Shaving diffusion tensor images in discriminant analysis: a study into schizophrenia

M. W. A. Caan, K. A. Vermeer, L. J. van Vliet, C. B. L. M. Majoie, B. D. Peters, G. J. den Heeten, F. M. Vos

Research output: Contribution to journalArticleAcademicpeer-review

49 Citations (Scopus)

Abstract

A technique called 'shaving' is introduced to automatically extract the combination of relevant image regions in a comparative study. No hypothesis is needed, as in conventional pre-defined or expert selected region of interest (ROI)-analysis. In contrast to traditional voxel based analysis (VBA), correlations within the data can be modeled using principal component analysis (PCA) and linear discriminant analysis (LDA). A study into schizophrenia using diffusion tensor imaging (DTI) serves as an application. Conventional VBA found a decreased fractional anisotropy (FA) in a part of the genu of the corpus callosum and an increased FA in larger parts of white matter. The proposed method reproduced the decrease in FA in the corpus callosum and found an increase in the posterior limb of the internal capsule and uncinate fasciculus. A correlation between the decrease in the corpus callosum and the increase in the uncinate fasciculus was demonstrated
Original languageEnglish
Pages (from-to)841-849
JournalMedical Image Analysis
Volume10
Issue number6
DOIs
Publication statusPublished - 2006

Cite this