/PRj24%20SimCardioTest_01.pdf},
HAL_ID = {hal-05400535},
HAL_VERSION = {v1},
}
-
Adrià Casamitjana,
Matteo Mancini,
Eleanor Robinson,
Loïc Peter,
Roberto Annunziata,
Juri Althonayan,
Shauna Crampsie,
Emily Blackburn,
Benjamin Billot,
Alessia Atzeni,
Oula Puonti,
Yaël Balbastre,
Peter Schmidt,
James Hughes,
Jean Augustinack,
Brian Edlow,
Lilla Zöllei,
David Thomas,
Dorit Kliemann,
Martina Bocchetta,
Catherine Strand,
Janice Holton,
Zane Jaunmuktane,
and Juan Eugenio Iglesias.
A probabilistic histological atlas of the human brain for MRI segmentation.
Nature,
(648):678-685,
November 2025.
Keyword(s): Brain atlas,
MRI,
segmentation,
registration.
@article{casamitjana:hal-05384226,
TITLE = {{A probabilistic histological atlas of the human brain for MRI segmentation}},
AUTHOR = {Casamitjana, Adri{\`a} and Mancini, Matteo and Robinson, Eleanor and Peter, Lo{\"i}c and Annunziata, Roberto and Althonayan, Juri and Crampsie, Shauna and Blackburn, Emily and Billot, Benjamin and Atzeni, Alessia and Puonti, Oula and Balbastre, Ya{\"e}l and Schmidt, Peter and Hughes, James and Augustinack, Jean and Edlow, Brian and Z{\"o}llei, Lilla and Thomas, David and Kliemann, Dorit and Bocchetta, Martina and Strand, Catherine and Holton, Janice and Jaunmuktane, Zane and Iglesias, Juan Eugenio},
url-hal= {https://hal.science/hal-05384226},
JOURNAL = {{Nature}},
PUBLISHER = {{Nature Publishing Group}},
NUMBER = {648},
PAGES = {678--685},
YEAR = {2025},
MONTH = Nov,
DOI = {10.1038/s41586-025-09708-2},
KEYWORDS = {Brain atlas ; MRI ; segmentation ; registration},
PDF = {https://hal.science/hal-05384226v2/file/s41586-025-09708-2.pdf},
HAL_ID = {hal-05384226},
HAL_VERSION = {v2},
}
-
Andrea Chierici,
Lisa Guzzi,
Sebastien Goffart,
Nizar Kamoun,
Manuel Gargiulo,
Patrick Chevallier,
Antonio Iannelli,
Rodolphe Anty,
Hervé Delingette,
Fabien Lareyre,
and Juliette Raffort.
Fully Automatic Artificial Intelligence Liver Anatomy Segmentation in the Management of Colorectal Liver Metastases.
Cureus Journal of Medical Science,
June 2025.
Keyword(s): deep learning artificial intelligence,
hepato-biliary-pancreatic surgery,
nnu-net,
oncological general surgery.,
colorectal cancer liver metastases.
@article{chierici:hal-05470387,
TITLE = {{Fully Automatic Artificial Intelligence Liver Anatomy Segmentation in the Management of Colorectal Liver Metastases}},
AUTHOR = {Chierici, Andrea and Guzzi, Lisa and Goffart, Sebastien and Kamoun, Nizar and Gargiulo, Manuel and Chevallier, Patrick and Iannelli, Antonio and Anty, Rodolphe and Delingette, Herv{\'e} and Lareyre, Fabien and Raffort, Juliette},
url-hal= {https://inria.hal.science/hal-05470387},
JOURNAL = {{Cureus Journal of Medical Science}},
PUBLISHER = {{Cureus, Inc.}},
YEAR = {2025},
MONTH = Jun,
DOI = {10.7759/cureus.86072},
KEYWORDS = {deep learning artificial intelligence ; hepato-biliary-pancreatic surgery ; nnu-net ; oncological general surgery. ; colorectal cancer liver metastases},
HAL_ID = {hal-05470387},
HAL_VERSION = {v1},
}
-
Andrea Chierici,
Fabien Lareyre,
Antonio Iannelli,
Benjamin Salucki,
Sébastien Goffart,
Lisa Guzzi,
Elise Poggi,
Hervé Delingette,
and Juliette Raffort.
Applications of artificial intelligence in liver cancer: A scoping review.
Artificial Intelligence in Medicine,
169:103244,
November 2025.
@article{chierici:hal-05470363,
TITLE = {{Applications of artificial intelligence in liver cancer: A scoping review}},
AUTHOR = {Chierici, Andrea and Lareyre, Fabien and Iannelli, Antonio and Salucki, Benjamin and Goffart, S{\'e}bastien and Guzzi, Lisa and Poggi, Elise and Delingette, Herv{\'e} and Raffort, Juliette},
url-hal= {https://inria.hal.science/hal-05470363},
JOURNAL = {{Artificial Intelligence in Medicine}},
PUBLISHER = {{Elsevier}},
VOLUME = {169},
PAGES = {103244},
YEAR = {2025},
MONTH = Nov,
DOI = {10.1016/j.artmed.2025.103244},
HAL_ID = {hal-05470363},
HAL_VERSION = {v1},
}
-
Marco Corneli,
Elena Erosheva,
Xunlei Qian,
and Marco Lorenzi.
A Bayesian approach for clustering and exact finite-sample model selection in longitudinal data mixtures.
Computational Statistics,
40:509-545,
2025.
Keyword(s): Longitudinal Data,
Mixture Models,
Bayesian Model Selection.
@article{corneli:hal-02310069,
TITLE = {{A Bayesian approach for clustering and exact finite-sample model selection in longitudinal data mixtures}},
AUTHOR = {Corneli, Marco and Erosheva, Elena and Qian, Xunlei and Lorenzi, Marco},
url-hal= {https://hal.science/hal-02310069},
JOURNAL = {{Computational Statistics}},
PUBLISHER = {{Springer Verlag}},
VOLUME = {40},
PAGES = {509--545},
YEAR = {2025},
DOI = {10.1007/s00180-024-01501-5},
KEYWORDS = {Longitudinal Data ; Mixture Models ; Bayesian Model Selection},
PDF = {https://hal.science/hal-02310069v3/file/sn-article-revision.pdf},
HAL_ID = {hal-02310069},
HAL_VERSION = {v3},
}
-
Mohamed Diouf,
Rafael Silva,
and Thierry Marie Guerra.
Trajectory Tracking Using Quasi-LPV Descriptor Models for Vehicle Control.
IFAC-PapersOnLine,
59(26):211-216,
2025.
@article{diouf:hal-05482594,
TITLE = {{Trajectory Tracking Using Quasi-LPV Descriptor Models for Vehicle Control}},
AUTHOR = {Diouf, Mohamed and Silva, Rafael and Guerra, Thierry Marie},
url-hal= {https://uphf.hal.science/hal-05482594},
JOURNAL = {{IFAC-PapersOnLine}},
PUBLISHER = {{Elsevier}},
VOLUME = {59},
NUMBER = {26},
PAGES = {211-216},
YEAR = {2025},
DOI = {10.1016/j.ifacol.2025.12.036},
HAL_ID = {hal-05482594},
HAL_VERSION = {v1},
}
-
Sébastien Frey,
Federica Facente,
Wen Wei,
Ezem Sura Ekmekci,
Eric Séjor,
Patrick Baqué,
Matthieu Durand,
Hervé Delingette,
Francois Bremond,
Pierre Berthet-Rayne,
and Nicholas Ayache.
Optimizing Intraoperative AI: Evaluation of YOLOv8 for Real-Time Recognition of Robotic and Laparoscopic Instruments.
Journal of Robotic Surgery,
19(131),
March 2025.
Keyword(s): Computer-Assisted Surgery,
YoloV8,
Robotic surgery,
Instrument segmentation,
Surgical instrument detection,
Computer vision.
