| Boundary loss for highly unbalanced segmentation H Kervadec, J Bouchtiba, C Desrosiers, E Granger, J Dolz, IB Ayed Medical image analysis 67, 2021 | 1100 | 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 | 385 | 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 | 315 | 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 | 153 | 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 | 151 | 2020 |
| Source-Free Domain Adaptation for Image Segmentation M Bateson, J Dolz, H Kervadec, H Lombaert, IB Ayed Medical Image Analysis, 102617, 2022 | 137 | 2022 |
| Curriculum semi-supervised segmentation H Kervadec, J Dolz, E Granger, IB Ayed Medical Image Computing and Computer Assisted Intervention (MICCAI), 2019 | 120 | 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 | 109 | 2022 |
| International conference on medical imaging with deep learning H Kervadec, J Bouchtiba, C Desrosiers, E Granger, J Dolz, IB Ayed Microtome Publishing, 2019 | 72 | 2019 |
| Discretely-constrained deep network for weakly supervised segmentation J Peng, H Kervadec, J Dolz, IB Ayed, M Pedersoli, C Desrosiers Neural Networks 130, 2020 | 48 | 2020 |
| 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 | 40 | 2021 |
| Constrained domain adaptation for segmentation M Bateson, H Kervadec, J Dolz, H Lombaert, IB Ayed Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2019 | 37 | 2019 |
| 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 | 27* | 2021 |
| Log-barrier constrained cnns H Kervadec, J Dolz, J Yuan, C Desrosiers, E Granger, IB Ayed Computing Research Repository (CoRR), 2019 | 13 | 2019 |
| 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 | 9 | 2020 |
| 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 |
| 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 | 6 | 2023 |
| On the dice loss gradient and the ways to mimic it H Kervadec, M de Bruijne arXiv preprint arXiv:2304.04319, 2023 | 6 | 2023 |
| On the dice loss variants and sub-patching H Kervadec, M De Bruijne Medical Imaging with Deep Learning, short paper track, 2023 | 5 | 2023 |
| Spatially continuous dual optimization on compactness function for image segmentation L Tan, S Ma, J Xu, J Pan, J Yuan, H Kervadec, M Pelillo Pattern Recognition, 112613, 2025 | 4 | 2025 |