Paper Title
Automatic Separation of Distinct Retinal Vessels
Abstract
The separation of retinal vessels is an important part of any automatic system for detection of vessel
abnormalities caused by several systemic diseases such as diabetes, hyper tension and other cardiovascular conditions. It also
provides a platform for medical researches on relation of various diseases and vessel characteristics. This paper presents a
graph-based method for automatic separation of retinal vessels. In the proposed method, we first model the vessel structure
as a directed graph where each node represents an intersection point in the vascular tree, and each link corresponds to a
vessel segment between two intersection points. Link directions are based on the vessel growth direction in the retina. In the
next step, the extracted graph is analyzed to find the most acceptable label for each link. The result is compared with the
manually labeled images of the DRIVE dataset and the accuracy value of 74.4% is obtained.
Keywords - Automatic separation, Graph-based, Retinal image, Vessel classification.