A Semi-supervised Puzzle-Based Method for Separating the Venous and Arterial Vascular Networks in Retinal Images

摘要

The focus of this work is to create a methodology to separate the entire vascular network into its independent veins and arteries networks in optical human fundus images. It has been developed following the logical procedure used by humans when they assemble a puzzle. In the development of the methodology we take into consideration physiological properties, topological properties of the tree structure and morphological properties of both networks, that is, they have only bifurcations, crosses and ending points, and also that crosses are produced always between venous and arterial branches. For arterial blood vessels we get a classification capability, based on the pixel counting, of 84.88% while for venous was 82.87%. This indicates that the methodology classified correctly as average 83.80% of the total blood vessels in the images.