论文标题

用于MRI快速电磁模拟的混合体积表面积分方程方法

A hybrid volume-surface integral equation method for rapid electromagnetic simulations in MRI

论文作者

Giannakopoulos, Ilias I., Guryev, Georgy D., Serrallés, José E. C., Paška, Jan, Zhang, Bei, Daniel, Luca, White, Jacob K., Collins, Christopher M., Lattanzi, Riccardo

论文摘要

目的:我们开发了基于域分解的杂交体积表面积分方程(VSIE)方法,以执行快速准确的磁共振成像(MRI)模拟,其中包括远程和局部导电元件。方法:我们将MRI设置中存在的导电表面分为两个域,并为每种情况进行优化的电磁(EM)建模。具体而言,用预校正的快速傅立叶变换对源自局部射频(RF)线圈的身体和EM波之间的相互作用进行建模,而与远程导电表面(RF Shield,Scanner Bore)相互作用的相互作用是用新型的基于交叉张量的基于基于刺激的算法的算法。我们将杂种VSIE与其他VSIE方法进行了比较,以实现现实的MRI模拟设置。结果:杂种VSIE是使用1 mM Voxel各向同性分辨率(VIR)模拟的唯一实用方法。对于2 mM VIR,我们的方法可以比传统的VSIE方法更快地求解23倍,并且需要低760倍的内存。结论:与多种现实的MRI场景中的传统方法相比,Hybrid-VSIE在数值EM模拟的收敛时间方面表现出明显的改善。意义:新型混合VSIE方法的效率可以快速模拟复杂而全面的MRI设置。

Objective: We developed a hybrid volume surface integral equation (VSIE) method based on domain decomposition to perform fast and accurate magnetic resonance imaging (MRI) simulations that include both remote and local conductive elements. Methods: We separated the conductive surfaces present in MRI setups into two domains and optimized electromagnetic (EM) modeling for each case. Specifically, interactions between the body and EM waves originating from local radiofrequency (RF) coils were modeled with the precorrected fast Fourier transform, whereas the interactions with remote conductive surfaces (RF shield, scanner bore) were modeled with a novel cross tensor train-based algorithm. We compared the hybrid- VSIE with other VSIE methods for realistic MRI simulation setups. Results: The hybrid-VSIE was the only practical method for simulation using 1 mm voxel isotropic resolution (VIR). For 2 mm VIR, our method could be solved at least 23 times faster and required 760 times lower memory than traditional VSIE methods. Conclusion: The hybrid-VSIE demonstrated a marked improvement in terms of convergence times of the numerical EM simulation compared to traditional approaches in multiple realistic MRI scenarios. Significance: The efficiency of the novel hybrid-VSIE method could enable rapid simulations of complex and comprehensive MRI setups.

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