title: Undersampled MR Image Reconstruction with Data-Driven Tight Frame.
abstract: Undersampled magnetic resonance image reconstruction employing sparsity regularization has fascinated many researchers in recent years under the support of compressed sensing theory. Nevertheless, most existing sparsity-regularized reconstruction methods either lack adaptability to capture the structure information or suffer from high computational load. With the aim of further improving image reconstruction accuracy without introducing too much computation, this paper proposes a data-driven tight frame magnetic image reconstruction (DDTF-MRI) method. By taking advantage of the efficiency and effectiveness of data-driven tight frame, DDTF-MRI trains an adaptive tight frame to sparsify the to-be-reconstructed MR image. Furthermore, a two-level Bregman iteration algorithm has been developed to solve the proposed model. The proposed method has been compared to two state-of-the-art methods on four datasets and encouraging performances have been achieved by DDTF-MRI.
authors.affiliation: Paul C. Lauterbur Research Centre for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.
authors.forename: Jianbo
authors.initials: J
authors.lastname: Liu
authors.affiliation: Paul C. Lauterbur Research Centre for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China ; School of Information Technologies, The University of Sydney, Sydney, NSW 2006, Australia.
authors.forename: Shanshan
authors.initials: S
authors.lastname: Wang
authors.affiliation: Paul C. Lauterbur Research Centre for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.
authors.forename: Xi
authors.initials: X
authors.lastname: Peng
authors.affiliation: Paul C. Lauterbur Research Centre for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.
authors.forename: Dong
authors.initials: D
authors.lastname: Liang
mesh_terms: D000465:Algorithms; D001921:Brain / Q000473:pathology; D003198:Computer Simulation; D044962:Data Compression; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D016018:Least-Squares Analysis; D008279:Magnetic Resonance Imaging; D015233:Models, Statistical; D015203:Reproducibility of Results; D012984:Software