We used independent components analysis to analysis the inter-subject variation of the voxel-based morphometry results of 446 subjects of Alzheimer's spectrum. 20 components which reflect the inter subject volume variation were extracted and used as features in SVM. We observed better performance in SVM classification by these features than those using atlas-based method. These findings might be helpful for classification of AD, MCI and NC populations, which provide assistance to the early diagnosis and intervention of Alzheimer’s disease.
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