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ORCIDZhenyu Tang 0002
Person information
- affiliation: Beihang University, Beijing Advanced Innovation Center for Big Data and Brain Computing, Beijing, China
- affiliation: Anhui University, Departmnet of computer science and technology, Hefei, China
- affiliation: University of North Carolina at Chapel Hill, Department of Radiology and BRIC, NC, USA
- affiliation: Chinese Academy of Science, Automation Institute, China
- affiliation (PhD 2011): University of Duisburg-Essen, department of Computer Engineering, Germany
Other persons with the same name
- Zhenyu Tang — disambiguation page
- Zhenyu Tang 0001
![[0000-0001-5544-9727]](https://dblp.dagstuhl.de/img/orcid-mark.12x12.png "0000-0001-5544-9727")
— University of Maryland, Department of Computer Science, College Park, MD, USA (and 2 more) - Zhenyu Tang 0003 — University of California, Computer Engineering Department, School of Engineering, Santa Cruz, CA, USA
- Zhenyu Tang 0004 — Peking University, Beijing, China
- Zhenyu Tang 0005 — Shanghai Jiao Tong University, China
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2020 – today
- 2024
[j10]Huabing Liu, Zhengze Ni, Dong Nie, Dinggang Shen, Jinda Wang, Zhenyu Tang:
Multimodal Brain Tumor Segmentation Boosted by Monomodal Normal Brain Images. IEEE Trans. Image Process. 33: 1199-1210 (2024)- [j9]Huabing Liu, Dong Nie, Jian Yang, Jinda Wang, Zhenyu Tang:
A New Multi-Atlas Based Deep Learning Segmentation Framework With Differentiable Atlas Feature Warping. IEEE J. Biomed. Health Informatics 28(3): 1484-1493 (2024) - 2023
- [c7]Zhenyu Tang, Zhenyu Zhang, Huabing Liu, Dong Ni, Jing Yan:
Pre-operative Survival Prediction of Diffuse Glioma Patients with Joint Tumor Subtyping. MICCAI (4) 2023: 786-795 - 2022
- [j8]Hancan Zhu, Mingxia Liu, Zhenyu Tang, Shuai Wang:
Editorial: Weakly supervised deep learning-based methods for brain image analysis. Frontiers Neuroinformatics 16 (2022) - [c6]Huabing Liu, Dong Ni, Dinggang Shen, Jinda Wang, Zhenyu Tang:
Multimodal Brain Tumor Segmentation Using Contrastive Learning Based Feature Comparison with Monomodal Normal Brain Images. MICCAI (5) 2022: 118-127 - [c5]Yuyan Ge, Zhenyu Tang, Lei Ma, Caiwen Jiang, Feng Shi, Shaoyi Du, Dinggang Shen:
Multi-scale and Focal Region Based Deep Learning Network for Fine Brain Parcellation. MLMI@MICCAI 2022: 466-475 - 2021
- [j7]Kelei He, Wei Zhao, Xingzhi Xie, Wen Ji, Mingxia Liu, Zhenyu Tang, Yinghuan Shi, Feng Shi, Yang Gao, Jun Liu, Junfeng Zhang, Dinggang Shen:
Synergistic learning of lung lobe segmentation and hierarchical multi-instance classification for automated severity assessment of COVID-19 in CT images. Pattern Recognit. 113: 107828 (2021) - 2020
- [j6]Zhenyu Tang, Xianli Liu, Yang Li, Pew-Thian Yap, Dinggang Shen:
Multi-Atlas Brain Parcellation Using Squeeze-and-Excitation Fully Convolutional Networks. IEEE Trans. Image Process. 29: 6864-6872 (2020) - [j5]Zhenyu Tang, Yuyun Xu, Lei Jin, Abudumijiti Aibaidula, Junfeng Lu, Zhicheng Jiao, Jinsong Wu, Han Zhang, Dinggang Shen:
Deep Learning of Imaging Phenotype and Genotype for Predicting Overall Survival Time of Glioblastoma Patients. IEEE Trans. Medical Imaging 39(6): 2100-2109 (2020) - [j4]Yang Li, Jingyu Liu, Zhenyu Tang, Baiying Lei:
Deep Spatial-Temporal Feature Fusion From Adaptive Dynamic Functional Connectivity for MCI Identification. IEEE Trans. Medical Imaging 39(9): 2818-2830 (2020) - [c4]Meng Kong, Haifeng Zhao, Shaojie Zhang, Zhenyu Tang:
Two-stage Generative Adversarial Recovery Network for MR Brain Images Containing Tumors. ICBBS 2020: 20-24 - [c3]Ying Bai, Haifeng Zhao, Shaojie Zhang, Dong Nie, Zhenyu Tang:
Multi-scale Hierarchy Feature Fusion Generative Adversarial Network for Low-Dose CT Denoising. ICBBS 2020: 102-106 - [c2]Xiao Zhang, Haifeng Zhao, Zhenyu Tang, Shaojie Zhang:
Brain Image Parcellation Using Fully Convolutional Network with Adaptively Selected Features from Brain Atlases. ICBBS 2020: 107-111 - [i3]Zhenyu Tang, Wei Zhao, Xingzhi Xie, Zheng Zhong, Feng Shi, Jun Liu, Dinggang Shen:
Severity Assessment of Coronavirus Disease 2019 (COVID-19) Using Quantitative Features from Chest CT Images. CoRR abs/2003.11988 (2020) - [i2]Feng Shi, Jun Wang, Jun Shi, Ziyan Wu, Qian Wang, Zhenyu Tang, Kelei He, Yinghuan Shi, Dinggang Shen:
Review of Artificial Intelligence Techniques in Imaging Data Acquisition, Segmentation and Diagnosis for COVID-19. CoRR abs/2004.02731 (2020) - [i1]Kelei He, Wei Zhao, Xingzhi Xie, Wen Ji, Mingxia Liu, Zhenyu Tang, Feng Shi, Yang Gao, Jun Liu, Junfeng Zhang, Dinggang Shen:
Synergistic Learning of Lung Lobe Segmentation and Hierarchical Multi-Instance Classification for Automated Severity Assessment of COVID-19 in CT Images. CoRR abs/2005.03832 (2020)
2010 – 2019
- 2019
- [j3]Zhenyu Tang, Pew-Thian Yap, Dinggang Shen:
A New Image Similarity Metric for Improving Deformation Consistency in Graph-Based Groupwise Image Registration. IEEE Trans. Biomed. Eng. 66(8): 2192-2199 (2019) - [j2]Zhenyu Tang, Pew-Thian Yap, Dinggang Shen:
A New Multi-Atlas Registration Framework for Multimodal Pathological Images Using Conventional Monomodal Normal Atlases. IEEE Trans. Image Process. 28(5): 2293-2304 (2019) - [c1]Zhenyu Tang, Yuyun Xu, Zhicheng Jiao, Junfeng Lu, Lei Jin, Abudumijiti Aibaidula, Jinsong Wu, Qian Wang, Han Zhang, Dinggang Shen:
Pre-operative Overall Survival Time Prediction for Glioblastoma Patients Using Deep Learning on Both Imaging Phenotype and Genotype. MICCAI (1) 2019: 415-422 - 2018
- [j1]Zhenyu Tang, Sahar Ahmad, Pew-Thian Yap, Dinggang Shen:
Multi-Atlas Segmentation of MR Tumor Brain Images Using Low-Rank Based Image Recovery. IEEE Trans. Medical Imaging 37(10): 2224-2235 (2018)
Coauthor Index
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