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Shousheng Luo



Name: Luo Shousheng

Address: School of mathematics and statistics, Jinming campus, Henan University, Kaifeng, Henan

Email: Luo_ ssheng@163.com


Research Field

• medical image reconstruction algorithm and application

• image processing

• fast splitting algorithm


Working Experience

• from January 2021 to now, associate professor, School of mathematics and statistics, Henan University

• from July 2013 to December 2020, lecturer, School of mathematics and statistics, Henan University


Education

• 2009.09-2013.07 doctor of computational mathematics, Peking University, instructor: Professor Zhou tie

Dissertation: reconstruction algorithms for single photon emission computed tomography

• 2006.09-2009.07 master of Applied Mathematics, Henan University, instructor: Professor Song Jinping

Dissertation: wavelet based multi-scale variation model for image processing and its applications

• 2002.09-2006.07 Henan University, information and computing science, bachelor


Visit experience

• from December 2019 to February 2020, visiting scholar and co tutor of Hong Kong Baptist University: Professor Tai Xuecheng

• from December 2017 to November 2019, Beijing Computing Science Research Center / Postdoctoral Fellow of Mathematics Department of Hong Kong University of science and technology, CO Tutor: Professor Tai Xuecheng / Professor Wang Yang

• from September 2016 to August 2017, a visiting scholar in the Department of mathematics of Georgia Institute of technology and co Tutor: Professor Zhou Haomin

Projects

• youth fund project of National Natural Science Foundation of China, research on reconstruction algorithm of single photon emission computed tomography (SPECT) (No. 1140117), January 2015-december 2017

• Henan science and technology research project, spectral CT image regularization reconstruction method based on adaptive tight frame, (192102310181), January 2019-december 2020

academic achievements


Papers

1.Shousheng Luo, Xue-Cheng Tai, and Yang Wang. Convex shape representation with binary labels for image segmentation: models and fast algorithms. Submitted to Analysis and Applications.

2.Shousheng Luo, Xue-Cheng Tai, Roland Glowinski. Level Set Representation for Convex object(s) with Application in Image Segmentation, submitted to Journal of Mathematical Imaging and Vision.

• Journal Papers

1.Lingfeng Li, Shousheng Luo, Xue-Cheng Tai, Jiang Yang. A level set representation method for N-dimensional convex shape and applicationsCommunications in Mathematical Research 37(2):180-208, 2021.

2.Lingfeng Li, Shousheng Luo, Xue-Cheng Tai, Jiang Yang. A new variational approach based on level-set function for convex hull problem with outliers, Inverse Problems and Imaging, 15(2): 315-338, 2021.

3.Shousheng Luo, Yanchun Zhang, Tie Zhou, Jinping Song and Yanfei Wang, XCT image reconstruction by a modified superiorized iteration and theoretical analysis, Optimization Methods and Software, 35(6): 1080-1097, 2020.

4.Yanfei Wang, Shousheng Luo, L. H. Wang, J. Q. Wang and C. Jin, Synchrotron radiation-basedl1-normregularization on micro-CT imaging in shale structureanalysis, Journal of Inverse and Ill-Posed Problems, vol.25, no.4, pp. 483-497, 2017.

5.Shousheng Luo, Qian Lv, Heshan Chen and Jinping Song, Second-order total variation and primary-dual algorithm for CT image reconstruction, International Journal of Numerical Analysis and Modeling vol. 14, no.1, pp.76-87, 2017 (SCI).

6.Shousheng Luo and Tie Zhou, Superiorization of EM algorithm and its application in single-photon emission computed tomography (SPECT), Inverse Problems and Imaging,vol.8, no.1,pp.223-246, 2014.

7.Shousheng Luo, Jiansheng Yang and Tie Zhou, A numerical algorithm for cosh-Hilbert transform and the SPECT reconstruction with truncated data, Chinese Journal of Computed Physics, vol.30, no. 6, pp. 95-103, 2013.

• Conference Papers

1.Shousheng Luo, Xue-Cheng Tai, Limei Huo, Yang Wang and Roland Glowinski, Convex shape prior for multi-object segmentation using a single level set function, In Proceedings of the IEEE International Conference on Computer Vision, pp. 613-621, 2019.

2.Shousheng Luo, Ruyue Meng, Suhua Wei, Jian-Feng Cai, Xue-Cheng Tai, and Yang Wang. Data-driven method for 3D axis-symmetric object reconstruction from single cone-beam projection data. In Proceedings of the Third International Symposium on Image Computing and Digital Medicine, pp. 288-292. 2019.

3.Shousheng Luo, Keke Kang, Yang Wang, and Xue-Cheng Tai. Low-dose x-ray computedtomography image reconstruction using edge sparsity regularization. In Proceedings of the Third International Symposium on Image Computing and Digital Medicine, pp. 303-307.2019.

4.Lingfeng Li, Shousheng Luo, Xue-Cheng Tai, and Jiang Yang. A variational convex hull algorithm. In International Conference on Scale Space and Variational Methods in Computer Vision, pp. 224-235. Springer, Cham, 2019.

5.Limei Huo, Shousheng Luo, Yiqiu Dong, Xue-Cheng Tai, and Yang Wang. An iteration method for x-ray CT reconstruction from variable-truncation projection data. In International Conference on Scale Space and Variational Methods in Computer Vision, pp. 144-155. Springer, Cham, 2019.

• Participate in the compilation of books

1.Glowinski, Roland, Shousheng Luo, and Xue-Cheng Tai. Fast operator-splitting algorithms for variational imaging models: Some recent developments. In Handbook of Numerical Analysis, vol. 20, pp. 191-232. Elsevier, 2019.


Teaching

Operations Research》《Numerical analysis》《Numerical Methods For Differential Equations


Academic reports

1. Image segmentation with convexity priority, effective algorithms in data science, learning and computational physics, Tsinghua Sanya International Mathematics Forum (tsimf), January 12-16, 2020 (International Conference)

2. XCT image reconstruction by a modified superior iteration and theoretical analysis, the Fifth International Workshop on computational inverse problems and Applications (cipa2019), Longyan, July 25 – 29, 2019 (International Conference)

3. Convex shape priori with level set representation, Efficient Operator Splitting Techniques for Complex System and Large Scale Data Analysis, Tsin


 

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