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Sarah Leclerc
Sarah Leclerc
Associate professor at the laboratory ImVia, Dijon, France
Verified email at u-bourgogne.fr - Homepage
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Cited by
Year
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
2142019
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
292017
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
232020
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
192018
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
182018
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
162020
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
142019
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
112018
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
102019
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, 105740J, 2018
72018
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
52019
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
32019
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
12020
Automatisation de la segmentation sémantique de structures cardiaques en imagerie ultrasonore par apprentissage supervisé
SMS Leclerc
INSA Lyon - CREATIS laboratory, 2019
12019
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