在分析功能磁共振成像(FMRI)试验数据时,为了在不同被试之间比较实验结果、增加实验数据的可靠性,需要对所有被试的脑解剖学影像在三维空间空间内归一到一个共同的标准模板影像,使得它们之间的解剖结构差异达到最小.过去被广泛使用的基于体素的自动化归一化方法虽然很精确,但很耗时.本文章发展了可以在高速度下达到高精确度归一的基于体素的3D归一化方法.该方法采用了余弦离散变换(DCT),克服了原来方法需要较长计算时间的缺点,在现有普通微机上2分钟之内完成对128×128×30体素尺寸下的三维脑图像归一化,文章对方法和结果进行了讨论.%In order to do the inter-comparison on active distribution of human brain mapping between individual volunteer subjects for human brain Functional Magnetic Resonance Imaging (fMRI) experiments, one has to do the spatial normalization to optimize the anatomical consistence between individual brain images by warping them to match both of the size and features to a template brain image. The automatic voxel-based spatial normalization methods which were used widely were highly precise but time consuming. In this paper, a 3D voxel-based method using discrete cosine transform (DCT) was developed at high accuracy and less computer time. The DCT method was tested on a normal equipped PC computer with less than 2 minutes in 3D frame for image matrix size of 128×128×30. The results were presented and discussed.
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