Zengqiang (John) Yan
Ph.D. HKUST
Associate Professor
School of Electronic Information and Communications, Huazhong University of Science and Technology
Email: zyanad [at] connect (dot) ust (dot) hk OR z_yan [at] hust [dot] edu [dot] cn
Ph.D. HKUST
Associate Professor
School of Electronic Information and Communications, Huazhong University of Science and Technology
Email: zyanad [at] connect (dot) ust (dot) hk OR z_yan [at] hust [dot] edu [dot] cn
I am an Associate Professor of School of Electronic Information and Communications at Huazhong University of Science and Technology. Before joining HUST, I received my Ph.D. degree and completed a one-year post-doc both at the Department of Computer Science and Engineering at the Hong Kong University of Science and Technology, supervised by Prof. Kwang-Ting Tim Cheng.
My research interests include deep learning and medical image analysis, with specific focus on medical image segmentation, domain adaptation and federated learning. The main motivation is to develop annotation-effecient deep learning approaches to tackle medical imaging problems.
研究兴趣：人工智能、医学图像处理、计算机视觉
Looking for self-motivated undergraduate/postgraduate students to join my group. Feel free to contact me if you have interests.
欢迎本科生、保研生、直博生或计划出国（境）读博的同学加入我们团队。
Apr. 2024
Nannan's paper, entitled "From Optimization to Generalization: Fair Federated Learning against Quality Shift via Inter-Client Sharpness Matching", has been accepted by IJCAI 2024. Congratulations!
Apr. 2024
Xiayu's paper, entitled "UCTNet: Uncertainty-guided CNN-Transformer Hybrid Networks for Medical Image Segmentation", has been accepted by Pattern Recognition (PR). Congratulations!
Dec. 2023
Zhehao's paper, entitled "DTMFormer: Dynamic Token Merging for Boosting Transformer-based Medical Image Segmentation", has been accepted by AAAI 2024. Congratulations!
湖北省海外高层次创新人才, 2023
IEEE TMI Distinguished Reviewer Gold Level 2022-2023
"武汉英才"（优秀青年人才）, 2022
[# Co-First Author * Corresponding Author]
From Optimization to Generalization: Fair Federated Learning against Quality Shift via Inter-Client Sharpness Matching
Nannan Wu, Zhuo Kuang, Zengqiang Yan*, and Li Yu
International Joint Conference on Artificial Intelligence (IJCAI), 2024.
UCTNet: Uncertainty-Guided CNN-Transformer Hybrid Networks for Medical Image Segmentation
Xiayu Guo, Xian Lin, Xin Yang, Li Yu, Kwang-Ting Cheng, and Zengqiang Yan*
Pattern Recognition (PR), 2024.
Weakly Supervised Learning for Multi-Class Medical Image Segmentation via Feature Decomposition
Zhuo Kuang, Zengqiang Yan, and Li Yu
Computers in Biology and Medicine (CIBM), 2024.
DTMFormer: Dynamic Token Merging for Boosting Transformer-based Medical Image Segmentation
Zhehao Wang, Xian Lin, Nannan Wu, Li Yu, Kwang-Ting Cheng, and Zengqiang Yan*
AAAI Conference on Artificial Intelligence (AAAI), 2024.
FedA3I: Annotation Quality-Aware Aggregation for Federated Medical Image Segmentation Against Heterogeneous Annotation Noise
Nannan Wu, Zhaobin Sun, Zengqiang Yan*, and Li Yu
AAAI Conference on Artificial Intelligence (AAAI), 2024.
FedIOD: Federated Multi-Organ Segmentation from Partial Labels by Exploring Inter-Organ Dependency
Qin Wan#, Zengqiang Yan#, and Li Yu
IEEE Journal of Biomedical and Health Informatics (IEEE JBHI), 2023.
M2FTrans: Modality-Masked Fusion Transformer for Incomplete Multi-Modality Brain Tumor Segmentation
Junjie Shi, Li Yu, Qimin Cheng, Xin Yang, Kwang-Ting Cheng, and Zengqiang Yan*
IEEE Journal of Biomedical and Health Informatics (IEEE JBHI), 2023. accepted
ConvFormer: Plug-and-Play CNN-Style Transformers for Improving Medical Image Segmentation
Xian Lin, Zengqiang Yan*, Xianbo Deng, Chuansheng Zheng, and Li Yu
International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2023.
FedIIC: Towards Robust Federated Learning for Class-Imbalanced Medical Image Classification
Nannan Wu, Li Yu, Xin Yang, Kwang-Ting Cheng, and Zengqiang Yan*
International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2023. (Early Accept)
Affinity Feature Strengthening for Accurate, Complete and Robust Vessel Segmentation
Tianyi Shi, Xiaohuan Ding, Wei Zhou, Feng Pan, Zengqiang Yan, Xiang Bai, and Xin Yang
IEEE Journal of Biomedical and Health Informatics (IEEE JBHI), 2023. accepted
FedNoRo: Towards Noise-Robust Federated Learning By Addressing Class Imbalance and Label Noise Heterogeneity
Nannan Wu, Li Yu, Xuefeng Jiang, Kwang-Ting Cheng, and Zengqiang Yan*
International Joint Conference on Artificial Intelligence (IJCAI), 2023.
