Computational Acceleration for MR Image Reconstruction in Partially Parallel Imaging
Computational Acceleration for MR Image Reconstruction in Partially Parallel Imaging
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DOI：
10.1109/tmi.2010.2073717
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发表时间：
2011-05
影响因子：
10.6
通讯作者：
X. Ye;Yunmei Chen;F. Huang
中科院分区：
文献类型：
--
作者：
X. Ye;Yunmei Chen;F. Huang
本文提出了一种基于总变分和TVL1的图像重构快速数值算法，并应用于部分并行磁共振成像。我们的算法采用变量分割的方法来减少计算量。算法采用Barzilai-Borwein步长选择方法，收敛速度更快。在临床部分并行成像数据上的实验结果表明，该算法比目前发展的算子分割和Bregman算子分割方法迭代次数少，计算成本低，可以在重构框架中处理一般的传感矩阵，得到相似甚至更好的重构图像质量。
In this paper, we present a fast numerical algorithm for solving total variation and ℓ1 (TVL1) based image reconstruction with application in partially parallel magnetic resonance imaging. Our algorithm uses variable splitting method to reduce computational cost. Moreover, the Barzilai-Borwein step size selection method is adopted in our algorithm for much faster convergence. Experimental results on clinical partially parallel imaging data demonstrate that the proposed algorithm requires much fewer iterations and/or less computational cost than recently developed operator splitting and Bregman operator splitting methods, which can deal with a general sensing matrix in reconstruction framework, to get similar or even better quality of reconstructed images.