Dimitrov L I
Institute of Information Processing, Austrian Academy of Sciences, Vienna, Austria.
Hum Brain Mapp. 1998;6(4):189-202. doi: 10.1002/(SICI)1097-0193(1998)6:4<189::AID-HBM1>3.0.CO;2-#.
A method for representing the results of statistical EEG analysis in a visually comprehensive and concentrated way is presented. It consists of a combination of scattered data interpolation, texture mapping, and volume rendering techniques. First, starting with an EEG study of the proband in question, a smoothly interpolated rectangular map of the EEG findings in the (phi, theta)-domain (phi and theta denote spherical coordinates) is calculated. Then, using the data from an accompanying MRI scan, volume-rendered representations of the brain with a pseudo-colored cortical surface, vividly depicting the precalculated EEG-activities, are produced. Custom-developed software was used for interpolating the EEG maps from the scattered data samples, as well as for mapping and rendering them together with the brain volume data. The algorithm which achieves the scattered data interpolation is a genuine development employing Delaunay triangulation and a modification of the well-known rotation-invariant Phong interpolation. The pictures produced by the presented method are currently being utilized in neurophysiology for detecting correlations between EEG-parameters, cortical morphology, and underlying mental activities.
本文提出了一种以视觉上全面且集中的方式呈现脑电图统计分析结果的方法。它由散乱数据插值、纹理映射和体绘制技术相结合而成。首先,从对相关先证者的脑电图研究开始,计算出在(φ,θ)域(φ和θ表示球坐标)中脑电图结果的平滑插值矩形图。然后,利用伴随的磁共振成像扫描数据,生成具有伪彩色皮质表面的大脑体绘制表示,生动地描绘预先计算出的脑电活动。定制开发的软件用于从散乱数据样本中插值脑电图图,以及将它们与脑体积数据一起进行映射和渲染。实现散乱数据插值的算法是一项真正的开发成果,采用了德劳内三角剖分和对著名的旋转不变冯氏插值的改进。所提出方法生成的图片目前正在神经生理学中用于检测脑电参数、皮质形态和潜在心理活动之间的相关性。