| Joint segment-level and pixel-wise losses for deep learning based retinal vessel segmentation Z Yan, X Yang, KT Cheng IEEE Transactions on Biomedical Engineering 65 (9), 1912-1923, 2018 | 399 | 2018 |
| A three-stage deep learning model for accurate retinal vessel segmentation Z Yan, X Yang, KT Cheng IEEE journal of Biomedical and Health Informatics 23 (4), 1427-1436, 2019 | 305 | 2019 |
| Variation-aware federated learning with multi-source decentralized medical image data Z Yan, J Wicaksana, Z Wang, X Yang, KT Cheng IEEE Journal of Biomedical and Health Informatics 25 (7), 2615-2628, 2020 | 100 | 2020 |
| A skeletal similarity metric for quality evaluation of retinal vessel segmentation Z Yan, X Yang, KT Cheng IEEE transactions on medical imaging 37 (4), 1045-1057, 2017 | 62 | 2017 |
| A Deep Model with Shape-preserving Loss for Gland Instance Segmentation Z Yan, X Yang, KTT Cheng International Conference on Medical Image Computing and Computer Assisted …, 2018 | 47* | 2018 |
| Enabling a single deep learning model for accurate gland instance segmentation: A shape-aware adversarial learning framework Z Yan, X Yang, KT Cheng IEEE transactions on medical imaging 39 (6), 2176-2189, 2020 | 42 | 2020 |
| Describing upper-body motions based on labanotation for learning-from-observation robots K Ikeuchi, Z Ma, Z Yan, S Kudoh, M Nakamura International Journal of Computer Vision 126, 1415-1429, 2018 | 39 | 2018 |
| Exploring intermediate representation for monocular vehicle pose estimation S Li, Z Yan, H Li, KT Cheng Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 34 | 2021 |
| FedMix: Mixed Supervised Federated Learning for Medical Image Segmentation J Wicaksana, Z Yan*, D Zhang, X Huang, H Wu, X Yang, KT Cheng IEEE Transactions on Medical Imaging, 2022 | 31 | 2022 |
| Beyond the interference problem: hierarchical patterns for multiple-projector structured light system Z Yan, L Yu, Y Yang, Q Liu Applied optics 53 (17), 3621-3632, 2014 | 25 | 2014 |
| BATFormer: Towards Boundary-Aware Lightweight Transformer for Efficient Medical Image Segmentation X Lin, L Yu, KT Cheng, Z Yan* IEEE Journal of Biomedical and Health Informatics, 2023 | 23* | 2023 |
| Customized Federated Learning for Multi-Source Decentralized Medical Image Classification J Wicaksana, Z Yan*, X Yang, Y Liu, L Fan, KT Cheng IEEE Journal of Biomedical and Health Informatics, 2022 | 19 | 2022 |
| The Lighter The Better: Rethinking Transformers in Medical Image Segmentation Through Adaptive Pruning X Lin, L Yu, KT Cheng, Z Yan* IEEE Transactions on Medical Imaging, 2022 | 12 | 2022 |
| Affinity feature strengthening for accurate, complete and robust vessel segmentation T Shi, X Ding, W Zhou, F Pan, Z Yan, X Bai, X Yang IEEE Journal of Biomedical and Health Informatics, 2023 | 10 | 2023 |
| FedIIC: Towards Robust Federated Learning for Class-Imbalanced Medical Image Classification N Wu, L Yu, X Yang, KT Cheng, Z Yan* MICCAI 2023, 2023 | 10* | 2023 |
| SAMUS: Adapting Segment Anything Model for Clinically-Friendly and Generalizable Ultrasound Image Segmentation X Lin, Y Xiang, L Zhang, X Yang, Z Yan*, L Yu arXiv preprint arXiv:2309.06824, 2023 | 9 | 2023 |
| Frequency estimation of the plenoptic function using the autocorrelation theorem C Zhu, L Yu, Z Yan, S Xiang IEEE Transactions on Computational Imaging 3 (4), 966-981, 2017 | 8 | 2017 |
| Texture edge-guided depth recovery for structured light-based depth sensor H Deng, J Wu, L Zhu, Z Yan, L Yu Multimedia Tools and Applications 76, 4211-4226, 2017 | 8 | 2017 |
| FedNoRo: Towards Noise-Robust Federated Learning by Addressing Class Imbalance and Label Noise Heterogeneity N Wu, L Yu, X Jiang, KT Cheng, Z Yan* IJCAI-23, 2023 | 5 | 2023 |
| Fracture R‐CNN: An anchor‐efficient anti‐interference framework for skull fracture detection in CT images X Lin#, Z Yan#, Z Kuang, H Zhang, X Deng, L Yu Medical Physics, 2022 | 5 | 2022 |
Kwang-Ting (Tim) ChengChair Professor of ECE and CSE, HKUSTVerified email at ust.hk
