The strong association of neurodegenerative diseases, such as Alzheimer's Disease, and abnormality in cerebral microvasculature has led our research into the analysis of space filling by microvessels and capillaries in angiogenesis. MicroCT images can achieve very resolution scans of vasculature.
Using multifractal theory, we have found a way of characterising the space filling properties as a feature space reduction by presenting the multifractal spectrum across the image irregularity. Due to lack of a benchmark 3D database, the techniques were tested on automatically segmented retinal vessel images. It was found that it is possible to distinguish between healthy and unhealthy patients using only the multifractal properties, and preliminary investigation further shows that microvasculature models of a rodent brain exhibits multifractality. This leads to a potential solution to automated classification of healthy and diseased brains.
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