Propagation of Myocardial Fibre Architecture Uncertainty on Electromechanical Model Parameter Estimation: A Case Study. - Roch Molléro; Dominik Neumann; Marc-Michel Rohé; Manasi Datar; Hervé Lombaert; Nicholas Ayache; Dorin Comaniciu; Olivier Ecabert; Marcello Chinali; Gabriele Rinelli; Xavier Pennec; Maxime Sermesant; et al. (FIMH, 2015)

Combination of Polyaffine Transformations and Supervised Learning for the Automatic Diagnosis of LV Infarct. - Marc-Michel Rohé; Nicolas Duchateau; Maxime Sermesant; Xavier Pennec (STACOM@MICCAI, 2015)

Highly reduced model of the cardiac function for fast simulation. - Marc-Michel Rohé; Roch Molléro; Maxime Sermesant; Xavier Pennec (IVMSP, 2016)

Barycentric Subspace Analysis: A New Symmetric Group-Wise Paradigm for Cardiac Motion Tracking. - Marc-Michel Rohé; Maxime Sermesant; Xavier Pennec (MICCAI (3), 2016)

Prediction of Post-Ablation Outcome in Atrial Fibrillation Using Shape Parameterization and Partial Least Squares Regression. - Shuman Jia; Claudia Camaioni; Marc-Michel Rohé; Pierre Jaïs; Xavier Pennec; Hubert Cochet; Maxime Sermesant (FIMH, 2017)

SVF-Net: Learning Deformable Image Registration Using Shape Matching. - Marc-Michel Rohé; Manasi Datar; Tobias Heimann; Maxime Sermesant; Xavier Pennec (MICCAI (1), 2017)

Automatic Multi-Atlas Segmentation of Myocardium with SVF-Net. - Marc-Michel Rohé; Maxime Sermesant; Xavier Pennec (STACOM@MICCAI, 2017)

Reduced Representation of Segmentation and Tracking in Cardiac Images for Group-Wise Longitudinal Analysis. (Représentation réduite de la segmentation et du suivi des images cardiaques pour l'analyse longitudinale de groupe). - Marc-Michel Rohé (2017)

Low-dimensional representation of cardiac motion using Barycentric Subspaces: A new group-wise paradigm for estimation, analysis, and reconstruction. - Marc-Michel Rohé; Maxime Sermesant; Xavier Pennec (Medical Image Anal., 2018)

Statistical Shape Modeling of the Left Ventricle: Myocardial Infarct Classification Challenge. - Avan Suinesiaputra; Pierre Ablin; Xènia Albà; Martino Alessandrini; Jack Allen; Wenjia Bai; Serkan Çimen; Peter Claes; Brett R. Cowan; Jan D'hooge; Nicolas Duchateau; Jan Ehrhardt; et al. (IEEE J. Biomed. Health Informatics, 2018)

Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved? - Olivier Bernard 001; Alain Lalande; Clément Zotti; Frederic Cervenansky; Xin Yang 009; Pheng-Ann Heng; Irem Cetin; Karim Lekadir; Oscar Camara 001; Miguel Ángel González Ballester; Gerard Sanroma; Sandy Napel; et al. (IEEE Trans. Medical Imaging, 2018)

Contrast-Enhanced Brain MRI Synthesis With Deep Learning: Key Input Modalities and Asymptotic Performance. - Alexandre Bône; Samy Ammari; Jean-Philippe Lamarque; Mickael Elhaik; Emilie Chouzenoux; François Nicolas; Philippe Robert; Corinne Balleyguier; Nathalie Lassau; Marc-Michel Rohé (ISBI, 2021)

Learning to Jointly Segment the Liver, Lesions and Vessels from Partially Annotated Datasets. - Omar Ali; Alexandre Bône; Marc-Michel Rohé; Eric Vibert; Irene E. Vignon-Clementel (ICIP, 2022)

Improving the Automatic Segmentation of Elongated Organs Using Geometrical Priors. - Rebeca Vétil; Alexandre Bône; Marie-Pierre Vullierme; Marc-Michel Rohé; Pietro Gori; Isabelle Bloch (ISBI, 2022)

CoRe: An Automated Pipeline for the Prediction of Liver Resection Complexity from Preoperative CT Scans. - Omar Ali; Alexandre Bône; Caterina Accardo; Omar Belkouchi; Marc-Michel Rohé; Eric Vibert; Irene E. Vignon-Clementel (AIIIMA/MIABID@MICCAI, 2022)

Learning Shape Distributions from Large Databases of Healthy Organs: Applications to Zero-Shot and Few-Shot Abnormal Pancreas Detection. - Rebeca Vétil; Clément Abi Nader; Alexandre Bône; Marie-Pierre Vullierme; Marc-Michel Rohé; Pietro Gori; Isabelle Bloch (MICCAI (2), 2022)

Leveraging Multi-Phase CT for the Automatic Diagnosis of HCC with Deep Learning: Impacts of Lesion Localization and Phase Inclusion. - Alexandre Bône; Marc-Michel Rohé (ISBI, 2023)

Learning to Diagnose Cirrhosis from Radiological and Histological Labels with Joint Self and Weakly-Supervised Pretraining Strategies. - Emma Sarfati; Alexandre Bône; Marc-Michel Rohé; Pietro Gori; Isabelle Bloch (ISBI, 2023)

Ensembling Voxel-Based and Box-Based Model Predictions for Robust Lesion Detection. - Noëlie Debs; Alexandre Routier; Clément Abi Nader; Arnaud Marcoux; Alexandre Bône; Marc-Michel Rohé (AMAI@MICCAI, 2023)

Weakly-Supervised Positional Contrastive Learning: Application to Cirrhosis Classification. - Emma Sarfati; Alexandre Bône; Marc-Michel Rohé; Pietro Gori; Isabelle Bloch (MICCAI (1), 2023)

Non-redundant Combination of Hand-Crafted and Deep Learning Radiomics: Application to the Early Detection of Pancreatic Cancer. - Rebeca Vétil; Clément Abi Nader; Alexandre Bône; Marie-Pierre Vullierme; Marc-Michel Rohé; Pietro Gori; Isabelle Bloch (CaPTion@MICCAI, 2023)

Deformable registration of 3D CT images with partial liver. - Giovanni Palma; Greg Padiasek; Arkadiusz Sitek; Paul Dufort; Pedro L. Esquinas; Marc-Michel Rohé (Image Processing, 2023)

Guiding the Classification of Hepatocellular Carcinoma on 3D CT-Scans Using Deep and Handcrafted Radiological Features. - Emma Sarfati; Alexandre Bône; Marc-Michel Rohé; C. Aubé; M. Ronot; Pietro Gori; Isabelle Bloch (ISBI, 2025)