title: Exploiting the wavelet structure in compressed sensing MRI.
abstract: Sparsity has been widely utilized in magnetic resonance imaging (MRI) to reduce k-space sampling. According to structured sparsity theories, fewer measurements are required for tree sparse data than the data only with standard sparsity. Intuitively, more accurate image reconstruction can be achieved with the same number of measurements by exploiting the wavelet tree structure in MRI. A novel algorithm is proposed in this article to reconstruct MR images from undersampled k-space data. In contrast to conventional compressed sensing MRI (CS-MRI) that only relies on the sparsity of MR images in wavelet or gradient domain, we exploit the wavelet tree structure to improve CS-MRI. This tree-based CS-MRI problem is decomposed into three simpler subproblems then each of the subproblems can be efficiently solved by an iterative scheme. Simulations and in vivo experiments demonstrate the significant improvement of the proposed method compared to conventional CS-MRI algorithms, and the feasibleness on MR data compared to existing tree-based imaging algorithms.
authors.affiliation: Department of Computer Science and Engineering, University of Texas at Arlington, 500 UTA Boulevard, Arlington, TX, 76019.
authors.forename: Chen
authors.initials: C
authors.lastname: Chen
authors.affiliation: Department of Computer Science and Engineering, University of Texas at Arlington, 500 UTA Boulevard, Arlington, TX, 76019. Electronic address: jzhuang@uta.edu.
authors.forename: Junzhou
authors.initials: J
authors.lastname: Huang
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D001921:Brain / Q000473:pathology; D003198:Computer Simulation; D044962:Data Compression; D006321:Heart / Q000502:physiology; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D015203:Reproducibility of Results; D012782:Shoulder / Q000473:pathology; D012815:Signal Processing, Computer-Assisted; D059629:Signal-To-Noise Ratio; D058067:Wavelet Analysis
keywords: Compressed sensing MRI; Sparse MRI; Structured sparsity; Tree sparsity; Wavelet tree structure