Automated method for the identification and analysis of vascular tree structures in retinal vessel network

Abstract

Structural analysis of retinal vessel network has so far served in the diagnosis of retinopathies and systemic diseases. The retinopathies are known to affect the morphologic properties of retinal vessels such as course, shape, caliber, and tortuosity. Whether the arteries and the veins respond to these changes together or in tandem has always been a topic of discussion. However the diseases such as diabetic retinopathy and retinopathy of prematurity have been diagnosed with the morphologic changes specific either to arteries or to veins. Thus a method describing the separation of retinal vessel trees imaged in a two dimensional color fundus image may assist in artery-vein classification and quantitative assessment of morphologic changes particular to arteries or veins. We propose a method based on mathematical morphology and graph search to identify and label the retinal vessel trees, which provides a structural mapping of vessel network in terms of each individual primary vessel, its branches and spatial positions of branching and cross-over points. The method was evaluated on a dataset of 15 fundus images resulting into an accuracy of 92.87 % correctly assigned vessel pixels when compared with the manual labeling of separated vessel trees. Accordingly, the structural mapping method performs well and we are currently investigating its potential in evaluating the characteristic properties specific to arteries or veins. © 2011 SPIE.