Exploratory and confirmatory factor analysis in morphometry

This paper presents a factor analytic approach to morphometry in which strong intercorrelations among a high-dimensional set of shape-related variables are sought. The correlated variables potentially correspond to substructures of anatomy and thus have a natural interpretation. The analysis is based on information about the pointwise size differences between the anatomy depicted in a template image and the anatomy in a subject image, obtained by registering the template to the subject and then calculating the Jacobian determinant of the registration transformation over the image volume. The method is demonstrated in a preliminary study of shape differences between the corpora callosa of schizophrenic patients and normal controls. We show that the regions where these differences occur can be determined by unsupervised analysis, indicating the method's potential for exploratory studies.