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Abstract
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.
Copyright 2000 Academic Press.