@article{frey:hal-04845670,
TITLE = {{Optimizing Intraoperative AI: Evaluation of YOLOv8 for Real-Time Recognition of Robotic and Laparoscopic Instruments}},
AUTHOR = {Frey, S{\'e}bastien and Facente, Federica and Wei, Wen and Ekmekci, Ezem Sura and S{\'e}jor, Eric and Baqu{\'e}, Patrick and Durand, Matthieu and Delingette, Herv{\'e} and Bremond, Francois and Berthet-Rayne, Pierre and Ayache, Nicholas},
url-hal= {https://hal.science/hal-04845670},
JOURNAL = {{Journal of Robotic Surgery}},
PUBLISHER = {{Springer Verlag}},
VOLUME = {19},
NUMBER = {131},
YEAR = {2025},
MONTH = Mar,
DOI = {10.1007/s11701-025-02284-7},
KEYWORDS = {Computer-Assisted Surgery ; YoloV8 ; Robotic surgery ; Instrument segmentation ; Surgical instrument detection ; Computer vision},
HAL_ID = {hal-04845670},
HAL_VERSION = {v1},
}
-
Sebastien Goffart,
Hervé Delingette,
Andrea Chierici,
Lisa Guzzi,
Bahaa Nasr,
Fabien Lareyre,
and Juliette Raffort.
Artificial Intelligence Techniques for Prognostic and Diagnostic Assessments in Peripheral Artery Disease: A Scoping Review.
Angiology,
2025.
Keyword(s): Machine Learning,
Peripheral Artery Disease (PAD),
Artificial Intelligence (AI),
Machine Learning (ML),
Diagnosis,
Prognosis.
@article{goffart:hal-04922713,
TITLE = {{Artificial Intelligence Techniques for Prognostic and Diagnostic Assessments in Peripheral Artery Disease: A Scoping Review}},
AUTHOR = {Goffart, Sebastien and Delingette, Herv{\'e} and Chierici, Andrea and Guzzi, Lisa and Nasr, Bahaa and Lareyre, Fabien and Raffort, Juliette},
url-hal= {https://hal.science/hal-04922713},
JOURNAL = {{Angiology}},
PUBLISHER = {{SAGE Publications}},
YEAR = {2025},
DOI = {10.1177/00033197241310572},
KEYWORDS = {Machine Learning ; Peripheral Artery Disease (PAD) ; Artificial Intelligence (AI) ; Machine Learning (ML) ; Diagnosis ; Prognosis},
PDF = {https://hal.science/hal-04922713v1/file/Manuscript_final.pdf},
HAL_ID = {hal-04922713},
HAL_VERSION = {v1},
}
-
Sébastien Goffart,
Odette Hart,
Fabien Lareyre,
Lisa Guzzi,
Kak Khee Yeung,
Hervé Delingette,
Manar Khashram,
and Juliette Raffort.
Deep Learning Strategies for Predicting Amputation Free Survival in Patients with Peripheral Artery Disease.
European Journal of Vascular and Endovascular Surgery,
October 2025.
Keyword(s): Survival models,
Prognostic,
Peripheral artery disease,
Machine learning,
Competing risk model.
@article{goffart:hal-05459134,
TITLE = {{Deep Learning Strategies for Predicting Amputation Free Survival in Patients with Peripheral Artery Disease}},
AUTHOR = {Goffart, S{\'e}bastien and Hart, Odette and Lareyre, Fabien and Guzzi, Lisa and Yeung, Kak Khee and Delingette, Herv{\'e} and Khashram, Manar and Raffort, Juliette},
url-hal= {https://hal.science/hal-05459134},
JOURNAL = {{European Journal of Vascular and Endovascular Surgery}},
PUBLISHER = {{Elsevier}},
YEAR = {2025},
MONTH = Oct,
DOI = {10.1016/j.ejvs.2025.10.043},
KEYWORDS = {Survival models ; Prognostic ; Peripheral artery disease ; Machine learning ; Competing risk model},
HAL_ID = {hal-05459134},
HAL_VERSION = {v1},
}
-
Jia Guo,
Fabien Lareyre,
Sébastien Goffart,
Andrea Chierici,
Hervé Delingette,
and Juliette Raffort.
Automatic Segmentation of Intraluminal Thrombus in Abdominal Aortic Aneurysms Based on CT Images: A Comprehensive Review of Deep Learning-Based Methods.
Journal of Clinical Medicine,
14(23):8497,
November 2025.
Keyword(s): intraluminal thrombus,
imaging segmentation,
deep learning,
abdominal aortic aneurysm,
EVAR,
CTA.
@article{guo:hal-05469421,
TITLE = {{Automatic Segmentation of Intraluminal Thrombus in Abdominal Aortic Aneurysms Based on CT Images: A Comprehensive Review of Deep Learning-Based Methods}},
AUTHOR = {Guo, Jia and Lareyre, Fabien and Goffart, S{\'e}bastien and Chierici, Andrea and Delingette, Herv{\'e} and Raffort, Juliette},
url-hal= {https://inria.hal.science/hal-05469421},
JOURNAL = {{Journal of Clinical Medicine}},
PUBLISHER = {{MDPI}},
VOLUME = {14},
NUMBER = {23},
PAGES = {8497},
YEAR = {2025},
MONTH = Nov,
DOI = {10.3390/jcm14238497},
KEYWORDS = {intraluminal thrombus ; imaging segmentation ; deep learning ; abdominal aortic aneurysm ; EVAR ; CTA},
HAL_ID = {hal-05469421},
HAL_VERSION = {v1},
}
-
Jia Guo,
Fabien Lareyre,
Regent Lee,
Martin Teraa,
Hervé Delingette,
and Juliette Raffort.
Artificial Intelligence and Machine Learning for Risk Prediction of Abdominal Aortic Aneurysm Growth and Rupture.
Angiology,
October 2025.
Keyword(s): rupture,
prediction model,
machine learning,
artificial intelligence,
aortic aneurysm,
aneurysm growth.
@article{guo:hal-05469404,
TITLE = {{Artificial Intelligence and Machine Learning for Risk Prediction of Abdominal Aortic Aneurysm Growth and Rupture}},
AUTHOR = {Guo, Jia and Lareyre, Fabien and Lee, Regent and Teraa, Martin and Delingette, Herv{\'e} and Raffort, Juliette},
url-hal= {https://inria.hal.science/hal-05469404},
JOURNAL = {{Angiology}},
PUBLISHER = {{SAGE Publications}},
YEAR = {2025},
MONTH = Oct,
DOI = {10.1177/00033197251379127},
KEYWORDS = {rupture ; prediction model ; machine learning ; artificial intelligence ; aortic aneurysm ; aneurysm growth},
HAL_ID = {hal-05469404},
HAL_VERSION = {v1},
}
-
Fabien Lareyre,
Lisa Guzzi,
Bahaa Nasr,
Ahmed Alouane,
Sébastien Goffart,
Andréa Chierici,
Hervé Delingette,
and Juliette Raffort.
Imaging Characterisation of Peripheral Artery Disease: A Scoping Review on Current Classifications and New Insights Brought by Artificial Intelligence.
EJVES Vascular Forum,
64:87-95,
2025.
Keyword(s): Artificial intelligence,
Classification,
Imaging,
Machine learning,
Peripheral artery disease.
@article{lareyre:hal-05470376,
TITLE = {{Imaging Characterisation of Peripheral Artery Disease: A Scoping Review on Current Classifications and New Insights Brought by Artificial Intelligence}},
AUTHOR = {Lareyre, Fabien and Guzzi, Lisa and Nasr, Bahaa and Alouane, Ahmed and Goffart, S{\'e}bastien and Chierici, Andr{\'e}a and Delingette, Herv{\'e} and Raffort, Juliette},
url-hal= {https://inria.hal.science/hal-05470376},
JOURNAL = {{EJVES Vascular Forum}},
PUBLISHER = {{Elsevier}},
VOLUME = {64},
PAGES = {87-95},
YEAR = {2025},
DOI = {10.1016/j.ejvsvf.2025.06.003},
KEYWORDS = {Artificial intelligence ; Classification ; Imaging ; Machine learning ; Peripheral artery disease},
HAL_ID = {hal-05470376},
HAL_VERSION = {v1},
}
-
Huiyu Li,
Nicholas Ayache,
and Hervé Delingette.
Data Exfiltration by Compression Attack: Definition and Evaluation on Medical Image Data.
