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姓名 周少华  性别 男 
联系方式 zhoushaohua AT ict.ac.cn  职称 研究员 
研究方向 医学影像、计算机视觉
个人主页 miracle.ict.ac.cn 
个人介绍
简历:

2018年5月 — 今 :中科院计算所,研究员

2004年8月 — 2018年4月 :西门子研究院美国,首席专家&高级研发总监

 

2000年8月 — 2004年8月:美国马里兰大学,ECE,博士生

1999年1月 — 2000年7月:新加坡国立大学,ECE,硕士生

1989年9月 — 1994年7月:中国科学技术大学,EE,本科生

 

个人主页的链接:miracle.ict.ac.cn

社会任职:
MICCAI (Medical Image Computing and Computer Assisted Intervention) Society协会理事
MONAI (Medical Open Network for AI) 顾问
CUHK深圳兼职教授
MICCAI 2020程序主席
CVPR, MICCAI, NeuRIPS邻域主席
Medical Image Analysis (IF: 11.148)、IEEE Trans. Medical Imaging (IF: 7.816) 编委
获奖及荣誉:
Fellow of IEEE and AIMBE
MICCAI Young Science Award提名
Siemens Inventor of the Year 2014
RD100 Award (Oscar of Inventions) 2014
University of Maryland ECE杰出校友奖 2016
代表论著:
专著:共10本
[1] S. Kevin Zhou, Daniel Rueckert, and Gabor Fichtinger (Eds.), Handbook of Medical Image Computing and Computer Assisted Intervention, Academic Press, 2019. ISBN 9780128161760. MICCAI book series.
[2] S. Kevin Zhou, Hayit Greenspan, and Dinggang Shen (Eds.), Deep learning for medical image analysis, Academic Press, 2017. ISBN 9780128104088. MICCAI book series.
[3] S. Kevin Zhou (Ed.), Medical image recognition, segmentation and parsing: machine learning and multiple object approaches, Academic Press, 2015. ISBN 9780128025819. MICCAI book series.

期刊文章:共50余篇
[1] J. Zhu, Y. Li, Y. Hu, K. Ma, S. Kevin Zhou, and Y. Zheng, “Rubiks cube+: A self-supervised feature learning framework for 3D medical image analysis,” Medical Image Analysis, 2020. (accepted)
[2] 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, 2020. (PMID: 32275586)
[3] 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. (PMID: 31395543)

会议文章:共150余篇
[1] Q. Yao, Z. He, H. Han, and S. Kevin Zhou, “Miss the point: Targeted adversarial attack on multiple landmark detection,”International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Lima, Peru, October 2020.
[2] H. Li, H. Han, and S. Kevin Zhou, “Bounding maps for universal lesion detection,” International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Lima, Peru, October 2020
[3] Z. Huang, Y. Ding, G. Song, L. Wang, R. Geng, H. He, S. Du, X. Liu, Y. Tian, Y. Liang, S. Kevin Zhou, and J. Chen, “BCData: A large-scale dataset and benchmark for cell detection and counting,” International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Lima, Peru, October 2020.
[4] Y. Lyu, W. Lin, H. Liao, J. Lu, and S. Kevin Zhou, “Encoding metal mask projection for metal artifact reduction in computed tomography,”International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Lima, Peru, October 2020.
W. Wang, Q. Song, J. Zhou, R. Feng, T. Chen, W. Ge, D.Z. Chen, S. Kevin [5] Zhou, W. Wang, and J. Wu, “Dual-level selective transfer learning for intrahepatic cholangiocarcinoma segmentation in non-enhanced abdominal CT,”International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Lima, Peru, October 2020.
[6] C. Peng, W. Lin, R. Chellappa, and S. Kevin Zhou, “Towards multi-sequence MR image recovery from undersampled k-space data,”Medical Imaging with Deep Learning (MIDL), Montral, Canada, July 2020.
[7] B. Zhou and S. Kevin Zhou, “DuDoRNet: Learning a dual-domain recurrent network for fast MRI reconstruction with deep T1 prior,”IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, Washington, June 2020.
[8] C. Peng, W. Lin, H. Liao, R. Chellappa, and S. Kevin Zhou, “SAINT: Spatially aware interpolation network for medical slice synthesis,” IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, Washington, June 2020.
[9] Z. Shen, Y. Chen, S. Kevin Zhou, B. Georgescu, X. Liu and T.S. Huang, “Learning a self-inverse network for bidirectional MRI image synthesis,”IEEE 17th International Symposium on Biomedical Imaging (ISBI), Iowa City, IA, USA, 2020, pp. 1765-1769.
[10] Z. Shen, S. Kevin Zhou, Y. Chen, B. Georgescu, X. Liu, and T.S. Huang, “One-to-one mapping for unpaired image-to-image translation,”The IEEE Winter Conference on Applications of Computer Vision, 1170-1179, 2020

授权专利:共140余个
[1] Grant US9495752, Multi-bone segmentation for 3D computed tomography. 2016-11-15. (J&J Supplier Enabled Innovation Award) 
[2] Grant US9020233, Method and system for up-vector detection for ribs in computed tomography volumes. 2015-04-28. (RD100 Award) 
[3] Grant US8989471, Method and system for automatic rib centerline extraction using learning based deformable template matching. 2015-03-24. (RD100 Award) 
[4] Grant US8571285, Automated rib ordering and pairing. 2013-10-29. (RD100 Award) 
[5] Grant US7949173, Method and system for regression-based object detection in medical images. 2011-05- 24. (Thomas Alva Edison Patent Award)
[6] Grant US10643105, Intelligent multi-scale medical image landmark detection. 2020-05-05. 
[7] Grant US10627470, System and method for learning based magnetic resonance fingerprinting. 2020-04-21.
[8] Grant US10607342, Atlas-based contouring of organs at risk for radiation therapy. 2020-03-31. 
[9] Grant US10600185, Automatic liver segmentation using adversarial image-to-image network. 2020-03-24. 
[10] Grant US10582907, Deep learning based bone removal in computed tomography angiography. 2020-03-10. 
[11] Grant US10565707, 3D anisotropic hybrid network: transferring convolutional features from 2D images to 3D anisotropic volumes. 2020-02-18. 
承担科研项目情况:

[1] 中科院项目:智能医学成像设备,项目负责人

[2] 阿里AIR项目:面向医疗影像分析的新型深度学习模型设计研究,项目负责人

所属部门:
智能信息处理重点实验室
其他备注:
博导计算机应用技术
其他备注2:
 
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