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

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), c...

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Bibliographic Details
Published in:Medical image analysis 2006-12, Vol.10 (6), p.841-849
Main Authors: Caan, M.W.A., Vermeer, K.A., van Vliet, L.J., Majoie, C.B.L.M., Peters, B.D., den Heeten, G.J., Vos, F.M.
Format: Article
Language:English
Subjects:
Adolescent
Adult
Computer Simulation
Corpus Callosum - pathology
Diffusion Magnetic Resonance Imaging
Diffusion tensor imaging
Discriminant Analysis
Humans
Image Processing, Computer-Assisted
Linear discriminant analysis
Male
Principal Component Analysis
Schizophrenia
Schizophrenia - classification
Schizophrenia - diagnosis
Schizophrenia - pathology
Shaving
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Summary: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.
ISSN:1361-8415
1361-8423
DOI:10.1016/j.media.2006.07.006