Projected Iterative Soft-Thresholding Algorithm for Tight Frames in Compressed Sensing Magnetic Resonance Imaging

• Published in: IEEE transactions on medical imaging Vol. 35; no. 9; pp. 2130 - 2140
• Main Authors: Liu, Yunsong, Zhan, Zhifang, Cai, Jian-Feng, Guo, Di, Chen, Zhong, Qu, Xiaobo
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.09.2016; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithm design and analysis; Algorithms; Analytical models; Brain; Compressed sensing; Data Compression; Dictionaries; Frames; Image Processing, Computer-Assisted; Image reconstruction; Iterative methods; iterative thresholding; Magnetic Resonance Imaging; Mathematical model; Mathematical models; MRI; NMR; Nuclear magnetic resonance; Parameters; Pista; Reconstruction; sparse models; Sparsity; tight frames

Compressed sensing (CS) has exhibited great potential for accelerating magnetic resonance imaging (MRI). In CS-MRI, we want to reconstruct a high-quality image from very few samples in a short time. In this paper, we propose a fast algorithm, called projected iterative soft-thresholding algorithm (p...