Retinal blood vessel segmentation using geodesic voting methods

Methods to segment retinal blood vessels are presented. Many authors have used minimal cost paths, or similarly geodesics relative to a weight potential P, to find a vessel pathway between two end points. We focus on the use of a set of such geodesic paths to extract retinal blood vessels, using minimal interaction. The approach consists in computing geodesics from a set of end points scattered in the image in such way that there is a high geodesic density on the vessels. This geodesic density is used to approximate the centerlines and walls of the vessels. The methods were applied to segment blood vessels from images of the retina.