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Retinal images provide early signs of diabetic retinopathy, glaucoma, andhypertension. These signs can be investigated based on microaneurysms orsmaller vessels. The diagnostic biomarkers are the change of vessel widths andangles especially at junctions, which are investigated using the vesselsegmentation or tracking. Vessel paths may also be interrupted; crossings andbifurcations may be disconnected. This paper addresses a novel contextualmethod based on the geometry of the primary visual cortex (V1) to study thesedifficulties. We have analyzed the specific problems at junctions with aconnectivity kernel obtained as the fundamental solution of the Fokker-Planckequation, which is usually used to represent the geometrical structure ofmulti-orientation cortical connectivity. Using the spectral clustering on alarge local affinity matrix constructed by both the connectivity kernel and thefeature of intensity, the vessels are identified successfully in a hierarchicaltopology each representing an individual perceptual unit.

Analysis of Vessel Connectivities in Retinal Images by Cortically Inspired Spectral Clustering