| 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 | 367 | 2019 |
| Real-time automatic ejection fraction and foreshortening detection using deep learning E Smistad, A Østvik, IM Salte, D Melichova, TM Nguyen, K Haugaa, ... IEEE transactions on ultrasonics, ferroelectrics, and frequency control 67 …, 2020 | 49 | 2020 |
| 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 |
| Detection of cardiac events in echocardiography using 3D convolutional recurrent neural networks AM Fiorito, A Østvik, E Smistad, S Leclerc, O Bernard, L Lovstakken 2018 IEEE International Ultrasonics Symposium (IUS), 1-4, 2018 | 33 | 2018 |
| 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 |
| Fully automatic real-time ejection fraction and MAPSE measurements in 2D echocardiography using deep neural networks E Smistad, A Østvik, IM Salte, S Leclerc, O Bernard, L Lovstakken 2018 IEEE International Ultrasonics Symposium (IUS), 1-4, 2018 | 29 | 2018 |
| 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 |
| Segmentation of apical long axis, four-and two-chamber views using deep neural networks E Smistad, IM Salte, A Østvik, S Leclerc, O Bernard, L Lovstakken 2019 IEEE International Ultrasonics Symposium (IUS), 8-11, 2019 | 17 | 2019 |
| 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 |
| Left ventricle segmentation in 3D ultrasound by combining structured random forests with active shape models F Khellaf, S Leclerc, JD Voorneveld, RS Bandaru, JG Bosch, O Bernard Medical Imaging 2018: Image Processing 10574, 120-129, 2018 | 9 | 2018 |
| Deep learning segmentation in 2d echocardiography using the camus dataset: Automatic assessment of the anatomical shape validity S Leclerc, E Smistad, A Østvik, F Cervenansky, F Espinosa, T Espeland, ... arXiv preprint arXiv:1908.02994, 2019 | 6 | 2019 |
| Robustly segmenting quadriceps muscles of ultra-endurance athletes with weakly supervised U-Net HT Nguyen, P Croisille, M Viallon, S Leclerc, S Grange, R Grange, ... arXiv preprint arXiv:1908.08294, 2019 | 5 | 2019 |
| LU-Net: a multi-task network to improve the robustness of segmentation of left ventriclular structures by deep learning in 2D echocardiography S Leclerc, E Smistad, A Østvik, F Cervenansky, F Espinosa, T Espeland, ... arXiv preprint arXiv:2004.02043, 2020 | 3 | 2020 |
| 4D segmentation of the thoracic aorta from 4D flow MRI using deep learning DM Marin-Castrillon, A Lalande, S Leclerc, K Ambarki, MC Morgant, ... Magnetic Resonance Imaging, 2023 | 2 | 2023 |
| Automatisation de la segmentation sémantique de structures cardiaques en imagerie ultrasonore par apprentissage supervisé SMS Leclerc INSA Lyon - CREATIS laboratory, 2019 | 2 | 2019 |
| Comparison of In-Vivo and Ex-Vivo Ascending Aorta Elastic Properties through Automatic Deep Learning Segmentation of Cine-MRI and Biomechanical Testing E Markodimitrakis, S Lin, E Koutoulakis, DM Marín-Castrillón, ... Journal of Clinical Medicine 12 (2), 402, 2023 | 1 | 2023 |
