An Image Analysis and Classification Protocol for Characterization of Normal and Abnormal Memory Loss in Aging from Structural MRI

In this paper we propose a new CAD (Computer Aided Diagnosis) system to classify patients with Alzheimer disease. Five textural features proposed by Harlick are extracted from the MRI scans which characterize the disease. An enhanced CBA algorithm is used to classify the images as Normal or Abnormal based on the rule set generated during the training phase. The experiments were conducted on OASIS dataset and result show that the proposed system classifies with 98% accuracy, making association rules efficient for the classification task.