Research Interests:

  • Mathematical Imaging Science and Computer Vision
  • Deep Learning
  • Inverse Problems
  • Sparse Optimization
  • Scientific Computing
  • Deep Learning
  • Applications: Biomedicine, Genetics and Others

Selected Publications (See CV for the complete list)

  1. Junying Meng, Weihong Guo, Jun Liu and Mingrui Yang, Assemble a Learnable MumfordShah Type Model with Multi-Grid Technique for Image Segmentation, accepted, to appear, SIAM Journal on Imaging Sciences, 2024, PDF
  2. Paramjyoti Mohapatraa, Richard Lartey, Weihong Guo, Michael Judkovich, and Xiaojuan Li, “A Geometric Flow Approach for Segmentation of Images with Inhomongeneous Intensity and Missing Boundaries”, Journal of Image and Graphics, Vol. 12, No. 1, pp. 2331, 2024, PDF
  3. Jiasen Zhang, Weihong Guo, A New Regularization for Deep Learning-Based Segmentation of Images with Fine Structures and Low Contrast, MDPI, Sensors, 2023, PDF
  4. Haifeng Li ,Weihong Guo, Jun Liu , Li Cui and Dongxing Xie, Image Segmentation with Adaptive Spatial Priors from Joint Registration, SIAM Journal on Imaging Sciences, Vol.15,No.3, pp.1314-1344, 2022, PDF.
  5. Weihong Guo, Yifei Lou, Jing Qin, Ming Yan, “A Novel Regularization Based on the Error Function for Sparse Recovery”, Journal of Scientific Computing, 87:31, 2021, PDF.
  6. Wei Wan, Weihong Guo, Haiyang Huang, and Jun Liu, “Non-negative and Non-local Sparse Tensor Factorization Based on Hyperspectral Image Super-resolution”, IEEE transaction on geoscience and remote sensing, to appear, 2020, PDF.
  7. *Wei Wan, Weihong Guo, Jun Liu, Haiyang Huang, “Non-local Blind Hyperspectral Image Super Resolution via 4D Sparse Tensor Factorization and Low Rank”, Inverse Problems and Imaging, 2020, 14 (2): 339–361.
  8. Liang-Jian Deng, Gemine Vivone,Weihong Guo, Mauro Dalla Mura, Jocelyn Chanussot, “A Variational Pansharpening Approach Based on Reproducible Kernel Hilbert Space and Heaviside Function”, IEEE transaction on image processing, 28 (9), p4330-4344, 2018. PDF.
  9. *Weihong Guo, Guohui Song and Yue Zhang, “PCM-TV-TFV: A Novel Two-Stage Framework for Image Reconstruction from Fourier Data”, SIAM Journal on Imaging Sciences, 10(4): pp2250-2274, 2017. PDF. 
  10. Julia Dobrosotskaya, Weihong Guo, “A PDE-Free Variational Method for Multi-Phase Image Segmentation Based on Multiscale Sparse Representations”, Journal of Imaging, MDPI, 2017. PDF. 
  11. *Si Wang, Weihong Guo, Ting-Zhu Huang, Garvesh Raskutti, “Image inpainting using reproducing kernel Hilbert space and Heaviside functions”, Journal of Computational and Applied Mathematics, volume 311, issue C, p551-564, 2017. PDF.
  12. Yue Zhang, Soumya Ray, Weihong Guo, “On the Consistency for Feature Selection with LASSO for Nonlinear Targets”, Int. Conf. Machine Learning, 2016. PDF.
  13. Thomas Atta-Fosu, Weihong Guo, Dana Jeter, Claudia Mizutani, Nathan Stopczynski, Rui Sousa-Neves, “3D Clumped Cell Segmentation Using Curvature Based Seeded Watershed”, Journal of Imaging, MDPI, 2016. PDF.
  14. Liangjian Deng,Weihong Guo, Ting-Zhu Huang,“Weighted Single Image Super-Resolution by Approximated Heaviside Functions”, Information Sciences, volume 348 Issue C, p107-123, 2016. PDF.
  15. Liangjian Deng, Weihong Guo, Ting-Zhu Huang,Single image super-resolution via an iterative reproducing kernel Hilbert space method, IEEE Transactions on Circuits and Systems for Video Technology, 2015. PDF.
  16. Weihong Guo, Jing Qin, Wotao Yin, “A new detail-preserving regularization scheme”, SIAM J. Imaging Science, 7(2), p1309-1334,2014. PDF.
  17. Weihong Guo, Jing Qin, “A geometry guided image denoising scheme”, Inverse Problems and Imaging, 7(2): p499-521, 2013. PDF.
  18. Weihong Guo, Ming-Jun Lai, “Box spline wavelet frames for image edge analysis, SIAM J. Imaging Science, 6(3), p1553-1578, 2013. PDF.
  19. Weihong Guo, Wotao Yin, “Edge guided reconstruction for Compressive Imaging”, SIAM J. Imaging Science, 5(3), p809-834, 2012. PDF.
  20. Jun Miao, Weihong Guo, Sreenath Narayan, David L. Wilson, “A simple application of compressed sensing to further accelerate partially parallel imaging”, Magnetic Resonance Imaging, 31(1), p75-85, 2012. PDF.
  21. Feng Huang, Yunmei Chen, Wotao Yin, Wei Lin, Xiaojing Ye, Weihong Guo, Arne Reykowski, “A rapid and robust numerical algorithm for sensitivity encoding with sparsity constraints: Self-feeding sparse SENSE”, Magnetic Resonance in Medicine, Oct; 64(4): p1078-88, 2010. PDF.
  22. Chuan Li, Qi Hao, Weihong Guo, Fei Hu, “A Hybrid Approach for Compressive Neural Activity Detection with Functional MR Images”, Proceedings of IEEE Engineering in Medicine and Biology Society, p4787-4790, 2009. PDF.
  23. Weihong Guo, Feng Huang, “A Local Mutual Information Guided Denoising Technique and Its Application to Self-calibrated Partially Parallel Imaging”, Metaxas et al. (Eds): proceedings of Medical Image Computing and Computer Assisted Intervention, Part II, Lecture notes on Computer Science 5242, p937-947, 2008. PDF.
  24. Weihong Guo, Yunmei Chen, Qingguo Zeng, “A Geometric Flow Based Approach for Diffusion Tensor Image Segmentation” Special issue on Mathematical and Statistical Methods for Diagnoses and Therapies, Journal of Philosophical Transaction A: Mathematical, Physical and Engineering Sciences, 366(1874): p2279-92, 2008. Invited cover paper.
  25. Yunmei Chen, Weihong Guo, Qingguo Zeng, Yijun Liu, “A Nonstandard Smoothing in Reconstruction of Apparent Diffusion Coefficient Profiles from Diffusion Weighted Images”, Journal of Inverse Problems and Imaging (IPI), Volume 2, Number 2, 205-224, 2008.
  26. Weihong Guo, “Medical Image Segmentation and Diffusion Weighted Magnetic Resonance Image Analysis”, PhD Thesis, 2007. PDF.