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矩阵梯度线圈的线圈单元结构优化。

Optimization of Coil Element Configurations for a Matrix Gradient Coil.

出版信息

IEEE Trans Med Imaging. 2018 Jan;37(1):284-292. doi: 10.1109/TMI.2017.2743463. Epub 2017 Aug 23.

Abstract

Recently, matrix gradient coils (also termed multi-coils or multi-coil arrays) were introduced for imaging and B shimming with 24, 48, and even 84 coil elements. However, in imaging applications, providing one amplifier per coil element is not always feasible due to high cost and technical complexity. In this simulation study, we show that an 84-channel matrix gradient coil (head insert for brain imaging) is able to create a wide variety of field shapes even if the number of amplifiers is reduced. An optimization algorithm was implemented that obtains groups of coil elements, such that a desired target field can be created by driving each group with an amplifier. This limits the number of amplifiers to the number of coil element groups. Simulated annealing is used due to the NP-hard combinatorial nature of the given problem. A spherical harmonic basis set up to the full third order within a sphere of 20-cm diameter in the center of the coil was investigated as target fields. We show that the median normalized least squares error for all target fields is below approximately 5% for 12 or more amplifiers. At the same time, the dissipated power stays within reasonable limits. With a relatively small set of amplifiers, switches can be used to sequentially generate spherical harmonics up to third order. The costs associated with a matrix gradient coil can be lowered, which increases the practical utility of matrix gradient coils.

摘要

最近,矩阵梯度线圈(也称为多线圈或多线圈阵列)已被引入用于成像和 B 匀场,其线圈元件数量可达 24、48,甚至 84 个。然而,在成像应用中,由于成本高和技术复杂,为每个线圈元件提供一个放大器并不总是可行的。在这项模拟研究中,我们表明,即使减少放大器的数量,一个 84 通道矩阵梯度线圈(脑部成像的头插入件)也能够创建各种各样的场形。我们实现了一种优化算法,该算法可以获得线圈元件组,以便通过驱动每个组来创建所需的目标场。这将放大器的数量限制为线圈元件组的数量。由于给定问题具有 NP 难的组合性质,因此使用模拟退火。我们研究了一个在线圈中心直径为 20 厘米的球体内部的全三次球谐函数基,作为目标场。我们表明,对于所有目标场,中位数归一化最小二乘误差对于 12 个或更多放大器都低于约 5%。同时,耗散功率保持在合理范围内。使用相对较小的一组放大器,可以使用开关来顺序生成高达三次的球谐函数。这可以降低矩阵梯度线圈的成本,从而提高矩阵梯度线圈的实际应用价值。

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