Suppr超能文献

一种具有快速多极子加速的准静态边界元方法,用于高分辨率生物电磁模型。

A Quasi-Static Boundary Element Approach With Fast Multipole Acceleration for High-Resolution Bioelectromagnetic Models.

出版信息

IEEE Trans Biomed Eng. 2018 Dec;65(12):2675-2683. doi: 10.1109/TBME.2018.2813261. Epub 2018 Mar 7.

Abstract

OBJECTIVE

We develop a new accurate version of the boundary element fast multipole method for transcranial magnetic stimulation (TMS) related problems. This method is based on the surface-charge formulation and is using the highly efficient fast multipole accelerator along with analytical computations of neighbor surface integrals.

RESULTS

The method accuracy is demonstrated by comparison with the proven commercial finite-element method (FEM) software ANSYS Maxwell 18.2 2017 operating on unstructured grids and with adaptive mesh refinement. Five realistic high-definition head models from the Population Head Repository (IT'IS Foundation, Switzerland) have been acquired and augmented with a commercial TMS coil model (MRi-B91, MagVenture, Denmark). For each head model, simulations with our method and simulations with the FEM software ANSYS Maxwell 18.2 2017 have been performed. These simulations have been compared with each other and an excellent agreement was established in every case.

SIGNIFICANCE

At the same time, our new method runs approximately 500 times faster than the ANSYS FEM, finishes in about 200 s on a standard server, and naturally provides a submillimeter field resolution, which is justified using mesh refinement.

CONCLUSIONS

Our method can be applied to modeling of brain stimulation and recording technologies such as TMS and magnetoencephalography, and has the potential to become a real-time high-resolution simulation tool.

摘要

目的

我们开发了一种新的准确的用于经颅磁刺激(TMS)相关问题的边界元快速多极方法。该方法基于面电荷公式,并结合高效的快速多极加速器以及邻域面积分的解析计算。

结果

通过与经过验证的商用有限元方法(FEM)软件 ANSYS Maxwell 18.2 2017 在非结构网格上运行的比较,并与自适应网格细化进行比较,证明了该方法的准确性。从人口头部存储库(瑞士 IT'IS 基金会)获得了五个现实的高清晰度头部模型,并增加了一个商用 TMS 线圈模型(MRi-B91,MagVenture,丹麦)。针对每个头部模型,使用我们的方法和 ANSYS Maxwell 18.2 2017 的 FEM 软件进行了模拟。将这些模拟进行了相互比较,在每种情况下都建立了极好的一致性。

意义

同时,我们的新方法的运行速度大约比 ANSYS FEM 快 500 倍,在标准服务器上大约 200 秒即可完成,并且自然提供亚毫米级的场分辨率,这可以通过网格细化来证明。

结论

我们的方法可应用于 TMS 和脑磁图等脑刺激和记录技术的建模,并有潜力成为实时高分辨率模拟工具。

相似文献

6
TMS modeling toolbox for realistic simulation.用于逼真模拟的经颅磁刺激建模工具箱。
Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:3113-6. doi: 10.1109/IEMBS.2010.5626096.

引用本文的文献

8
Enabling electric field model of microscopically realistic brain.微观真实大脑的赋能电场模型
Brain Stimul. 2025 Jan-Feb;18(1):77-93. doi: 10.1016/j.brs.2024.12.1192. Epub 2024 Dec 20.

本文引用的文献

2
Where and what TMS activates: Experiments and modeling.TMS 的激活部位和激活区域:实验与建模。
Brain Stimul. 2018 Jan-Feb;11(1):166-174. doi: 10.1016/j.brs.2017.09.011. Epub 2017 Sep 27.
3
Virtual Human Models for Electromagnetic Studies and Their Applications.虚拟人体模型在电磁研究中的应用及其应用
IEEE Rev Biomed Eng. 2017;10:95-121. doi: 10.1109/RBME.2017.2722420. Epub 2017 Jun 30.
6
Inter-subject Variability in Electric Fields of Motor Cortical tDCS.运动皮质 tDCS 电场的个体间变异性。
Brain Stimul. 2015 Sep-Oct;8(5):906-13. doi: 10.1016/j.brs.2015.05.002. Epub 2015 May 8.
7
Determinants of the electric field during transcranial direct current stimulation.经颅直流电刺激时电场的决定因素。
Neuroimage. 2015 Apr 1;109:140-50. doi: 10.1016/j.neuroimage.2015.01.033. Epub 2015 Jan 19.
10
MNE software for processing MEG and EEG data.MEG 和 EEG 数据处理的 MNE 软件。
Neuroimage. 2014 Feb 1;86:446-60. doi: 10.1016/j.neuroimage.2013.10.027. Epub 2013 Oct 24.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验