周少华是中国科学技术大学讲席教授，博导，生物医学工程学院执行院长，医学影像智能与机器人研究中心主任。长期致力于医学影像的研究创新、应用落地及学术服务。

研究创新：在医学影像领域，率先开展了“机器学习+知识模型”的系统性研究，最近明确了“大任务、小数据”的研究范式和挑战，探出了标注高效、通用模型、知识融合的三大解决途径。发表270余篇学术论文和章节，谷歌学术总引用超14000次，H因子为64；撰编学术专著8本。

应用落地：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。

学术服务：行业顶级协会MICCAI司库兼理事、Medical Open Network for AI（MONAI）顾问、顶级期刊Medical Image Analysis 、IEEE Trans. Pattern Analysis and Machine Intelligence（TPAMI）、IEEE Trans. Medical Imaging（TMI）等编委、顶级会议AAAI、CVPR、ICCV、MICCAI和NeurIPS等领域主席、MICCAI2020的程序联席主席、《视觉求索》公众号联席主编。他多次因算法、论文、专利、服务等多次获得认可和奖励，包括MICCAI年轻科学家奖提名文章、RD100 科技奥斯卡奖、西门子年度发明家、马里兰大学EE杰出校友奖、BMEF年度编辑、Fellow of IEEE、AIMBE (美国医学与生物工程院)、NAI（美国国家学术发明院）等。

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