Journal of Machine Learning for Biomedical Imaging,
3(December 2025):728-756,
December 2025.
Keyword(s): Steganography,
Privacy,
Image compression,
Data Exfiltration by Compression Attack.
@article{li:hal-05383223,
TITLE = {{Data Exfiltration by Compression Attack: Definition and Evaluation on Medical Image Data}},
AUTHOR = {Li, Huiyu and Ayache, Nicholas and Delingette, Herv{\'e}},
url-hal= {https://hal.science/hal-05383223},
JOURNAL = {{Journal of Machine Learning for Biomedical Imaging}},
PUBLISHER = {{Melba editors}},
VOLUME = {3},
NUMBER = {December 2025},
PAGES = {728-756},
YEAR = {2025},
MONTH = Dec,
DOI = {10.59275/j.melba.2025-113f},
KEYWORDS = {Steganography ; Privacy ; Image compression ; Data Exfiltration by Compression Attack},
PDF = {https://hal.science/hal-05383223v2/file/MELBA.pdf},
HAL_ID = {hal-05383223},
HAL_VERSION = {v2},
}
-
Sébastien Molière,
Dimitri Hamzaoui,
Guillaume Ploussard,
Romain Mathieu,
Gaëlle Fiard,
Michael Baboudjian,
benjamin granger,
Morgan Roupret,
Hervé Delingette,
and Raphaële Renard-Penna.
A Systematic Review of the Diagnostic Accuracy of Deep Learning Models for the Automatic Detection, Localization, and Characterization of Clinically Significant Prostate Cancer on Magnetic Resonance Imaging.
European Urology Oncology,
8(4):1182-1202,
August 2025.
Keyword(s): Deep learning,
Diagnostic accuracy,
Magnetic resonance imaging,
Prostate cancer,
Systematic review,
Artificial intelligence.
@article{moliere:hal-04827079,
TITLE = {{A Systematic Review of the Diagnostic Accuracy of Deep Learning Models for the Automatic Detection, Localization, and Characterization of Clinically Significant Prostate Cancer on Magnetic Resonance Imaging}},
AUTHOR = {Moli{\`e}re, S{\'e}bastien and Hamzaoui, Dimitri and Ploussard, Guillaume and Mathieu, Romain and Fiard, Ga{\"e}lle and Baboudjian, Michael and granger, benjamin and Roupret, Morgan and Delingette, Herv{\'e} and Renard-Penna, Rapha{\"e}le},
url-hal= {https://hal.science/hal-04827079},
JOURNAL = {{European Urology Oncology}},
PUBLISHER = {{Elsevier}},
VOLUME = {8},
NUMBER = {4},
PAGES = {1182-1202},
YEAR = {2025},
MONTH = Aug,
DOI = {10.1016/j.euo.2024.11.001},
KEYWORDS = {Deep learning ; Diagnostic accuracy ; Magnetic resonance imaging ; Prostate cancer ; Systematic review ; Artificial intelligence},
PDF = {https://hal.science/hal-04827079v1/file/1-s2.0-S2588931124002487-main.pdf},
HAL_ID = {hal-04827079},
HAL_VERSION = {v1},
}
-
Benjamin Sacristan,
Hubert Cochet,
Benjamin Bouyer,
Romain Tixier,
Josselin Duchateau,
Nicolas Derval,
Thomas Pambrun,
Marine Arnaud,
Jan Charton,
Geoffroy Ditac,
Allan Plant,
John Fitzgerald,
Soumaya Sdiri-Cheniti,
Laurens Verhaege,
Michel Montaudon,
Mélèze Hocini,
Michel Haissaguerre,
Maxime Sermesant,
Pierre Jais,
and Frederic Sacher.
Imaging-Aided VT Ablation. Long-Term Results From a Pilot Study.
Journal of Cardiovascular Electrophysiology,
36(8):1841-1848,
May 2025.
Keyword(s): InHeart software,
ventricular tachycardia,
imaging,
CT-Scan,
catheter ablation.
@article{sacristan:hal-05535349,
TITLE = {{Imaging-Aided VT Ablation. Long-Term Results From a Pilot Study}},
AUTHOR = {Sacristan, Benjamin and Cochet, Hubert and Bouyer, Benjamin and Tixier, Romain and Duchateau, Josselin and Derval, Nicolas and Pambrun, Thomas and Arnaud, Marine and Charton, Jan and Ditac, Geoffroy and Plant, Allan and Fitzgerald, John and Sdiri-Cheniti, Soumaya and Verhaege, Laurens and Montaudon, Michel and Hocini, M{\'e}l{\`e}ze and Haissaguerre, Michel and Sermesant, Maxime and Jais, Pierre and Sacher, Frederic},
url-hal= {https://inria.hal.science/hal-05535349},
JOURNAL = {{Journal of Cardiovascular Electrophysiology}},
PUBLISHER = {{Wiley}},
VOLUME = {36},
NUMBER = {8},
PAGES = {1841-1848},
YEAR = {2025},
MONTH = May,
DOI = {10.1111/jce.16741},
KEYWORDS = {InHeart software ; ventricular tachycardia ; imaging ; CT-Scan ; catheter ablation},
PDF = {https://inria.hal.science/hal-05535349v1/file/JCE-36-1841.pdf},
HAL_ID = {hal-05535349},
HAL_VERSION = {v1},
}
-
Marta Saiz-Vivó,
Jordi Mill,
Xavier Iriart,
Hubert Cochet,
Gemma Piella,
Maxime Sermesant,
and Oscar Camara.
Digital twin integrating clinical, morphological and hemodynamic data to identify stroke risk factors.
npj Digital Medicine,
8(1):369,
June 2025.
@article{saizvivo:hal-05535351,
TITLE = {{Digital twin integrating clinical, morphological and hemodynamic data to identify stroke risk factors}},
AUTHOR = {Saiz-Viv{\'o}, Marta and Mill, Jordi and Iriart, Xavier and Cochet, Hubert and Piella, Gemma and Sermesant, Maxime and Camara, Oscar},
url-hal= {https://inria.hal.science/hal-05535351},
JOURNAL = {{npj Digital Medicine}},
PUBLISHER = {{Nature Research }},
VOLUME = {8},
NUMBER = {1},
PAGES = {369},
YEAR = {2025},
MONTH = Jun,
DOI = {10.1038/s41746-025-01676-1},
PDF = {https://inria.hal.science/hal-05535351v1/file/s41746-025-01676-1.pdf},
HAL_ID = {hal-05535351},
HAL_VERSION = {v1},
}
-
T. Soulier,
Ninon Burgos,
Ravi Hassanaly,
M. Pitombeira,
Maëlys Solal,
Hugues Roy,
M. Hamzaoui,
A. Yazdan-Panah,
D. de Paula Faria,
C. Louapre,
B. Bodini,
M. Bottlaender,
Nicholas Ayache,
Olivier Colliot,
and B. Stankoff.
Artificial intelligence in presymptomatic neurological diseases: Bridging normal variation and prodromal signatures.
Revue Neurologique,
181(9):944-950,
November 2025.
Keyword(s): Anomaly detection,
Pseudo healthy digital twins,
Artificial intelligence,
Presymptomatic neurological diseases.
@article{soulier:hal-05378338,
TITLE = {{Artificial intelligence in presymptomatic neurological diseases: Bridging normal variation and prodromal signatures}},
AUTHOR = {Soulier, T. and Burgos, Ninon and Hassanaly, Ravi and Pitombeira, M. and Solal, Ma{\"e}lys and Roy, Hugues and Hamzaoui, M. and Yazdan-Panah, A. and de Paula Faria, D. and Louapre, C. and Bodini, B. and Bottlaender, M. and Ayache, Nicholas and Colliot, Olivier and Stankoff, B.},
url-hal= {https://hal.sorbonne-universite.fr/hal-05378338},
JOURNAL = {{Revue Neurologique}},
PUBLISHER = {{Elsevier Masson}},
VOLUME = {181},
NUMBER = {9},
PAGES = {944-950},
YEAR = {2025},
MONTH = Nov,
DOI = {10.1016/j.neurol.2025.07.011},
KEYWORDS = {Anomaly detection ; Pseudo healthy digital twins ; Artificial intelligence ; Presymptomatic neurological diseases},
PDF = {https://hal.sorbonne-universite.fr/hal-05378338v1/file/presympto.pdf},
HAL_ID = {hal-05378338},
HAL_VERSION = {v1},
}
-
Javier Villar-Valero,
Jairo Rodrìguez Padilla,
Nicolas Cedilnik,
Buntheng Ly,
Juan F. Gómez,
Maxime Sermesant,
Mihaela Pop,
and Beatriz Trenor.
