Academy of Mathematics and Systems Science, CAS
Colloquia & Seminars

Speaker:	Professor Jianping Zhang, School of Mathematics and Computational Science, Xiangtan University
Inviter:	Associate Professor Chong Chen
Title:	Optimization-inspired deep unfolding correction-distillation network for CS-MRI reconstruction
Language:	Chinese
Time & Venue:	2023.04.26 15:30-16:30 腾讯会议：876-209-886
Abstract:	In this talk, we discuss a unifying deep unfolding multi-sampling-ratio interpretable CS-MRI framework. The combined approach offers more generalizability than the existing deep-learning-based CS-MRI works whereas deep learning gains explainability through a geometric prior module. Inspired by the multigrid algorithm, we first embed the CS-MRI-based optimization algorithm into correction-distillation scheme that consists of three ingredients: pre-relaxation module, correction module and geometric prior distillation module. Furthermore, we employ a condition module to learn adaptively step-length and noise level, which enables the proposed framework to jointly train multi-ratio tasks through a single model. The proposed model not only compensates for the lost contextual information of reconstructed image which is refined from low frequency error in geometric characteristic k-space, but also integrates the theoretical guarantee of model-based methods and the superior reconstruction performances of deep learning-based methods. Therefore, it can give us a novel perspective to design biomedical imaging networks. Numerical experiments show that our framework outperforms state-of-the-art methods in terms of qualitative and quantitative evaluations.