A Novel Target-Field Method Using LASSO Algorithm for Shim and Gradient Coil Design
A Novel Target-Field Method Using LASSO Algorithm for Shim and Gradient Coil Design
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一种使用 LASSO 算法进行匀场和梯度线圈设计的新型目标场方法
DOI：
10.1109/tasc.2011.2179396
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发表时间：
2012-06-01
影响因子：
1.8
通讯作者：
Wang, Qiuliang
中科院分区：
文献类型：
--
作者：
Hu, Geli;Ni, Zhipeng;Wang, Qiuliang
靶场方法在磁共振成像(MRI)和其他应用中的垫片和梯度线圈的设计中起着非常重要的作用。已有许多基于转移函数的工作被提出。为了限制给定长度的圆柱线圈上的电流分布，用三角级数展开电流密度，并基于标准的L2范数正则化最小二乘(LS-L2)估计未知系数。本文提出了基于L1范数正则化的最小二乘(LS-L1)算法(LS-L1)，也称为最小绝对收缩和选择算子(LASSO)，通过快速迭代收缩阈值算法(FISTA)进行求解。该方法可得到稀疏解和较好的近似解，可用于磁共振成像中圆柱形垫片和梯度线圈的设计。仿真结果表明，提出的LS-L1方法比LS-L2TF方法具有更好的性能。
Target field (TF) method is very important for design of shim and gradient coils which have been used in magnetic resonance imaging (MRI) and other applications. Many works based on TF have been proposed. To restrict the current distribution on cylindrical coils with a given finite length, the current density is expanded by trigonometric series and the unknown coefficients are estimated based on the standard Least Square (LS) with L2 norm regularization (LS-L2). In this paper, we propose to estimate the coefficients using LS with L1 norm regularization (LS-L1), also named Least Absolute Shrinkage and Selection Operator (LASSO), which is solved via Fast Iterative Shrinkage-Thresholding Algorithm (FISTA). The proposed method can obtain sparse solutions and better approximations, which can be used to design cylindrical shim and gradient coils for MRI. Simulation results show that the proposed LS-L1 method performs better than the LS-L2 TF method.