Automated MRI-Based Quantification of the Cerebral Atrophy Providing Diagnostic Information on Mild Cognitive Impairment and Alzheimer’s Disease

Abstract

Alzheimer's disease (AD) is a major public health challenge as the median age of the industrialized world's population is increasing gradually. No cure for this disease has yet been found and the development of new treatments has become a topic of major research interest. This paper aims to propose a sequence of fully automated MRI-based image analysis steps to measure the development stage of atrophy in the brain. The results have been validated on a mixed group of 68 subjects by distinguishing between AD patients, MCIs and health controls using linear classifiers and ANNs. The best classifier identified unseen AD patients correctly in 80% of the cases and control subjects in 85%. Recognizing more than 8 out of 10 MCI subjects, the method also yields an early indication of AD. This simple yet powerful analysis can compete with other more time-consuming and semi-automatic methodologies. It could abet an AD diagnosis and provide a tool for measuring the success of therapies