周少华，男，教授，博士生导师。美国国家发明院、美国医学与生物工程院  & IEEE Fellow,  中科院学术帅才。

在医学影像、计算机视觉等研究方向上，发表200余篇学术论文和章节，谷歌学术总引用超10000次，H因子为50。撰编学术专著五本，其中《Deep  Learning for Medical Image Analysis》售出超1000份硬拷贝，《Handbook of Medical  Image Computing and Computer Assisted  Intervention》是MICCAI研究领域全面权威的参考书。在工业界有长达14年的经历，曾任西门子高级研发总监及首席AI专家。获授权专利逾140项，算法成功转入10多项FDA批准的产品。产品部署在全球几千家医院，用于逾7百万病人的临床治疗诊断。

电子邮箱：skevinzhou@ustc.edu.cn

承担科研项目情况

1．智能医学成像设备 中科院 2020.01-2022.12 主持；

2．面向医疗影像分析的新型深度学习模型设计研究 & 医学影像联邦学习 多家公司 2020.01-2021.12主持；

重要科研获奖情况

1．Fellow of National Academy of Inventors (NAI) 美国国家发明院, 2021.01

2．Fellow of The Institute of Electrical and Electronics Engineers (IEEE) 电气电子工程师学会，2020.01

3．Fellow of American Institute for Medical and Biological Engineering (AIMBE) 美国医学与生物工程院，2016.01

4．RD100 Award科技奥斯卡，2014

5．Siemens Inventor of the Year西门子年度发明家, 2014

近2年内学术论文和公开出版的著作（部分）(累计撰编学术专著五本、发表200余篇学术论文和章节)

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.

近2年内获授权专利(累计授权专利140余项)

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 9. 

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