A comparison of machine learning approaches for the automated classification of dementia

Abstract

Like many diseases, dementia is associated with a changed physical structure of diseased tissue. This study is a preliminary attempt to show that these changes are detectable using image processing, and could facilitate the automated classification of dementia subtypes. The identification of a link between different pathologies and the physical structure of tissue is potentially of great benefit to our understanding of this group of diseases. We have shown the existence of such a link by applying machine learning techniques to features derived using fractal analysis, as well as classical shape parameters.