An improved ant colony system for retinal blood vessel segmentation

The diabetic retinopathy disease spreads diabetes on the retina vessels thus they lose blood supply that causes blindness in short time, so early detection of diabetes prevents blindness in more than 50% of cases. The early detection can be achieved by automatic segmentation of retinal blood vessels in retinal images which is two-class classification problem. This paper proposes two improvements in previous approach uses ant colony system for automatic segmentation of retinal blood vessels. The first improvement is done by adding new discriminant feature to the features pool used in classification. The second improvement is done by applying new heuristic function based on probability theory in the ant colony system instead of the old that based on Euclidean distance used before. The results of improvements are promising when applying the improved approach on STARE database of retinal images.