Abstract
It has been hypothesized that by examining the changes of intensity in medical images, we can extract some property that characterizes the pathology of disease process. This paper presents the conceptual framework of the regularity dimension of images which can be utilized in computational neuroscience to obtain objective information to support clinical decision making. As an example model, the proposed approach is applied for studying pattern similarity of white matter hyperintensities of the brain on magnetic resonance imaging.