利用脑磁图-多重信号分类算法求解真实头模型中磁源定位问题

Localization of current dipoles in a realistic head shape model by a magnetoencephalogram-multiple signal classification algorithm

脑磁图 多重信号分类 (MEG MUSIC)算法与常见的利用时域空域数据定位多偶极子源的全局优化方法相比 ,具有求解速度快、独立确定各偶极子源的位置、求解难度与偶极子数量无关等优点 ,在偶极子数量较多的情况下 ,MEG MUSIC算法的优势显得更为突出 .利用MEG

It has been proved that the magnetoencephalogram-multiple signal classification algorithm has many advantages over the general global optimization methods in localizing current dipoles in a spherically symmetrical conductor head model. Making use of this method, we can tell the total number of current dipoles conveniently and localize those dipoles one by one in a shorter time, simply by calculating generalized eigenvalues of a two- or three-dimensional matrix. In this paper, this method is used to localize the current dipoles in a realistic head shape model. Numerical simulation demonstrates that this algorithm is effective and has great advantages in the localization of multiple dipoles.