In silico predictions of action potential propagation in doxorubicin cardiotoxicity: A parametric study using preclinical 3D magnetic resonance imaging-based fibrotic left ventricle models.
The Journal of Physiology,
November 2025.
Keyword(s): cardiac modelling,
cardiotoxicity,
computational electrophysiology,
doxorubicin,
reentrant arrhythmias.
@article{villarvalero:hal-05449683,
TITLE = {{In silico predictions of action potential propagation in doxorubicin cardiotoxicity: A parametric study using preclinical 3D magnetic resonance imaging-based fibrotic left ventricle models}},
AUTHOR = {Villar-Valero, Javier and Rodr{\'i}guez Padilla, Jairo and Cedilnik, Nicolas and Ly, Buntheng and G{\'o}mez, Juan F. and Sermesant, Maxime and Pop, Mihaela and Trenor, Beatriz},
url-hal= {https://hal.science/hal-05449683},
JOURNAL = {{The Journal of Physiology}},
PUBLISHER = {{Wiley}},
YEAR = {2025},
MONTH = Nov,
DOI = {10.1113/JP288819},
KEYWORDS = {cardiac modelling ; cardiotoxicity ; computational electrophysiology ; doxorubicin ; reentrant arrhythmias},
PDF = {https://hal.science/hal-05449683v1/file/The%20Journal%20of%20Physiology%20-%202025%20-%20Villar%E2%80%90Valero%20-%20In%20silico%20predictions%20of%20action%20potential%20propagation%20in%20doxorubicin.pdf},
HAL_ID = {hal-05449683},
HAL_VERSION = {v1},
}
-
Zihao Wang,
Clair Vandersteen,
Charles Raffaelli,
Nicolas Guevara,
and Hervé Delingette.
Multi-Energy Quasi-Symplectic Langevin Inference for Latent Disentangled Learning.
IEEE Transactions on Image Processing,
34:7037-7049,
2025.
Keyword(s): Survival modelling.,
Prognostic features,
Peripheral artery disease,
Machine learning,
Competing risk model.
@article{wang:hal-05470414,
TITLE = {{Multi-Energy Quasi-Symplectic Langevin Inference for Latent Disentangled Learning}},
AUTHOR = {Wang, Zihao and Vandersteen, Clair and Raffaelli, Charles and Guevara, Nicolas and Delingette, Herv{\'e}},
url-hal= {https://inria.hal.science/hal-05470414},
JOURNAL = {{IEEE Transactions on Image Processing}},
PUBLISHER = {{Institute of Electrical and Electronics Engineers}},
VOLUME = {34},
PAGES = {7037-7049},
YEAR = {2025},
DOI = {10.1109/TIP.2025.3624614},
KEYWORDS = {Survival modelling. ; Prognostic features ; Peripheral artery disease ; Machine learning ; Competing risk model},
HAL_ID = {hal-05470414},
HAL_VERSION = {v1},
}
-
Wilhelm Wimmer and Hervé Delingette.
Second order kinematic surface fitting in anatomical structures.
Medical Image Analysis,
pp 103488,
February 2025.
Keyword(s): Stationary velocity field,
Symmetry,
Core line detection,
Cochlea,
Shape classification.
@article{wimmer:hal-04937619,
TITLE = {{Second order kinematic surface fitting in anatomical structures}},
AUTHOR = {Wimmer, Wilhelm and Delingette, Herv{\'e}},
url-hal= {https://inria.hal.science/hal-04937619},
JOURNAL = {{Medical Image Analysis}},
PUBLISHER = {{Elsevier}},
PAGES = {103488},
YEAR = {2025},
MONTH = Feb,
DOI = {10.1016/j.media.2025.103488},
KEYWORDS = {Stationary velocity field ; Symmetry ; Core line detection ; Cochlea ; Shape classification},
PDF = {https://inria.hal.science/hal-04937619v1/file/Final___Second_Order_Kinematic_Surface_Fitting_in_Anatomical_Structures%20%281%29.pdf},
HAL_ID = {hal-04937619},
HAL_VERSION = {v1},
}
-
Francesco Cremonesi,
Marc Vesin,
Sergen Cansiz,
Yannick Bouillard,
Irene Balelli,
Lucia Innocenti,
Riccardo Taiello,
Santiago Silva,
Samy-Safwan Ayed,
Melek Önen,
Fanny Orlhac,
Christophe Nioche,
Bastien Houis,
Romain Modzelewski,
Nathan Lapel,
Renaud Schiappa,
Olivier Humbert,
and Marco Lorenzi.
Fed-BioMed: Open, Transparent and Trusted Federated Learning for Real-world Healthcare Applications.
In Federated Learning Systems,
volume 832 of Studies in Computational Intelligence,
pages 19-41.
Springer Nature Switzerland,
April 2025.
Keyword(s): Machine learning,
Biomedical Application,
Healthcare,
Federated Learning Framework.
@incollection{cremonesi:hal-04081557,
TITLE = {{Fed-BioMed: Open, Transparent and Trusted Federated Learning for Real-world Healthcare Applications}},
AUTHOR = {Cremonesi, Francesco and Vesin, Marc and Cansiz, Sergen and Bouillard, Yannick and Balelli, Irene and Innocenti, Lucia and Taiello, Riccardo and Silva, Santiago and Ayed, Samy-Safwan and {\"O}nen, Melek and Orlhac, Fanny and Nioche, Christophe and Houis, Bastien and Modzelewski, Romain and Lapel, Nathan and Schiappa, Renaud and Humbert, Olivier and Lorenzi, Marco},
url-hal= {https://inria.hal.science/hal-04081557},
BOOKTITLE = {{Federated Learning Systems}},
PUBLISHER = {{Springer Nature Switzerland}},
SERIES = {Studies in Computational Intelligence},
VOLUME = {832},
PAGES = {19-41},
YEAR = {2025},
MONTH = Apr,
DOI = {10.1007/978-3-031-78841-3\_2},
KEYWORDS = {Machine learning ; Biomedical Application ; Healthcare ; Federated Learning Framework},
PDF = {https://inria.hal.science/hal-04081557v1/file/fedbiomed_paper-5.pdf},
HAL_ID = {hal-04081557},
HAL_VERSION = {v1},
}
-
Yanis Aeschlimann,
Anna Calissano,
Théodore Papadopoulo,
and Samuel Deslauriers-Gauthier.
Brain network alignment using structural and functional connectivity with anatomical constraints.
In 2025 IEEE 22nd International Symposium on Biomedical Imaging (ISBI),
Houston, United States,
pages 1-4,
April 2025.
IEEE.
Keyword(s): inter-subject variability,
graph alignment,
cortical atlas,
Functional connectivity,
Structural connectivity.
@inproceedings{aeschlimann:hal-04387986,
TITLE = {{Brain network alignment using structural and functional connectivity with anatomical constraints}},
AUTHOR = {Aeschlimann, Yanis and Calissano, Anna and Papadopoulo, Th{\'e}odore and Deslauriers-Gauthier, Samuel},
url-hal= {https://hal.science/hal-04387986},
BOOKTITLE = {{2025 IEEE 22nd International Symposium on Biomedical Imaging (ISBI)}},
ADDRESS = {Houston, United States},
PUBLISHER = {{IEEE}},
PAGES = {1-4},
YEAR = {2025},
MONTH = Apr,
DOI = {10.1109/ISBI60581.2025.10981283},
KEYWORDS = {inter-subject variability ; graph alignment ; cortical atlas ; Functional connectivity ; Structural connectivity},
PDF = {https://hal.science/hal-04387986v2/file/ISBI_2025_Yanis_reviewed_version.pdf},
HAL_ID = {hal-04387986},
HAL_VERSION = {v2},
}
-
Safaa Al-Ali,
Jairo Rodrìguez-Padilla,
Maxime Sermesant,
and Irene Balelli.