Cluster-Re-Supervision: Bridging the Gap Between Image-Level and Pixel-Wise Labels for Weakly Supervised Medical Image Segmentation
Zhuo Kuang, Zengqiang Yan*, Huiyu Zhou, and Li Yu*
IEEE Journal of Biomedical and Health Informatics (IEEE JBHI), 2023. accepted
BATFormer: Towards Boundary-Aware Lightweight Transformer for Efficient Medical Image Segmentation
Xian Lin, Li Yu, Kwang-Ting Cheng, and Zengqiang Yan*
IEEE Journal of Biomedical and Health Informatics (IEEE JBHI), 2022. accepted
The Lighter The Better: Rethinking Transformers in Medical Image Segmentation Through Adaptive Pruning
Xian Lin, Li Yu, Kwang-Ting Cheng, and Zengqiang Yan*
IEEE Transactions on Medical Imaging (IEEE TMI), 2022. accepted
FedMix: Mixed Supervised Federated Learning for Medical Image Segmentation
Jeffry Wicaksana, Zengqiang Yan*, Dong Zhang, Xijie Huang, Huimin Wu, Xin Yang, and Kwang-Ting Cheng
IEEE Transactions on Medical Imaging (IEEE TMI), 2022. accepted
Hierarchical Associative Encoding and Decoding for BottomUp Human Pose Estimation
Congju Du, Zengqiang Yan, Han Yu, Li Yu, and Zixiang Xiong
IEEE Transactions on Circuits and Systems for Video Technology (IEEE TCSVT), 2022. to appear
Customized Federated Learning for Multi-Source Decentralized Medical Image Classification
Jeffry Wicaksana, Zengqiang Yan*, Xin Yang, Yang Liu, Lixin Fan, Kwang-Ting Cheng
IEEE Journal of Biomedical and Health Informatics (IEEE JBHI), 2022. to appear
Symmetry-Aware Deep Learning for Cerebral Ventricle Segmentation with Intra-Ventricular Hemorrhage
Yineng Hua#, Zengqiang Yan#, Zhuo Kuang, Hang Zhang, Xianbo Deng, Li Yu
IEEE Journal of Biomedical and Health Informatics (IEEE JBHI), 2022. online published
Fracture R-CNN: An Anchor-Efficient Anti-Interference Framework for Skull Fracture Detection in CT Images
Xian Lin#, Zengqiang Yan#, Zhuo Kuang, Hang Zhang, Xianbo Deng, Li Yu
Medical Physics, 2022. online published
Uncertainty-Aware Deep Learning with Cross-Task Supervision for PHE Segmentation on CT Images
Zhuo Kuang#, Zengqiang Yan#, Li Yu, Xianbo Deng, Yineng Hua, Shuyun Li
IEEE Journal of Biomedical and Health Informatics (IEEE JBHI), vol. 26, no. 6, pp. 2615-2626, 2022.
Variation-Aware Federated Learning with Multi-Source Decentralized Medical Image Data
Zengqiang Yan, Jeffry Wicaksana, Zhiwei Wang, Xin Yang, Kwang-Ting Cheng
IEEE Journal of Biomedical and Health Informatics (IEEE JBHI), vol. 25, no. 7, pp. 2615-2628, 2021.
Enabling a Single Deep Learning Model for Accurate Gland Instance Segmentation: A Shape-aware Adversarial Learning Framework
Zengqiang Yan, Xin Yang, Kwang-Ting Cheng
IEEE Transactions on Medical Imaging (IEEE TMI), vol. 39, no. 6, pp. 2176-2189, Jun. 2020.
A Three-stage Deep Learning Model for Accurate Retinal Vessel Segmentation
Zengqiang Yan, Xin Yang, Kwang-Ting Cheng
IEEE Journal of Biomedical and Health Informatics (IEEE JBHI), vol. 23, no. 4, pp. 1427-1436, Jul. 2019.
ESI Highly Cited Paper
Joint Segment-level and Pixel-wise Losses for Deep Learning based Retinal Vessel Segmentation
Zengqiang Yan, Xin Yang, Kwang-Ting Cheng
IEEE Transactions on Biomedical Engineering (IEEE TBME), vol. 65, no. 9, pp. 1912-1923, Sept. 2018.
[
Github
]
ESI Highly Cited Paper
A Skeletal Similarity Metric for Quality Evaluation of Vessel Segmentation
Zengqiang Yan, Xin Yang, Kwang-Ting Cheng
IEEE Transactions on Medical Imaging (IEEE TMI), vol. 37, no. 4, pp. 1045-1057, Apr. 2018.
[
Github
]
A Deep Model with Shape-preserving Loss for Gland Instance Segmentation
Zengqiang Yan, Xin Yang, Kwang-Ting Cheng
International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2018, pp. 138-146.
Exploring Intermediate Representation for Monocular Vehicle Pose Estimation
Shichao Li, Zengqiang Yan, Hongyang Li, Kwang-Ting Cheng
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
