Exponential Wavelet Iterative Shrinkage Thresholding Algorithm for compressed sensing magnetic resonance imaging

被引:102
作者
Zhang, Yudong [1 ,2 ,3 ,4 ,5 ]
Dong, Zhengchao [3 ,4 ,5 ]
Phillips, Preetha [6 ]
Wang, Shuihua [1 ,7 ]
Ji, Genlin [1 ]
Yang, Jiquan [2 ]
机构
[1] Nanjing Normal Univ, Sch Comp Sci & Technol, Nanjing 210023, Jiangsu, Peoples R China
[2] Jiangsu Key Lab 3D Printing Equipment & Mfg, Nanjing 210042, Jiangsu, Peoples R China
[3] Columbia Univ, Translat Imaging Div, New York, NY 10032 USA
[4] Columbia Univ, MRI Unit, New York, NY 10032 USA
[5] New York State Psychiat Inst & Hosp, New York, NY 10032 USA
[6] Shepherd Univ, Sch Nat Sci & Math, Shepherdstown, WV 25443 USA
[7] Nanjing Univ, Sch Elect Sci & Engn, Nanjing 210046, Jiangsu, Peoples R China
关键词
Magnetic resonance imaging; Compressed sensing; Sparsity measure; Sparsifying transform; Iterative Shrinkage/Thresholding Algorithm; SPARSE REPRESENTATION; RECONSTRUCTION METHOD; INVERSE PROBLEMS; MRI; TRANSFORM; DOMAIN; CS;
D O I
10.1016/j.ins.2015.06.017
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
It is beneficial for both hospitals and patients to accelerate MRI scanning. Recently, a new fast MRI technique based on CS was proposed. However, the reconstruction quality and computation time of CS-MRI did not meet the standard of clinical use. Therefore, we proposed a novel algorithm based on three successful components: the sparsity of EWT, the rapidness of FISTA, and the excellent tuning in SISTA. The proposed method was dubbed Exponential Wavelet Iterative Shrinkage/Threshold Algorithm (EWISTA). Experiments over four kinds of MR images (brain, ankle, knee, and ADHD) indicated that the proposed EWISTA showed better reconstruction performance than the state-of-the-art algorithms such as FCSA, ISTA, FISTA, SISTA, and EWT-ISTA. Moreover, EWISTA was faster than ISTA and EVVT-ISTA, but slightly slower than FCSA, FISTA and SISTA. (C) 2015 Elsevier Inc. All rights reserved.
引用
收藏
页码:115 / 132
页数:18
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