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通过匹配头皮表面的样条插值和MRI分割重建来实现脑电图(EEG)和磁共振成像(MRI)数据的共同配准。

Co-registration of EEG and MRI data using matching of spline interpolated and MRI-segmented reconstructions of the scalp surface.

作者信息

Lamm C, Windischberger C, Leodolter U, Moser E, Bauer H

机构信息

Department of Psychology, University of Vienna, Austria.

出版信息

Brain Topogr. 2001 Winter;14(2):93-100. doi: 10.1023/a:1012988728672.

Abstract

Accurate co-registration of MRI and EEG data is indispensable for the correct interpretation of EEG maps or source localizations in relation to brain anatomy derived from MRI. In this study, a method for the co-registration of EEG and MRI data is presented. The method consists of an iterative matching of EEG-electrode based reconstructions of the scalp surface to scalp-segmented MRIs. EEG-electrode based surface reconstruction is achieved via spline interpolation of individually digitized 3D-electrode coordinates. In contrast to other approaches, neither fiducial determination nor any additional provisions (such as bite bars, other co-registration devices or head shape digitization) are required, and co-registration errors associated with inaccurate fiducial determination are avoided. The accuracy of the method was estimated by calculating the root-mean-square (RMS) deviation of spline interpolated and MRI-segmented surface reconstructions in 20 subjects. In addition, the distance between co-registered and genuine electrode coordinates was assessed via a simulation study, in which surface reconstruction was based on virtual electrodes determined on the scalp surface of a high-resolution MRI data set. The mean RMS deviation of surface reconstructions was 2.43 mm, and the maximal distance between any two matched surface points was 5.06 mm. The simulated co-registration revealed a mean deviation of genuine and co-registered electrode coordinates of 0.61 mm. It is concluded that surface matching using spline interpolated reconstructions of scalp surfaces is a precise and highly practicable method to co-register EEG and MRI data.

摘要

准确地将磁共振成像(MRI)和脑电图(EEG)数据进行配准,对于正确解读与源自MRI的脑解剖结构相关的EEG图谱或源定位至关重要。在本研究中,提出了一种EEG和MRI数据配准的方法。该方法包括将基于EEG电极的头皮表面重建与头皮分割的MRI进行迭代匹配。基于EEG电极的表面重建是通过对单独数字化的3D电极坐标进行样条插值来实现的。与其他方法不同,该方法既不需要确定基准点,也不需要任何额外的准备(如咬棒、其他配准设备或头部形状数字化),并且避免了与不准确的基准点确定相关的配准误差。通过计算20名受试者中样条插值和MRI分割的表面重建的均方根(RMS)偏差,估计了该方法的准确性。此外,通过模拟研究评估了配准电极坐标与真实电极坐标之间的距离,其中表面重建基于在高分辨率MRI数据集的头皮表面上确定的虚拟电极。表面重建的平均RMS偏差为2.43毫米,任意两个匹配表面点之间的最大距离为5.06毫米。模拟配准显示真实电极坐标与配准电极坐标的平均偏差为0.61毫米。得出的结论是,使用头皮表面样条插值重建进行表面匹配是一种精确且高度可行的EEG和MRI数据配准方法。

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