体素
人工智能
基于体素的形态计量学
分割
平滑的
灰色(单位)
工件(错误)
高斯分布
参数统计
市场细分
计算机科学
模式识别(心理学)
计算机视觉
数学
统计
白质
物理
核医学
磁共振成像
放射科
医学
量子力学
营销
业务
作者
John Ashburner,Karl Friston
出处
期刊:NeuroImage
[Elsevier]
日期:2000-06-01
卷期号:11 (6): 805-821
被引量:8016
标识
DOI:10.1006/nimg.2000.0582
摘要
At its simplest, voxel-based morphometry (VBM) involves a voxel-wise comparison of the local concentration of gray matter between two groups of subjects. The procedure is relatively straightforward and involves spatially normalizing high-resolution images from all the subjects in the study into the same stereotactic space. This is followed by segmenting the gray matter from the spatially normalized images and smoothing the gray-matter segments. Voxel-wise parametric statistical tests which compare the smoothed gray-matter images from the two groups are performed. Corrections for multiple comparisons are made using the theory of Gaussian random fields. This paper describes the steps involved in VBM, with particular emphasis on segmenting gray matter from MR images with nonuniformity artifact. We provide evaluations of the assumptions that underpin the method, including the accuracy of the segmentation and the assumptions made about the statistical distribution of the data.
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