• laixy@hust.edu.cn
  • 027-87543130
  • TAN Shan

Dr. Tan is a professor with the School of Artificial Intelligence and Automation, HUST, and is also a member of the Key Laboratory of Image Processing and Intelligent Control, Ministry of Education, China.

Academic Areas: Image processing and analysis, Pattern Recognition, Machine learning,

Research Interests: Biomedical Imaging, Inverse problem, Sparse representation, Deep learning

Academic Degrees

Ph. D. in Pattern Recognition and Intelligent Systems, 09/2002-03/2007, School of Electronic Engineering, Xidian University, Xi’an, Shannxi Province, China
M. Sc. in Electrical Engineering, 09/1999-06/2002, School of Electrical Engineering, Wuhan University, Wuhan, Hubei Province, China

Professional Experience

06/2011- present, Professor, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, Hubei Province, China
06/2010-09/2011, Postdoctoral Fellow, Department of Radiation Oncology, School of Medicine, University of Maryland, Baltimore, MD, USA
06/2007-06/2010, Postdoctoral Fellow, Department of Computer Science, University of Houston, Houston, TX, USA

Selected Publications

[1].F. Xu and S. Tan*, "Deep learning with multiple scale attention and direction regularization for asset price prediction," Expert Systems with Applications, vol. 186, p. 115796, 2021.

[2].H. Liu, X. Liu, J. Lu, and S. Tan*, "Self-Supervised Image Prior Learning with GMM from a Single Noisy Image," in IEEE/CVF International Conference on Computer Vision (ICCV), 2021. (Full Oral Presentation, 3.4% acceptance rate)

[3].L. Li, W. Lu, Y. Tan, and S. Tan*, "Variational PET/CT Tumor Co-segmentation Integrated with PET Restoration," IEEE Transactions on Radiation and Plasma Medical Sciences, vol. 4, pp. 37-49, 2020.

[4].J. Liu, X. Huang, L. Chen, and S. Tan*, "Deep learning–enhanced fluorescence microscopy via degeneration decoupling," Optics Express, vol. 28, pp. 14859-14873, 2020/05/11 2020.

[5].X. Zhao, L. Li, W. Lu, and S. Tan*, "Tumor Co-Segmentation in PET/CT using Multi-Modality Fully Convolutional Neural Network," Physics in medicine and biology, vol. 64, p. 015011, 2019. (IOP Publishing Top Cited Paper Award (China))

[6].H. Liu and S. Tan*, "Image Regularizations Based on the Sparsity of Corner Points," IEEE Trans Image Process, vol. 28, pp. 72-87, Jan 2019.

[7].X. Huang, J. Fan, L. Li, H. Liu, R. Wu, Y. Wu, L. Wei, H. Mao, A. Lal, P. Xi, L. Tang, Y. Zhang, Y. Liu, S. Tan*, L. Chen*, "Fast, long-term, super-resolution imaging with Hessian structured illumination microscopy," Nature Biotechnology, vol. 36, p. 451, 2018.

[8].B. Chen, K. Xiang, Z. Gong, J. Wang*, and S. Tan*, "Statistical Iterative CBCT Reconstruction Based on Neural Network," IEEE Trans. Medical Imaging, vol. 37, pp. 1511-1521, Jun 2018.

[9].L. Liu, X. Li, K. Xiang, J. Wang, and S. Tan*, "Low-Dose CBCT Reconstruction Using Hessian Schatten Penalties," IEEE Transactions on Medical Imaging, vol. 36, pp. 2588-2599, 2017.

[10].T. Sun, N. Sun, J. Wang*, and S. Tan*, "Iterative CBCT reconstruction using Hessian penalty," Physics in medicine and biology, vol. 60, pp. 1965-1987, Feb 12, 2015.

Awards and Honors

[1].Honorable Mention of the 2009 Chinese Excellent Dissertation Award (2009)

[2].Modeling Pathologic Response of Locally Advanced Esophageal Cancer to Chemoradiotherapy Using Spatial-Temporal FDG-PET features, Clinical Parameters and Demographicsthe 54th Annual Meeting of the AAPM, Best in Physics, 2012.

[3].IOP Publishing Top Cited Paper Award (China) (2021)

Courses Taught

For Undergraduates:
 1 Digital Image Process
 2. An Introduction to Scientific Research

For Graduates:
 1. Pattern recognition and intelligent system


[1].1/2021 –12/2024, " Theory and Algorithms on Singal Recovery in Super-resolution Microscopy Imaging”, National Natural Science Foundation of China (NNSFC), Grant No. 62071197.

[2].1/2017 –12/2021, "CBCT Reconstruction Using Optimized Multiple Regularizations”, National Natural Science Foundation of China (NNSFC), Grant No. 61672253.

[3].1/2014 – 12/2017, "PET Image Blind Segmentation”, National Natural Science Foundation of China (NNSFC), Grant No. 61375018.

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