Cardiac Electromechanical Model Sensitivity Analysis using Causal Discovery.
In Lecture notes in computer science,
number LNCS-15672 of Functional Imaging and Modeling of the Heart. FIMH 2025 : part 1,
Dallas, United States,
June 2025.
Radomìr Chabiniok.
Keyword(s): Sensitivity analysis,
Causal discovery,
Electromechanical properties,
Heart modeling.
@inproceedings{alali:hal-05121540,
TITLE = {{Cardiac Electromechanical Model Sensitivity Analysis using Causal Discovery}},
AUTHOR = {Al-Ali, Safaa and Rodr{\'i}guez-Padilla, Jairo and Sermesant, Maxime and Balelli, Irene},
url-hal= {https://hal.science/hal-05121540},
BOOKTITLE = {{Lecture notes in computer science}},
ADDRESS = {Dallas, United States},
ORGANIZATION = {{Radom{\'i}r Chabiniok}},
SERIES = {Functional Imaging and Modeling of the Heart. FIMH 2025 : part 1},
NUMBER = {LNCS-15672},
YEAR = {2025},
MONTH = Jun,
DOI = {10.1007/978-3-031-94559-5\_31},
KEYWORDS = {Sensitivity analysis ; Causal discovery ; Electromechanical properties ; Heart modeling},
PDF = {https://hal.science/hal-05121540v2/file/Preprint_FIMH_2025_Hal.pdf},
HAL_ID = {hal-05121540},
HAL_VERSION = {v2},
}
-
Benjamin Billot,
Ramya Muthukrishnan,
Esra Abaci Turk,
P. Ellen Grant,
Nicholas Ayache,
Hervé Delingette,
and Polina Golland.
Spatial Regularisation for Improved Accuracy and Interpretability in Keypoint-Based Registration.
In MICCAI 2025 - 28th International Conference on Medical Image Computing and Computer Assisted Intervention,
volume 15973,
Daejeon, South Korea,
pages 583-593,
2025.
Springer Nature.
Keyword(s): Deep learning,
Spatial regularisation,
Interpretability,
Affine registration.
@inproceedings{billot:hal-05291717,
TITLE = {{Spatial Regularisation for~Improved Accuracy and~Interpretability in~Keypoint-Based Registration}},
AUTHOR = {Billot, Benjamin and Muthukrishnan, Ramya and Abaci Turk, Esra and Grant, P. Ellen and Ayache, Nicholas and Delingette, Herv{\'e} and Golland, Polina},
url-hal= {https://hal.science/hal-05291717},
BOOKTITLE = {{MICCAI 2025 - 28th International Conference on Medical Image Computing and Computer Assisted Intervention}},
ADDRESS = {Daejeon, South Korea},
PUBLISHER = {{Springer Nature}},
VOLUME = {15973},
PAGES = {583-593},
YEAR = {2025},
DOI = {10.1007/978-3-032-05185-1\_56},
KEYWORDS = {Deep learning ; Spatial regularisation ; Interpretability ; Affine registration},
PDF = {https://hal.science/hal-05291717v1/file/MICCAI_25__spatial_regularisation__Arxiv_.pdf},
HAL_ID = {hal-05291717},
HAL_VERSION = {v1},
}
-
Olivier Bisson,
Yanis Aeschlimann,
Samuel Deslauriers-Gauthier,
and Xavier Pennec.
Log-Euclidean Frameworks for Smooth Brain Connectivity Trajectories.
In Lecture Notes in Computer Science (LNCS),
volume 16035,
Saint-Malo (France), France,
pages 194-204,
October 2025.
Keyword(s): Correlation matrices,
Riemannian geometry,
Log-Euclidean polynomial regression.
@inproceedings{bisson:hal-05165921,
TITLE = {{Log-Euclidean Frameworks for Smooth Brain Connectivity Trajectories}},
AUTHOR = {Bisson, Olivier and Aeschlimann, Yanis and Deslauriers-Gauthier, Samuel and Pennec, Xavier},
url-hal= {https://hal.science/hal-05165921},
BOOKTITLE = {{Lecture Notes in Computer Science (LNCS)}},
ADDRESS = {Saint-Malo (France), France},
VOLUME = {16035},
PAGES = {194--204},
YEAR = {2025},
MONTH = Oct,
DOI = {10.1007/978-3-032-03924-8\_20},
KEYWORDS = {Correlation matrices ; Riemannian geometry ; Log-Euclidean polynomial regression},
PDF = {https://hal.science/hal-05165921v1/file/GSI2025-46.pdf},
HAL_ID = {hal-05165921},
HAL_VERSION = {v1},
}
-
Francesco Cremonesi,
Lucie Chambon,
Nelson Mokkadem,
Huyen Thi Trang Nguyen,
Oliver Humbert,
and Marco Lorenzi.
Knowledge-based semantic enrichment of medical imaging data for automatic phenotyping and pattern discovery in metastatic lung cancer.
In 2025 SNMMI Annual Meeting - Society for Nuclear Medicine and Molecular Imaging,
New orleans, LA, United States,
June 2025.
@inproceedings{cremonesi:hal-04879690,
TITLE = {{Knowledge-based semantic enrichment of medical imaging data for automatic phenotyping and pattern discovery in metastatic lung cancer}},
AUTHOR = {Cremonesi, Francesco and Chambon, Lucie and Mokkadem, Nelson and Nguyen, Huyen Thi Trang and Humbert, Oliver and Lorenzi, Marco},
url-hal= {https://hal.science/hal-04879690},
BOOKTITLE = {{2025 SNMMI Annual Meeting - Society for Nuclear Medicine and Molecular Imaging}},
ADDRESS = {New orleans, LA, United States},
YEAR = {2025},
MONTH = Jun,
PDF = {https://hal.science/hal-04879690v1/file/whitepaper.pdf},
HAL_ID = {hal-04879690},
HAL_VERSION = {v1},
}
-
Federica Facente,
Benjamin Billot,
Vivek Gopalakrishnan,
Manasi Kattel,
Wen Wei,
Polina Golland,
Hervé Delingette,
Nicholas Ayache,
and Pierre Berthet-Rayne.
Multi-stage CNN for fast registration of 3D preoperative CTs to 2D intraoperative X-rays.
In Lecture Notes in Computer Science - International Workshop on Collaborative Intelligence and Autonomy in Image-Guided Surgery,
Daejon, South Korea,
pages 137-147,
September 2025.
Keyword(s): Multi-stage CNN,
Pose estimation.
@inproceedings{facente:hal-05218972,
TITLE = {{Multi-stage CNN for fast registration of 3D preoperative CTs to 2D intraoperative X-rays}},
AUTHOR = {Facente, Federica and Billot, Benjamin and Gopalakrishnan, Vivek and Kattel, Manasi and Wei, Wen and Golland, Polina and Delingette, Herv{\'e} and Ayache, Nicholas and Berthet-Rayne, Pierre},
url-hal= {https://hal.science/hal-05218972},
BOOKTITLE = {{Lecture Notes in Computer Science - International Workshop on Collaborative Intelligence and Autonomy in Image-Guided Surgery}},
ADDRESS = {Daejon, South Korea},
PAGES = {137-147},
YEAR = {2025},
MONTH = Sep,
DOI = {10.1007/978-3-032-09784-2\_14},
KEYWORDS = {Multi-stage CNN ; Pose estimation},
PDF = {https://hal.science/hal-05218972v1/file/MICCAI_25__LXPose.pdf},
HAL_ID = {hal-05218972},
HAL_VERSION = {v1},
}
-
Camilla Ferrario.
Myocardial Stiffness Quantification Using Ultrasound Shear Wave Elastography and Reduced Modeling for Subject-Specific Simulations.
In Journées annuelles du PEPR Santé Numérique,
Lille (France), France,
October 2025.
PEPR Santé Numérique.
Keyword(s): ultrafast ultrasound imaging,
modeling mathematic.
