Accelerating SENSE Using Compressed Sensing

被引:370
作者
Liang, Dong [1 ]
Liu, Bo [1 ,2 ]
Wang, Jiunjie [3 ]
Ying, Leslie [1 ]
机构
[1] Univ Wisconsin, Dept Elect Engn & Comp Sci, Milwaukee, WI 53211 USA
[2] GE Healthcare, MR Engn, Waukesha, WI USA
[3] ChangGung Univ, Dept Med Imaging & Radiol Sci, Tao Yuan, Taiwan
基金
美国国家科学基金会;
关键词
SENSE; compressed sensing; SparseMRI; Sparse-SENSE; CS-SENSE; SIMULTANEOUS SPARSE APPROXIMATION; IMAGE-RECONSTRUCTION; SIGNAL RECONSTRUCTION; MRI; ALGORITHMS;
D O I
10.1002/mrm.22161
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Both parallel MRI and compressed sensing (CS) are emerging techniques to accelerate conventional MRI by reducing the number of acquired data. The combination of parallel MRI and CS for further acceleration is of great interest. In this paper, we propose a novel method to combine sensitivity encoding (SENSE), one of the standard methods for parallel MRI, and compressed sensing for rapid MR imaging (SparseMRI), a recently proposed method for applying CS in MR imaging with Cartesian trajectories. The proposed method, named CS-SENSE, sequentially reconstructs a set of aliased reduced-field-of-view images in each channel using SparseMRI and then reconstructs the final image from the aliased images using Cartesian SENSE. The results from simulations and phantom and in vivo experiments demonstrate that CS-SENSE can achieve a reduction factor higher than those achieved by SparseMRI and SENSE individually and outperform the existing method that combines parallel MRI and CS. Magn Reson Med 62:1574-1584, 2009. (C) 2009 Wiley-Liss, Inc.
引用
收藏
页码:1574 / 1584
页数:11
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