Zhenyu Tang, associate professor. He received his Ph.D. degree from the University of Duisburg-Essen, Germany and conducted postdoctoral research at the Institute of Automation, Chinese Academy of Sciences, and at the University of North Carolina at Chapel Hill, USA. His research interests include image processing, pattern recognition, and machine learning. He has published more than 30 papers with over 2,500 citations (Google Scholar). He leads several research projects funded by the National Natural Science Foundation of China (General Program and Young Scientists Fund) and the Beijing Natural Science Foundation, and has participated as a key member in China’s National Key R&D Program. 

Selected Paper（Journal）：

[1] Zhenyu Tang, Jiannan Li, Jingliang Cheng, Zhi-Cheng Li, Zhenyu Zhang, and Jing Yan*, Pre-operative Overall Survival Prediction of Diffuse Glioma Enhanced by Longitudinal Data, IEEE Journal of Biomedical and Health Informatics, 2025. (Q1, IF: 7.7)

[2] Ziman Yin , Zhengze Ni , Yuxiang Ren , Dong Nie , and Zhenyu Tang*, Multi-Sequence Brain Tumor Segmentation Boosted by Deep Semantic Features, Medical Physics, 91, pp. 376-387, 2025. (Q1, IF: 3.2)

[3] Huabing Liu, Zhengze Ni, Dong Nie, Dinggang Shen, Jinda Wang, and Zhenyu Tang*, Multimodal Brain Tumor Segmentation Boosted by Monomodal Normal Brain Images, IEEE Transactions on Image Processing, 33, pp. 1199-1210, 2024. (Q1, IF: 10.6)

[4] Huabing Liu, Dong Nie, Jian Yang, Jinda Wang, and Zhenyu Tang*, A New Multi-Atlas Based Deep Learning Segmentation Framework with Differentiable Atlas Feature Warping, IEEE Journal of Biomedical and Health Informatics, 28(3), pp. 1484-1493, 2024. (Q1, IF: 7.7)

[5] Zhenyu Tang, Hongda Cao, Yuyun Xu, Qing Yang, Jinda Wang, and Han Zhang, Overall survival time prediction for glioblastoma using multimodal deep KNN, Physics in Medicine & Biology, 2022. (Q2, IF: 3.5)

[6] Zhenyu Tang, Wei Zhao, Xingzhi Xie, Zheng Zhong, Feng Shi, Jun Liu, and Dinggang Shen*, Severity assessment of COVID-19 using CT image features and laboratory indices, Physics in Medicine & Biology, 2021. (Q2, IF: 3.5, ESI 高被引)

[7] Zhenyu Tang, Xianli Liu, Yang Li, Pew-Thian Yap, and Dinggang Shen*, Multi-Atlas Brain Parcellation Using Squeeze-and-Excitation Fully Convolutional Networks, IEEE Transactions on Image Processing, 29, pp. 6864-6872, 2020. (Q1, IF: 10.6)

[8] Zhenyu Tang, Yuyun Xu, Lei Jin, Abudumijiti Aibaidula, Junfeng Lu, Zhicheng Jiao, Jinsong Wu, Han Zhang, and Dinggang Shen*, Deep Learning of Imaging Phenotype and Genotype for Predicting Overall Survival Time of Glioblastoma Patients, IEEE Transactions on Medical Imaging, 39(6), pp. 2100-2109, 2020. (Q1, IF: 10.6)

[9] Zhenyu Tang, Pew-Thian Yap, and Dinggang Shen*, A New Multi-Atlas Registration Framework for Multimodal Pathological Images Using Conventional Monomodal Normal Atlases, IEEE Transactions on Image Processing, 28(5), pp. 2293-2304, 2019. (Q1, IF: 10.6)

[10] Zhenyu Tang, Pew-Thian Yap, and Dinggang Shen*, A New Image Similarity Metric for Improving Deformation Consistency in Graph-Based Groupwise Image Registration, IEEE Transactions on Biomedical Engineering, 66(8), pp. 2192-2199, 2019. (Q1, IF: 4.6,  Featured article)

[11] Zhenyu Tang, Sahar Ahmad, Pew-Thian Yap, and Dinggang Shen*, Multi-Atlas Segmentation of MR Tumor Brain Images Using Low-Rank Based Image Recovery, IEEE Transactions on Medical Imaging, 37(10), pp. 2224-2235, 2018. (Q1, IF: 10.6)

Selected Paper（Conference）：

[1] Libiao Chen, Dong Nie, Junjun Pan, Jing Yan, and Zhenyu Tang*, Generalized Zero-Shot Classification via Semantics-Free Inter-Class Feature Generation, CVPR 2025. 

[2] Ziman Yin, Dong Nie, Shuo Li, Junjun Pan, and Zhenyu Tang*, Iterative Foundation-Dedicated Learning: Optimized Key Frames, Prompts and Memories for Semi-Supervised Segmentation, MICCAI 2025. 

[3] Zhenyu Tang, Zhenyu Zhang, Huabing Liu, Dong Nie, and Jing Yan*, Pre-operative Survival Prediction of Diffuse Glioma Patients with Joint Tumor Subtyping, MICCAI 2023. 

[4] Huabin Liu, Dong Nie, Jinda Wang, and Zhenyu Tang*, Multimodal Brain Tumor Segmentation Using Contrastive Learning based Feature Comparison with Monomodal Normal Brain Images, MICCAI 2022. 

[5] Xiangdong Guo, Haifeng Zhao, and Zhenyu Tang*, An Improved Deep Learning Approach for Thyroid Nodule Diagnosis, ISBI 2020.

[6] Zhenyu Tang, Yuyun Xu, Zhicheng Jiao, Junfeng Lu, Lei Jin, Abudumijiti Aibaidula, Jinsong Wu, Qian Wang, Han Zhang*, and Dinggang Shen, Pre-operative Overall Survival Time Prediction for Glioblastoma Patients Using Deep Learning on Both Imaging Phenotype and Genotype, MICCAI 2019. 

[7] Xianli Liu, Haifeng Zhao, Shaojie Zhang, and Zhenyu Tang*, Brain Image Parcellation Using Multi-Atlas Guided Adversarial Fully Convolutional Network, ISBI 2019.

[8] Zhenyu Tang, Yue Cui, and Bo Jiang*, Groupwise Registration of MR Brain Images Containing Tumors via Spatially Constrained Low-Rank Based Image Recovery, MICCAI 2017.