Research Focus
Innovation, application, and academic service in medical imaging
Chair Professor at the University of Science and Technology of China, Ph.D. advisor, Executive Dean of the School of Biomedical Engineering, and Director of the Medical Imaging Intelligence and Robotics Research Center. Dedicated to research innovation, application, and academic service in the field of medical imaging.
Research Innovation
Pioneered systematic research in machine learning + knowledge models within medical imaging. Recently addressed the big task, small data paradigm and challenges, identifying three key solutions: efficient annotation, general models, and knowledge integration. Published over 250 academic papers and book chapters, with more than 11,000 citations on Google Scholar and an H-index of 56; authored 8 academic books.
Application Implementation
With 14 years of industry experience, previously served as Senior R&D Director and Chief AI Expert at Siemens. Holds over 140 authorized patents, with algorithms integrated into more than 10 FDA-approved products. These products are deployed in thousands of hospitals worldwide, aiding in the clinical diagnosis and treatment of over 7 million patients.
Academic Service
Treasurer and board member of the MICCAI Society, advisor for the Medical Open Network for AI (MONAI), editorial board member for top journals such as Medical Image Analysis, IEEE Trans. Pattern Analysis and Machine Intelligence (TPAMI), and IEEE Trans. Medical Imaging (TMI). Served as area chair for top conferences including AAAI, CVPR, ICCV, MICCAI, and NeurIPS, co-chair of MICCAI 2020, and co-editor-in-chief of the Vision Quest WeChat public account. Recognized for contributions in algorithms, papers, patents, and service, including MICCAI Young Scientist Award nomination, RD100 Award, Siemens Inventor of the Year, University of Maryland EE Distinguished Alumni Award, BMEF Annual Editor, Fellow of IEEE, AIMBE, and NAI.
Research Projects
1. Intelligent Medical Imaging Equipment, Chinese Academy of Sciences, 2020.01-2022.12, Principal Investigator
2. Design and Research of New Deep Learning Models for Medical Image Analysis & Federated Learning in Medical Imaging, Multiple Companies, 2020.01-2021.12, Principal Investigator
Major Research Awards
1. Fellow of the National Academy of Inventors (NAI), January 2021
2. Fellow of The Institute of Electrical and Electronics Engineers (IEEE), January 2020
3. Fellow of the American Institute for Medical and Biological Engineering (AIMBE), January 2016
4. RD100 Award, 2014
5. Siemens Inventor of the Year, 2014
Academic Papers and Published Works (Partial) in the Last 2 Years
(Accumulated: 5 academic monographs, over 200 academic papers and chapters)
1. S. Kevin Zhou, Daniel Rueckert, and Gabor Fichtinger (Eds.) Handbook of Medical Image Computing and Computer Assisted Intervention, Elsevier, 2019.
2. S. Kevin Zhou, H. Greenspan, C. Davatzikos, J.S. Duncan, B. van Ginneken, A. Madabhushi, J.L. Prince, D. Rueckert, and R.M. Summers, “A review of deep learning in medical imaging: Imaging traits, technology trends, case studies with progress highlights, and future promises,” Proceedings of the IEEE, 2021.
3. Q. Yao, L. Xiao, P. Liu, and S. Kevin Zhou, “Label-free segmentation of COVID-19 lesions in lung CT,” IEEE Trans. on Medical Imaging, 2021.
4. G. Shi, L. Xiao, Y. Chen, and S. Kevin Zhou, “Marginal loss and exclusion loss for partially supervised multi-organ segmentation,” Medical Image Analysis, 2021.
5. B. Zhou, Z. Augenfeld, J. Chapiro, S. Kevin Zhou, C. Liu, and J.S. Duncan, “Anatomy-guided multimodal registration by learning segmentation without ground truth: Application to intraprocedural CBCT/MR liver segmentation and registration,” Medical Image Analysis, 2021.
6. B. Zhou, S. Kevin Zhou, J.S. Duncan, and C. Liu, “Limited view tomographic reconstruction using a cascaded residual dense spatial-channel attention network with projection data fidelity layer,” IEEE Trans. on Medical Imaging, 2021.
7. X. Wei, Z. Yang, X. Zhang, G. Liao, A. Sheng, S. Kevin Zhou, Y. Wu, L. Du, “Deep collocative learning for immunofixation electrophoresis image analysis,” IEEE Trans. on Medical Imaging, 2021.
8. J. Cai, H. Han, J. Cui, J. Chen, L. Liu, and S. Kevin Zhou, “Semi-supervised natural face de-occlusion,” IEEE Trans. on Information Forensics & Security, Vol. 16, pp. 1044-1057, 2020.
9. J. Zhu, Y. Li, Y. Hu, K. Ma, S. Kevin Zhou, and Y. Zheng, “Rubik’s cube+: A self-supervised feature learning framework for 3D medical image analysis,” Medical Image Analysis, Vol. 64, p101746, 2020.
10. H. Li, H. Han, Z. Li, L. Wang, Z. Wu, J. Lu, and S. Kevin Zhou, “High-resolution chest X-ray bone suppression using unpaired CT structural priors,” IEEE Trans. on Medical Imaging, Vol. 39, No. 10, pp. 3053-3063, 2020.
11. H. Liao, W.A. Lin, S. Kevin Zhou, and J. Luo, “ADN: Artifact disentanglement network for unsupervised metal artifact reduction,” IEEE Trans. on Medical Imaging, Vol. 39, No. 3, pp. 634-643, 2020.
Authorized Patents in the Last 2 Years
(Accumulated: Over 140 authorized patents)
1. Grant US10910099, Segmentation, landmark detection and view classification using multi-task learning. 2021-02-02. 5/5
2. Grant US10878219, Method and system for artificial intelligence based medical image segmentation. 2020-12-29. 1/14
3. Grant US10779785, Semantic segmentation for cancer detection in digital breast tomosynthesis. 2020-09-22. 10/10
4. Grant US10748277, Tissue characterization based on machine learning in medical imaging. 2020-08-18. 1/8
5. Grant US10643105, Intelligent multi-scale medical image landmark detection. 2020-05-05. 8/8
6. Grant US10627470, System and method for learning based magnetic resonance fingerprinting. 2020-04-21. 4/10
7. Grant US10607342, Atlas-based contouring of organs at risk for radiation therapy. 2020-03-31. 3/12
8. Grant US10600185, Automatic liver segmentation using adversarial image-to-image network. 2020-03-24. 3/6
9. Grant US10582907, Deep learning based bone removal in computed tomography angiography. 2020-03-10. 5/10
10. Grant US10565707, 3D anisotropic hybrid network: transferring convolutional features from 2D images to 3D anisotropic volumes. 2020-02-18. 3/9
Email: skevinzhou@ustc.edu.cn