Exploiting weak shape constraints to segment capillary images in microangiopathy

Abstract

Microangiopathy is one form of pathology associated with peripheral neuropathy in diabetes. Capillaries imaged by electron microscopy show a complex textured appearance, which makes segmentation difficult. Considerable variation occurs among boundaries manually positioned by human experts. Detection of region boundaries using Active Contour Models has proved impractical due to the existence of confusing image evidence in the vicinity of these boundaries. Despite the fact that the shapes have no identifying landmarks, the weak constraints imposed by statistical shape modelling combined with genetic search can provide accurate segmentations.