Comparison of reconstruction algorithm for compressive sensing magnetic resonance imaging

被引：4
|
作者：
Kong, Fanqiang [1 ]
机构：
[1] Nanjing Univ Aeronaut & Astronaut, Coll Astronaut, Nanjing 210016, Jiangsu, Peoples R China
来源：
MULTIMEDIA TOOLS AND APPLICATIONS | 2018年 / 77卷 / 17期
基金：
中国国家自然科学基金;
关键词：
compressed sensing; magnetic resonance imaging; iterative shrinkage/threshold algorithm; exponential wavelet transform; DENSITY;
D O I：
10.1007/s11042-017-4985-2
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Compressed sensing can reconstruct the undersampled image. The combination of compressed sensing and magnetic resonance imaging is a potential future fast imaging method in hospitals. This study investigated five state-of-the-art reconstruction approaches: iterative shrinkage/threshold algorithm (ISTA), fast ISTA, subband-adaptive ISTA, exponential wavelet transform ISTA, and exponential wavelet ISTA with random search (EWISTARS). The simulation results compared the five algorithms over hand image and shoulder image. Finally, we can observe the EWISTARS obtains the best result.
引用
收藏
页码：22617 / 22628
页数：12
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