| Deep learning techniques for automatic MRI cardiac multi-structures segmentation and diagnosis: is the problem solved? O Bernard, A Lalande, C Zotti, F Cervenansky, X Yang, PA Heng, I Cetin, ... IEEE transactions on medical imaging 37 (11), 2514-2525, 2018 | 1447 | 2018 |
| SVF-Net: learning deformable image registration using shape matching MM Rohé, M Datar, T Heimann, M Sermesant, X Pennec Medical Image Computing and Computer Assisted Intervention− MICCAI 2017 …, 2017 | 352 | 2017 |
| Statistical shape modeling of the left ventricle: myocardial infarct classification challenge A Suinesiaputra, P Ablin, X Alba, M Alessandrini, J Allen, W Bai, S Cimen, ... IEEE journal of biomedical and health informatics 22 (2), 503-515, 2017 | 89 | 2017 |
| Automatic multi-atlas segmentation of myocardium with svf-net MM Rohé, M Sermesant, X Pennec Statistical Atlases and Computational Models of the Heart. ACDC and MMWHS …, 2018 | 48 | 2018 |
| Can deep learning replace gadolinium in neuro-oncology?: a reader study S Ammari, A Bône, C Balleyguier, E Moulton, É Chouzenoux, A Volk, ... Investigative Radiology 57 (2), 99-107, 2022 | 27 | 2022 |
| Contrast-enhanced brain MRI synthesis with deep learning: key input modalities and asymptotic performance A Bône, S Ammari, JP Lamarque, M Elhaik, É Chouzenoux, F Nicolas, ... 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), 1159-1163, 2021 | 23 | 2021 |
| Low-dimensional representation of cardiac motion using barycentric subspaces: a new group-wise paradigm for estimation, analysis, and reconstruction MM Rohé, M Sermesant, X Pennec Medical image analysis 45, 1-12, 2018 | 18 | 2018 |
| Combination of polyaffine transformations and supervised learning for the automatic diagnosis of LV infarct MM Rohé, N Duchateau, M Sermesant, X Pennec Statistical Atlases and Computational Models of the Heart. Imaging and …, 2016 | 15 | 2016 |
| From dose reduction to contrast maximization: can deep learning amplify the impact of contrast media on brain magnetic resonance image quality? A reader study A Bône, S Ammari, Y Menu, C Balleyguier, E Moulton, É Chouzenoux, ... Investigative Radiology 57 (8), 527-535, 2022 | 14 | 2022 |
| Barycentric subspace analysis: a new symmetric group-wise paradigm for cardiac motion tracking MM Rohé, M Sermesant, X Pennec International Conference on Medical Image Computing and Computer-Assisted …, 2016 | 14 | 2016 |
| Propagation of myocardial fibre architecture uncertainty on electromechanical model parameter estimation: a case study R Molléro, D Neumann, MM Rohé, M Datar, H Lombaert, N Ayache, ... International Conference on Functional Imaging and Modeling of the Heart …, 2015 | 9 | 2015 |
| Automatic detection of pancreatic lesions and main pancreatic duct dilatation on portal venous CT scans using deep learning C Abi Nader, R Vetil, LK Wood, MM Rohe, A Bône, H Karteszi, ... Investigative Radiology 58 (11), 791-798, 2023 | 5 | 2023 |
| Highly reduced model of the cardiac function for fast simulation MM Rohé, R Molléro, M Sermesant, X Pennec 2016 IEEE 12th Image, Video, and Multidimensional Signal Processing Workshop …, 2016 | 5 | 2016 |
| Learning shape distributions from large databases of healthy organs: applications to zero-shot and few-shot abnormal pancreas detection R Vétil, C Abi-Nader, A Bône, MP Vullierme, MM Rohé, P Gori, I Bloch International Conference on Medical Image Computing and Computer-Assisted …, 2022 | 4 | 2022 |
| Prediction of post-ablation outcome in atrial fibrillation using shape parameterization and partial least squares regression S Jia, C Camaioni, MM Rohé, P Jaïs, X Pennec, H Cochet, M Sermesant International Conference on Functional Imaging and Modeling of the Heart …, 2017 | 4 | 2017 |
| Learning to diagnose cirrhosis from radiological and histological labels with joint self and weakly-supervised pretraining strategies E Sarfati, A Bone, MM Rohe, P Gori, I Bloch arXiv preprint arXiv:2302.08427, 2023 | 2 | 2023 |
| Feasibility of using deep learning techniques to assess hepatic fibrosis directly from magnetic resonance elastography source images M Rohé, E Oubel, M Grisoni, S Djedjos, R Myers, H Loomba, M Middleto The Liver Meeting® 2018, AASLD, 2018 | 2 | 2018 |
| Reduced representation of segmentation and tracking in cardiac images for group-wise longitudinal analysis MM Rohé Université Côte d'Azur, 2017 | 2 | 2017 |
| Going beyond voxel-wise deconvolution in perfusion MRI: learning and leveraging spatio-temporal regularities with the stU-Net JV Vialard, MM Rohé, P Robert, F Nicolas, A Bône | 1 | 2021 |
| METHOD FOR CHARACTERIZING AN ORGAN OF A PATIENT IN A MEDICAL IMAGE R Vétil, C Abi-Nader, A Bône, MM Rohé, P Gori, I Bloch | | 2024 |
Maxime SermesantInria, Université Côte d'Azur - IHU Liryc - 3IA Côte d'AzurAdresse e-mail validée de inria.fr
