| 3D deeply supervised network for automated segmentation of volumetric medical images Q Dou, L Yu, H Chen, Y Jin, X Yang, J Qin, PA Heng Medical image analysis 41, 40-54, 2017 | 611 | 2017 |
| 3D deeply supervised network for automatic liver segmentation from CT volumes Q Dou, H Chen, Y Jin, L Yu, J Qin, PA Heng Medical Image Computing and Computer-Assisted Intervention–MICCAI 2016: 19th …, 2016 | 427 | 2016 |
| Deep learning for automated contouring of primary tumor volumes by MRI for nasopharyngeal carcinoma L Lin, Q Dou, YM Jin, GQ Zhou, YQ Tang, WL Chen, BA Su, F Liu, CJ Tao, ... Radiology 291 (3), 677-686, 2019 | 283 | 2019 |
| SV-RCNet: workflow recognition from surgical videos using recurrent convolutional network Y Jin, Q Dou, H Chen, L Yu, J Qin, CW Fu, PA Heng IEEE transactions on medical imaging 37 (5), 1114-1126, 2018 | 268 | 2018 |
| Medical sam adapter: Adapting segment anything model for medical image segmentation J Wu, Y Zhang, R Fu, H Fang, Y Liu, Z Wang, Y Xu, Y Jin arXiv preprint arXiv:2304.12620, 2023 | 227 | 2023 |
| Automated pulmonary nodule detection via 3d convnets with online sample filtering and hybrid-loss residual learning Q Dou, H Chen, Y Jin, H Lin, J Qin, PA Heng Medical Image Computing and Computer Assisted Intervention− MICCAI 2017 …, 2017 | 167 | 2017 |
| Multi-task recurrent convolutional network with correlation loss for surgical video analysis Y Jin, H Li, Q Dou, H Chen, J Qin, CW Fu, PA Heng Medical image analysis 59, 101572, 2020 | 162 | 2020 |
| Robust multimodal brain tumor segmentation via feature disentanglement and gated fusion C Chen, Q Dou, Y Jin, H Chen, J Qin, PA Heng Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 143 | 2019 |
| Incorporating temporal prior from motion flow for instrument segmentation in minimally invasive surgery video Y Jin, K Cheng, Q Dou, PA Heng Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 108 | 2019 |
| Comparative validation of multi-instance instrument segmentation in endoscopy: Results of the robust-mis 2019 challenge T Roß, A Reinke, PM Full, M Wagner, H Kenngott, M Apitz, H Hempe, ... Medical Image Analysis 70, 101920, 2021 | 100* | 2021 |
| Source-free domain adaptive fundus image segmentation with denoised pseudo-labeling C Chen, Q Liu, Y Jin, Q Dou, PA Heng Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th …, 2021 | 86 | 2021 |
| Trans-SVNet: Accurate Phase Recognition from Surgical Videos via Hybrid Embedding Aggregation Transformer X Gao, Y Jin, Y Long, Q Dou, PA Heng MICCAI 2021, 2021 | 85 | 2021 |
| Difficulty-aware meta-learning for rare disease diagnosis X Li, L Yu, Y Jin, CW Fu, L Xing, PA Heng Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 71 | 2020 |
| Medsegdiff-v2: Diffusion based medical image segmentation with transformer J Wu, H Ji, Wei, Fu, M Xu, Y Jin, Y Xu AAAI 2024, 2024 | 69 | 2024 |
| Temporal Memory Relation Network for Workflow Recognition from Surgical Video Y Jin, Y Long, C Chen, Z Zhao, Q Dou, PA Heng IEEE Transactions on Medical Imaging (TMI), 2021 | 67 | 2021 |
| Automatic Gesture Recognition in Robot-assisted Surgery with Reinforcement Learning and Tree Search X Gao, Y Jin, Q Dou, PA Heng ICRA 2020, 2020 | 59 | 2020 |
| Comparative validation of machine learning algorithms for surgical workflow and skill analysis with the heichole benchmark M Wagner, BP Müller-Stich, A Kisilenko, D Tran, P Heger, L Mündermann, ... Medical image analysis 86, 102770, 2023 | 52 | 2023 |
| Reconfigurable interlocking furniture P Song, CW Fu, Y Jin, H Xu, L Liu, PA Heng, D Cohen-Or ACM Transactions on Graphics (TOG) 36 (6), 1-14, 2017 | 49 | 2017 |
| Learning with privileged multimodal knowledge for unimodal segmentation C Chen, Q Dou, Y Jin, Q Liu, PA Heng IEEE transactions on medical imaging 41 (3), 621-632, 2021 | 43 | 2021 |
| Learning Motion Flows for Semi-supervised Instrument Segmentation from Robotic Surgical Video Z Zhao, Y Jin, X Gao, Q Dou, PA Heng MICCAI 2020, 2020 | 36 | 2020 |
Pheng Ann HengProfessor, Computer Science & Engineering, Chinese University of Hong Kong在 cse.cuhk.edu.hk 的电子邮件经过验证
