Boundary loss for highly unbalanced segmentation H Kervadec, J Bouchtiba, C Desrosiers, E Granger, J Dolz, IB Ayed Medical image analysis 67, 2021 | 556 | 2021 |
Constrained-CNN losses for weakly supervised segmentation H Kervadec, J Dolz, M Tang, E Granger, Y Boykov, IB Ayed Medical Image Analysis 54, 2019 | 295 | 2019 |
Few-Shot Segmentation Without Meta-Learning: A Good Transductive Inference Is All You Need? M Boudiaf, H Kervadec, ZI Masud, P Piantanida, IB Ayed, J Dolz CVPR, 2021 | 214 | 2021 |
Source-relaxed domain adaptation for image segmentation M Bateson, H Kervadec, J Dolz, H Lombaert, IB Ayed Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2020 | 106 | 2020 |
Bounding boxes for weakly supervised segmentation: Global constraints get close to full supervision H Kervadec, J Dolz, S Wang, E Granger, IB Ayed Medical Imaging with Deep Learning (MIDL), 2020 | 100 | 2020 |
Curriculum semi-supervised segmentation H Kervadec, J Dolz, E Granger, IB Ayed Medical Image Computing and Computer Assisted Intervention (MICCAI), 2019 | 88 | 2019 |
Constrained Deep Networks: Lagrangian Optimization via Log-Barrier Extensions H Kervadec, J Dolz, J Yuan, C Desrosiers, E Granger, IB Ayed EUSIPCO, 962--966, 2022 | 75 | 2022 |
Source-Free Domain Adaptation for Image Segmentation M Bateson, J Dolz, H Kervadec, H Lombaert, IB Ayed Medical Image Analysis, 102617, 2022 | 61 | 2022 |
Discretely-constrained deep network for weakly supervised segmentation J Peng, H Kervadec, J Dolz, IB Ayed, M Pedersoli, C Desrosiers Neural Networks 130, 2020 | 40 | 2020 |
Constrained domain adaptation for segmentation M Bateson, H Kervadec, J Dolz, H Lombaert, IB Ayed Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2019 | 29 | 2019 |
Constrained domain adaptation for image segmentation M Bateson, J Dolz, H Kervadec, H Lombaert, IB Ayed IEEE Transactions on Medical Imaging 40 (7), 1875-1887, 2021 | 23 | 2021 |
Beyond pixel-wise supervision: semantic segmentation with higher-order shape descriptors H Kervadec, H Bahig, L Letourneau-Guillon, J Dolz, IB Ayed Medical Imaging with Deep Learning (MIDL), 2021 | 16* | 2021 |
Log-barrier constrained cnns H Kervadec, J Dolz, J Yuan, C Desrosiers, E Granger, IB Ayed Computing Research Repository (CoRR), 2019 | 11 | 2019 |
Polystyrene: the decentralized data shape that never dies S Bouget, H Kervadec, AM Kermarrec, F Taïani 2014 IEEE 34th International Conference on Distributed Computing Systems …, 2014 | 8 | 2014 |
Laplacian pyramid-based complex neural network learning for fast MR imaging H Liang, Y Gong, H Kervadec, C Li, J Yuan, X Liu, H Zheng, S Wang Medical Imaging with Deep Learning (MIDL), 2020 | 5 | 2020 |
On the dice loss variants and sub-patching H Kervadec, M De Bruijne Medical Imaging with Deep Learning, short paper track, 2023 | 3 | 2023 |
Nested star-shaped objects segmentation using diameter annotations R Camarasa, H Kervadec, ME Kooi, J Hendrikse, PJ Nederkoorn, D Bos, ... Medical image analysis 90, 102934, 2023 | 2 | 2023 |
On the dice loss gradient and the ways to mimic it H Kervadec, M de Bruijne arXiv preprint arXiv:2304.04319, 2023 | 2 | 2023 |
Differentiable Boundary Point Extraction for Weakly Supervised Star-shaped Object Segmentation R Camarasa, H Kervadec, D Bos, M de Bruijne Medical Imaging with Deep Learning, 2022 | 2 | 2022 |
Constrained deep networks for medical image segmentation H Kervadec École de technologie supérieure, 2020 | 2 | 2020 |