Feature Extraction Method of Retinal Vessel Diameter

Digital image processing is one of the most widely used computer vision techniques, especially in biomedical engineering. Modern ophthalmology is directly dependent on this robust technology, digital image processing to find out the biomarkers analyzing the fundus eye images that are responsible for different kinds of life-threatening diseases like hypertensive retinopathy, Transient Ischemic Attack or sharp stroke. The geometric features like vessel tortuosity, branching angles, vessel diameter, and fractal dimension are considered as the biomarkers for the above-mentioned cardiovascular diseases. Retinal vessel diameter widening has found as the early symptom of transient ischemic attack or sharp stroke. In this paper, a completely new and computer-aided automated method to measure the retinal vessel diameter by employing the Euclidean Distance Transform technique was developed. The proposed algorithm measures the Euclidean Distance of the bright pixels exist on the Region of Interest (ROI). Further, the Vascular Disease Image Set (VDIS) and Central Light Reflex Image Set (CLRIS) of Retinal Vessel Image Set for Estimation of Width database were used to evaluate the performance of the proposed algorithm that measures the vessel diameter. The proposed algorithm obtained 98.1% accuracy for the CLRIS and 97.7% accuracy for VDIS. With further evaluation, validation and enhancement of the method, it can be integrated into the clinical computer-aided diagnostic tool.