@inproceedings{ferrario:inserm-05362487,
TITLE = {{Myocardial Stiffness Quantification Using Ultrasound Shear Wave Elastography and~Reduced Modeling for~Subject-Specific Simulations}},
AUTHOR = {Ferrario, Camilla},
url-hal= {https://inserm.hal.science/inserm-05362487},
BOOKTITLE = {{Journ{\'e}es annuelles du PEPR Sant{\'e} Num{\'e}rique}},
ADDRESS = {Lille (France), France},
ORGANIZATION = {{PEPR Sant{\'e} Num{\'e}rique}},
YEAR = {2025},
MONTH = Oct,
KEYWORDS = {ultrafast ultrasound imaging ; modeling mathematic},
HAL_ID = {inserm-05362487},
HAL_VERSION = {v1},
}
-
Camilla Ferrario,
Jairo Rodrìguez-Padilla,
Maelys Venet,
Olivier Villemain,
and Maxime Sermesant.
Myocardial Stiffness Quantification using Ultrasound Shear Wave Elastography and Reduced Modeling for Subject-specific Simulations.
In Lecture Notes in Computer Science,
volume 15673 of Functional Imaging and Modeling of the Heart. FIMH 2025,
Dallas (TX), United States,
pages 41-54,
June 2025.
Keyword(s): patient-specific analyses,
myocardial stiffness,
ultrafast ultrasound imaging,
reduced-order models,
Cardiac mechanics.
@inproceedings{ferrario:hal-05123170,
TITLE = {{Myocardial Stiffness Quantification using Ultrasound Shear Wave Elastography and Reduced Modeling for Subject-specific Simulations}},
AUTHOR = {Ferrario, Camilla and Rodr{\'i}guez-Padilla, Jairo and Venet, Maelys and Villemain, Olivier and Sermesant, Maxime},
url-hal= {https://hal.science/hal-05123170},
BOOKTITLE = {{Lecture Notes in Computer Science}},
ADDRESS = {Dallas (TX), United States},
SERIES = {Functional Imaging and Modeling of the Heart. FIMH 2025},
VOLUME = {15673},
NUMBER = {LNCS-15673},
PAGES = {41-54},
YEAR = {2025},
MONTH = Jun,
DOI = {10.1007/978-3-031-94562-5\_5},
KEYWORDS = {patient-specific analyses ; myocardial stiffness ; ultrafast ultrasound imaging ; reduced-order models ; Cardiac mechanics},
PDF = {https://hal.science/hal-05123170v1/file/FIMH_definitivo_official-3.pdf},
HAL_ID = {hal-05123170},
HAL_VERSION = {v1},
}
-
Evariste Njomgue Fotso,
Marta Nuñez-Garcia,
Buntheng Ly,
Hubert Cochet,
and Maxime Sermesant.
Uncertainty-Informed Multimodal Infarct Age Prediction from Imaging and Clinical Data.
In Lecture Notes in Computer Science,
number LNCS-15673 of Functional Imaging and Modeling of the Heart. FIMH 2025,
Dallas (TX), United States,
June 2025.
Radomir Chabiniok and Maria Gusseva and Tarique Hussain and Hoang Nguyen and Vlad Zaha and Qing Zou.
Keyword(s): Multimodal deep learning,
Infarct age regression,
Medical imaging,
Intramyocardial fat,
Calcification,
Myocardial thickness.
@inproceedings{fotso:hal-05126700,
TITLE = {{Uncertainty-Informed Multimodal Infarct Age Prediction from Imaging and Clinical Data}},
AUTHOR = {Fotso, Evariste Njomgue and Nu{\~n}ez-Garcia, Marta and Ly, Buntheng and Cochet, Hubert and Sermesant, Maxime},
url-hal= {https://inria.hal.science/hal-05126700},
BOOKTITLE = {{Lecture Notes in Computer Science}},
ADDRESS = {Dallas (TX), United States},
ORGANIZATION = {{Radomir Chabiniok and Maria Gusseva and Tarique Hussain and Hoang Nguyen and Vlad Zaha and Qing Zou}},
SERIES = {Functional Imaging and Modeling of the Heart. FIMH 2025},
NUMBER = {LNCS-15673},
YEAR = {2025},
MONTH = Jun,
DOI = {10.1007/978-3-031-94562-5\_6},
KEYWORDS = {Multimodal deep learning ; Infarct age regression ; Medical imaging ; Intramyocardial fat ; Calcification ; Myocardial thickness},
PDF = {https://inria.hal.science/hal-05126700v1/file/FIMH_2025-04-03_v1.pdf},
HAL_ID = {hal-05126700},
HAL_VERSION = {v1},
}
-
Lisa Guzzi,
Maria A Zuluaga,
Fabien Lareyre,
Gilles Di Lorenzo,
Sébastien Goffart,
Andrea Chierici,
Juliette Raffort,
and Hervé Delingette.
Automatic Segmentation of Lower-Limb Arteries on CTA for Pre-surgical Planning of Peripheral Artery Disease.
In MICCAI-AMAI2025 - 4th Workshop on Applications of Medical Artifical Intelligence,
Daejeon, South Korea,
September 2025.
Keyword(s): Peripheral Artery Disease,
Computed Tomography Angiography,
Image Segmentation.
@inproceedings{guzzi:hal-05225711,
TITLE = {{Automatic Segmentation of Lower-Limb Arteries on CTA for Pre-surgical Planning of Peripheral Artery Disease}},
AUTHOR = {Guzzi, Lisa and Zuluaga, Maria A and Lareyre, Fabien and Lorenzo, Gilles Di and Goffart, S{\'e}bastien and Chierici, Andrea and Raffort, Juliette and Delingette, Herv{\'e}},
url-hal= {https://hal.science/hal-05225711},
BOOKTITLE = {{MICCAI-AMAI2025 - 4th Workshop on Applications of Medical Artifical Intelligence}},
ADDRESS = {Daejeon, South Korea},
YEAR = {2025},
MONTH = Sep,
KEYWORDS = {Peripheral Artery Disease ; Computed Tomography Angiography ; Image Segmentation},
PDF = {https://hal.science/hal-05225711v1/file/AMAI2025_Paper59.pdf},
HAL_ID = {hal-05225711},
HAL_VERSION = {v1},
}
-
Lisa Guzzi,
Maria A Zuluaga,
Riccardo Taiello,
Fabien Lareyre,
Gilles Di Lorenzo,
Sébastien Goffart,
Andrea Chierici,
Juliette Raffort,
and Hervé Delingette.
Regional Hausdorff Distance Losses for Medical Image Segmentation.
In MLMI 2025 - 16th International Workshop on Machine Learning in Medical Imaging (In conjunction with MICCAI 2025),
Daejeon, South Korea,
September 2025.
Keyword(s): Image Segmentation,
Distance transforms,
Hausdorff Distance.
@inproceedings{guzzi:hal-05225722,
TITLE = {{Regional Hausdorff Distance Losses for Medical Image Segmentation}},
AUTHOR = {Guzzi, Lisa and Zuluaga, Maria A and Taiello, Riccardo and Lareyre, Fabien and Lorenzo, Gilles Di and Goffart, S{\'e}bastien and Chierici, Andrea and Raffort, Juliette and Delingette, Herv{\'e}},
url-hal= {https://hal.science/hal-05225722},
BOOKTITLE = {{MLMI 2025 - 16th International Workshop on Machine Learning in Medical Imaging (In conjunction with MICCAI 2025)}},
ADDRESS = {Daejeon, South Korea},
YEAR = {2025},
MONTH = Sep,
KEYWORDS = {Image Segmentation ; Distance transforms ; Hausdorff Distance},
PDF = {https://hal.science/hal-05225722v1/file/Paper-007.pdf},
HAL_ID = {hal-05225722},
HAL_VERSION = {v1},
}
-
Manasi Kattel,
Benjamin Billot,
Federica Facente,
Hervé Delingette,
and Nicholas Ayache.
Robust rigid MRI-TRUS registration in prostate cancer using attention-CNN and ICP.
In Lecture Notes in Computer Science,
volume 16165 of Lecture Notes in Computer Science - Simplifying Medical Ultrasound,
Daejeon, South Korea,
pages 65-75,
September 2025.
Springer Nature Switzerland.
