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A novel computer aided diagnosis system for the early diagnosis of Alzheimer's disease (AD) is presented. The system consists of voxel-based normalised mean square error feature extraction, a t-test with feature correlation weighting for feature selection and random forest image classification. The proposed method yields an up to 96% classification accuracy, thus outperforming recent developed methods for early AD diagnosis.
Date of Publication: June 4 2009