| Deep learning for segmentation using an open large-scale dataset in 2D echocardiography S Leclerc, E Smistad, J Pedrosa, A Østvik, F Cervenansky, F Espinosa, ... IEEE transactions on medical imaging 38 (9), 2198-2210, 2019 | 369 | 2019 |
| New OFSEP recommendations for MRI assessment of multiple sclerosis patients: special consideration for gadolinium deposition and frequent acquisitions JC Brisset, S Kremer, S Hannoun, F Bonneville, F Durand-Dubief, ... Journal of Neuroradiology 47 (4), 250-258, 2020 | 50 | 2020 |
| Artificial intelligence to predict clinical disability in patients with multiple sclerosis using FLAIR MRI P Roca, A Attye, L Colas, A Tucholka, P Rubini, S Cackowski, J Ding, ... Diagnostic and Interventional Imaging 101 (12), 795-802, 2020 | 44 | 2020 |
| Fast electron tomography: Applications to beam sensitive samples and in situ TEM or operando environmental TEM studies S Koneti, L Roiban, F Dalmas, C Langlois, AS Gay, A Cabiac, T Grenier, ... Materials Characterization 151, 480-495, 2019 | 38 | 2019 |
| A fully automatic and multi-structural segmentation of the left ventricle and the myocardium on highly heterogeneous 2D echocardiographic data S Leclerc, T Grenier, F Espinosa, O Bernard 2017 IEEE International Ultrasonics Symposium (IUS), 1-4, 2017 | 34 | 2017 |
| LU-Net: a multistage attention network to improve the robustness of segmentation of left ventricular structures in 2-D echocardiography S Leclerc, E Smistad, A Østvik, F Cervenansky, F Espinosa, T Espeland, ... IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control 67 …, 2020 | 29 | 2020 |
| RU-Net: A refining segmentation network for 2D echocardiography S Leclerc, E Smistad, T Grenier, C Lartizien, A Ostvik, F Cervenansky, ... 2019 IEEE International Ultrasonics Symposium (IUS), 1160-1163, 2019 | 28 | 2019 |
| Evaluation of noise and blur effects with SIRT-FISTA-TV reconstruction algorithm: Application to fast environmental transmission electron tomography H Banjak, T Grenier, T Epicier, S Koneti, L Roiban, AS Gay, I Magnin, ... Ultramicroscopy 189, 109-123, 2018 | 27 | 2018 |
| A pilot study on convolutional neural networks for motion estimation from ultrasound images E Evain, K Faraz, T Grenier, D Garcia, M De Craene, O Bernard IEEE transactions on ultrasonics, ferroelectrics, and frequency control 67 …, 2020 | 26 | 2020 |
| Unifying variational approach and region growing segmentation JL Rose, T Grenier, C Revol-Muller, C Odet 2010 18th European Signal Processing Conference, 1781-1785, 2010 | 26 | 2010 |
| 3D robust adaptive region growing for segmenting [18F] fluoride ion PET images T Grenier, C Revol-Muller, N Costes, M Janier, G Gimenez 2006 IEEE Nuclear Science Symposium Conference Record 5, 2644-2648, 2006 | 20 | 2006 |
| Unsupervised spatio-temporal filtering of image sequences. a mean-shift specification S Mure, T Grenier, DS Meier, CRG Guttmann, H Benoit-Cattin Pattern Recognition Letters 68, 48-55, 2015 | 18 | 2015 |
| Hybrid approach for multiparametric mean shift filtering T Grenier, C Revol-Muller, G Gimenez 2006 International Conference on Image Processing, 1541-1544, 2006 | 18 | 2006 |
| Deep learning applied to Multi-Structure segmentation in 2D echocardiography: A preliminary investigation of the required database size S Leclerc, E Smistad, T Grenier, C Lartizien, A Ostvik, F Espinosa, ... 2018 IEEE International Ultrasonics Symposium (IUS), 1-4, 2018 | 15 | 2018 |
| Automated seeds location for whole body NaF PET segmentation T Grenier, C Revol-Muller, N Costes, M Janier, G Gimenez IEEE transactions on nuclear science 52 (5), 1401-1405, 2005 | 15 | 2005 |
| Deep learning detection of nanoparticles and multiple object tracking of their dynamic evolution during in situ ETEM studies K Faraz, T Grenier, C Ducottet, T Epicier Scientific Reports 12 (1), 2484, 2022 | 13 | 2022 |
| Quantitative magnetic resonance imaging assessment of the quadriceps changes during an extreme mountain ultramarathon HT Nguyen, T Grenier, B Leporq, C Le Goff, B Gilles, S Grange, R Grange, ... Medicine and Science in Sports and Exercise 53 (4), 869-881, 2021 | 10 | 2021 |
| Optimization of Mean-Shift scale parameters on the EGEE grid. T Li, S Camarasu-Pop, T Glatard, T Grenier, H Benoit-Cattin HealthGrid, 203-214, 2010 | 10 | 2010 |
| A more interpretable classifier for multiple sclerosis V Wargnier-Dauchelle, T Grenier, F Durand-Dubief, F Cotton, M Sdika 2021 IEEE 18th international symposium on biomedical imaging (ISBI), 1062-1066, 2021 | 9 | 2021 |
| Region growing: When simplicity meets theory–region growing revisited in feature space and variational framework C Revol-Muller, T Grenier, JL Rose, A Pacureanu, F Peyrin, C Odet Computer Vision, Imaging and Computer Graphics. Theory and Application: 7th …, 2013 | 9 | 2013 |
Olivier BernardCREATISAdresse e-mail validée de creatis.insa-lyon.fr