Note: Workshop held in conjunction with MICCAI 2025.
Keyword(s): learning-based regression,
MRI-TRUS rigid registration.
@inproceedings{kattel:hal-05218125,
TITLE = {{Robust rigid MRI-TRUS registration in prostate cancer using attention-CNN and ICP}},
AUTHOR = {Kattel, Manasi and Billot, Benjamin and Facente, Federica and Delingette, Herv{\'e} and Ayache, Nicholas},
url-hal= {https://hal.science/hal-05218125},
NOTE = {Workshop held in conjunction with MICCAI 2025},
BOOKTITLE = {{Lecture Notes in Computer Science}},
ADDRESS = {Daejeon, South Korea},
PUBLISHER = {{Springer Nature Switzerland}},
SERIES = {Lecture Notes in Computer Science - Simplifying Medical Ultrasound},
VOLUME = {16165},
PAGES = {65-75},
YEAR = {2025},
MONTH = Sep,
DOI = {10.1007/978-3-032-06329-8\_7},
KEYWORDS = {learning-based regression ; MRI-TRUS rigid registration},
PDF = {https://hal.science/hal-05218125v1/file/MICCAI_25__MUReg_camera_ready.pdf},
HAL_ID = {hal-05218125},
HAL_VERSION = {v1},
}
-
Huiyu Li,
Nicholas Ayache,
and Hervé Delingette.
Generative medical image anonymization based on latent code projection and optimization.
In IEEE Xplore,
Houston (Texas), United States,
April 2025.
Keyword(s): Medical image anonymization,
Identity utility trade-off,
Latent code optimization.
@inproceedings{li:hal-04913904,
TITLE = {{Generative medical image anonymization based on latent code projection and optimization}},
AUTHOR = {Li, Huiyu and Ayache, Nicholas and Delingette, Herv{\'e}},
url-hal= {https://inria.hal.science/hal-04913904},
BOOKTITLE = {{IEEE Xplore}},
ADDRESS = {Houston (Texas), United States},
YEAR = {2025},
MONTH = Apr,
KEYWORDS = {Medical image anonymization ; Identity utility trade-off ; Latent code optimization},
PDF = {https://inria.hal.science/hal-04913904v1/file/ISBI%20%283%29.pdf},
HAL_ID = {hal-04913904},
HAL_VERSION = {v1},
}
-
Buntheng Ly,
Nicolas Cedilnik,
Mihaela Pop,
Josselin Duchateau,
Frédéric Sacher,
Pierre Jaïs,
Hubert Cochet,
and Maxime Sermesant.
Multimodal Personalisation of Cardiac Electrophysiology Models combining 12-lead ECG and Computed Tomography.
In Lecture Notes in Computer Science,
number LNCS-15672 of Functional Imaging and Modeling of the Heart. FIMH 2025,
Dallas (TX), United States,
June 2025.
Keyword(s): Computational Modelling,
Myocardial Infarction,
ECG,
Computed Tomography,
Model Personalisation.
@inproceedings{ly:hal-05122021,
TITLE = {{Multimodal Personalisation of Cardiac Electrophysiology Models combining 12-lead ECG and Computed Tomography}},
AUTHOR = {Ly, Buntheng and Cedilnik, Nicolas and Pop, Mihaela and Duchateau, Josselin and Sacher, Fr{\'e}d{\'e}ric and Ja{\"i}s, Pierre and Cochet, Hubert and Sermesant, Maxime},
url-hal= {https://inria.hal.science/hal-05122021},
BOOKTITLE = {{Lecture Notes in Computer Science}},
ADDRESS = {Dallas (TX), United States},
SERIES = {Functional Imaging and Modeling of the Heart. FIMH 2025},
NUMBER = {LNCS-15672},
YEAR = {2025},
MONTH = Jun,
DOI = {10.1007/978-3-031-94559-5\_1},
KEYWORDS = {Computational Modelling ; Myocardial Infarction ; ECG ; Computed Tomography ; Model Personalisation},
PDF = {https://inria.hal.science/hal-05122021v1/file/fimh2025_bunthengly_finalised.pdf},
HAL_ID = {hal-05122021},
HAL_VERSION = {v1},
}
-
Maëlis Morier,
Jairo Rodrìguez-Padilla,
Patrick Gallinari,
and Maxime Sermesant.
Learning Cardiac Electrophysiology with Graph Neural Networks for Fast Data-driven Personalised Predictions.
In Functional Imaging and Modeling of the Heart: 13th International Conference, FIMH 2025, Dallas, TX, USA, June 1--5, 2025, Proceedings, Part II (Lecture Notes in Computer Science, 15673),
volume 15672 (Part I) and 15673 (Part II),
Dallas (TX), United States,
pages LNCS 15672 and LNCS 15673,
June 2025.
Radomìr Chabiniok.
Keyword(s): Graph Neural Network,
Data-Driven Modeling,
Personalized Cardiac Electrophysiology.
@inproceedings{morier:hal-05114524,
TITLE = {{Learning Cardiac Electrophysiology with Graph Neural Networks for Fast Data-driven Personalised Predictions}},
AUTHOR = {Morier, Ma{\"e}lis and Rodr{\'i}guez-Padilla, Jairo and Gallinari, Patrick and Sermesant, Maxime},
url-hal= {https://hal.science/hal-05114524},
BOOKTITLE = {{Functional Imaging and Modeling of the Heart: 13th International Conference, FIMH 2025, Dallas, TX, USA, June 1--5, 2025, Proceedings, Part II (Lecture Notes in Computer Science, 15673)}},
ADDRESS = {Dallas (TX), United States},
ORGANIZATION = {{Radom{\'i}r Chabiniok}},
VOLUME = {15672 (Part I) and 15673 (Part II)},
PAGES = {LNCS 15672 and LNCS 15673},
YEAR = {2025},
MONTH = Jun,
KEYWORDS = {Graph Neural Network ; Data-Driven Modeling ; Personalized Cardiac Electrophysiology},
PDF = {https://hal.science/hal-05114524v3/file/AGATA_hal.pdf},
HAL_ID = {hal-05114524},
HAL_VERSION = {v3},
}
-
Jairo Rodrìguez Padilla,
Rafael Silva,
Buntheng Ly,
Graham Wright,
Mihaela Pop,
and Maxime Sermesant.
In silico Assessment of Arrhythmia Inducibility Dependence on Stimulus Location using Calibrated MR-based Infarcted Heart Models.
In Lecture Notes in Computer Science,
number LNCS-15672 of Functional Imaging and Modeling of the Heart. FIMH 2025,
Dallas, United States,
June 2025.
Keyword(s): Personalization,
Finite Element,
Simulations,
Modeling,
Electrophysiology.
@inproceedings{padilla:hal-05119965,
TITLE = {{In silico Assessment of Arrhythmia Inducibility Dependence on Stimulus Location using Calibrated MR-based Infarcted Heart Models}},
AUTHOR = {Padilla, Jairo Rodr{\'i}guez and Silva, Rafael and Ly, Buntheng and Wright, Graham and Pop, Mihaela and Sermesant, Maxime},
url-hal= {https://inria.hal.science/hal-05119965},
BOOKTITLE = {{Lecture Notes in Computer Science}},
ADDRESS = {Dallas, United States},
SERIES = {Functional Imaging and Modeling of the Heart. FIMH 2025},
NUMBER = {LNCS-15672},
YEAR = {2025},
MONTH = Jun,
DOI = {10.1007/978-3-031-94559-5\_9},
KEYWORDS = {Personalization ; Finite Element ; Simulations ; Modeling ; Electrophysiology},
PDF = {https://inria.hal.science/hal-05119965v1/file/FIMH_2025_halversion.pdf},
HAL_ID = {hal-05119965},
HAL_VERSION = {v1},
}
-
Rafael Silva,
Caroline Stehlé,
Guillaume Pétriat,
Pierre-Henri Cadet,
Thierry Tibi,
and Maxime Sermesant.
Frugal AI for Automated Cardiac Defibrillation: Balancing Performance & Hardware Constraints.
In Lecture notes in computer science,
number LNCS-15672 of Functional Imaging and Modeling of the Heart : part 1,
Dallas (TX), United States,
June 2025.
Keyword(s): Embedded Systems,
ECG Classification,
Automated Cardiac Defibrillation.
@inproceedings{silva:hal-05119661,
TITLE = {{Frugal AI for Automated Cardiac Defibrillation: Balancing Performance \& Hardware Constraints}},
AUTHOR = {Silva, Rafael and Stehl{\'e}, Caroline and P{\'e}triat, Guillaume and Cadet, Pierre-Henri and Tibi, Thierry and Sermesant, Maxime},
url-hal= {https://hal.science/hal-05119661},
BOOKTITLE = {{Lecture notes in computer science}},
ADDRESS = {Dallas (TX), United States},
SERIES = {Functional Imaging and Modeling of the Heart : part 1},
NUMBER = {LNCS-15672},
YEAR = {2025},
MONTH = Jun,
DOI = {10.1007/978-3-031-94559-5\_14},
KEYWORDS = {Embedded Systems ; ECG Classification ; Automated Cardiac Defibrillation},
PDF = {https://hal.science/hal-05119661v1/file/Article_FIMH%20%287%29.pdf},
HAL_ID = {hal-05119661},
HAL_VERSION = {v1},
}
-
Tom Szwagier,
Guillaume Olikier,
and Xavier Pennec.
Eigengap Sparsity for Covariance Parsimony.
In Proc. of the 7th International Conference on Geometric Science of Information - GSI'25,
volume LNCS 16034 of Lecture Notes in Computer Science,
Saint-Malo (35400), France,
pages pp 50-59,
October 2025.
Keyword(s): Isotonic regression,
Monotone cone,
Flag manifolds,
Eigengaps,
Parsimony,
Covariance estimation.
@inproceedings{szwagier:hal-05047196,
TITLE = {{Eigengap Sparsity for Covariance Parsimony}},
AUTHOR = {Szwagier, Tom and Olikier, Guillaume and Pennec, Xavier},
url-hal= {https://inria.hal.science/hal-05047196},
BOOKTITLE = {{Proc. of the 7th International Conference on Geometric Science of Information - GSI'25}},
ADDRESS = {Saint-Malo (35400), France},
SERIES = {Lecture Notes in Computer Science},
VOLUME = {LNCS 16034},
PAGES = {pp 50--59},
YEAR = {2025},
MONTH = Oct,
DOI = {10.1007/978-3-032-03921-7\_6},
KEYWORDS = {Isotonic regression ; Monotone cone ; Flag manifolds ; Eigengaps ; Parsimony ; Covariance estimation},
PDF = {https://inria.hal.science/hal-05047196v2/file/GSI25-099.pdf},
HAL_ID = {hal-05047196},
HAL_VERSION = {v2},
}
-
Riccardo Taiello,
Clémentine Gritti,
Melek Önen,
and Marco Lorenzi.
Buffalo: A Practical Secure Aggregation Protocol for Buffered Asynchronous Federated Learning.
In CODASPY 2025 - 15th ACM Conference on Data and Application Security and Privacy,
Pittsburgh, United States,
pages 1-12,
June 2025.
ACM,
ACM.
Keyword(s): Asynchronous Federated Learning,
Secure Aggregation.
@inproceedings{taiello:hal-05034678,
TITLE = {{Buffalo: A Practical Secure Aggregation Protocol for Buffered Asynchronous Federated Learning}},
AUTHOR = {Taiello, Riccardo and Gritti, Cl{\'e}mentine and {\"O}nen, Melek and Lorenzi, Marco},
url-hal= {https://hal.science/hal-05034678},
BOOKTITLE = {{CODASPY 2025 - 15th ACM Conference on Data and Application Security and Privacy}},
ADDRESS = {Pittsburgh, United States},
ORGANIZATION = {{ACM}},
PUBLISHER = {{ACM}},
PAGES = {1-12},
YEAR = {2025},
MONTH = Jun,
DOI = {10.1145/3714393.3726498},
KEYWORDS = {Asynchronous Federated Learning ; Secure Aggregation},
PDF = {https://hal.science/hal-05034678v1/file/publi-8173.pdf},
HAL_ID = {hal-05034678},
HAL_VERSION = {v1},
}
-
Elie Thellier,
Huiyu Li,
Nicholas Ayache,
and Hervé Delingette.
Mitigating Data Exfiltration Attacks through Layer-Wise Learning Rate Decay Fine-Tuning.
In Bridging Regulatory Science and Medical Imaging Evaluation; and Distributed, Collaborative, and Federated Learning,
volume Lecture Notes in Computer Science of Bridging Regulatory Science and Medical Imaging Evaluation; and Distributed, Collaborative, and Federated Learning,
Daejeon, South Korea,
September 2025.
Keyword(s): Data Lake Security,
Data Exfiltration Mitigation,
Medical Images.
@inproceedings{thellier:hal-05167639,
TITLE = {{Mitigating Data Exfiltration Attacks through Layer-Wise Learning Rate Decay Fine-Tuning}},
AUTHOR = {Thellier, Elie and Li, Huiyu and Ayache, Nicholas and Delingette, Herv{\'e}},
url-hal= {https://hal.science/hal-05167639},
BOOKTITLE = {{Bridging Regulatory Science and Medical Imaging Evaluation; and Distributed, Collaborative, and Federated Learning}},
ADDRESS = {Daejeon, South Korea},
SERIES = {Bridging Regulatory Science and Medical Imaging Evaluation; and Distributed, Collaborative, and Federated Learning},
VOLUME = {Lecture Notes in Computer Science},
NUMBER = {16135},
YEAR = {2025},
MONTH = Sep,
KEYWORDS = {Data Lake Security ; Data Exfiltration Mitigation ; Medical Images},
PDF = {https://hal.science/hal-05167639v2/file/Paper_0002.pdf},
HAL_ID = {hal-05167639},
HAL_VERSION = {v2},
}
-
Zihao Wang,
Yuzhou Chen,
and Herve Delingette.
Stochastic Flow Inference for Medical Image Digital Twins.
In CHASE '25: ACM/IEEE International Conference on Connected Health: Applications, Systems and Engineering Technologies,
Yeshiva University Museum New York NY USA, United States,
pages 353-357,
June 2025.
ACM.
@inproceedings{wang:hal-05470422,
TITLE = {{Stochastic Flow Inference for Medical Image Digital Twins}},
AUTHOR = {Wang, Zihao and Chen, Yuzhou and Delingette, Herve},
url-hal= {https://inria.hal.science/hal-05470422},
BOOKTITLE = {{CHASE '25: ACM/IEEE International Conference on Connected Health: Applications, Systems and Engineering Technologies}},
ADDRESS = {Yeshiva University Museum New York NY USA, United States},
PUBLISHER = {{ACM}},
PAGES = {353-357},
YEAR = {2025},
MONTH = Jun,
DOI = {10.1145/3721201.3725437},
HAL_ID = {hal-05470422},
HAL_VERSION = {v1},
}
-
Martin van Waerebeke,
Marco Lorenzi,
Giovanni Neglia,
and Kevin Scaman.
When to Forget? Complexity Trade-offs in Machine Unlearning.
In ICML 2025 - International Conference in Machine Learning,
Vancouver (BC), Canada,
July 2025.
Keyword(s): Complexity bounds,
Machine Unlearning,
Oubli Machine,
Désapprentissage,
Borne de complexité.
@inproceedings{vanwaerebeke:hal-05464347,
TITLE = {{When to Forget? Complexity Trade-offs in Machine Unlearning}},
AUTHOR = {van Waerebeke, Martin and Lorenzi, Marco and Neglia, Giovanni and Scaman, Kevin},
url-hal= {https://hal.science/hal-05464347},
BOOKTITLE = {{ICML 2025 - International Conference in Machine Learning}},
ADDRESS = {Vancouver (BC), Canada},
YEAR = {2025},
MONTH = Jul,
KEYWORDS = {Complexity bounds ; Machine Unlearning ; Oubli Machine ; D{\'e}sapprentissage ; Borne de complexit{\'e}},
PDF = {https://hal.science/hal-05464347v1/file/arxiv_main.pdf},
HAL_ID = {hal-05464347},
HAL_VERSION = {v1},
}