Retinal vessel segmentation using system fuzzy and DBSCAN algorithm

Abstract

Retinal vessel segmentation used for the early diagnosis of retinal diseases such as hypertension, diabetes and glaucoma. There exist several methods for segmenting blood vessels from retinal images. The aim of this paper is to analyze the retinal vessel segmentation based on the clustering algorithm DBSCAN relying on a density-based notion of clusters which is designed to discover clusters of arbitrary shape. DBSCAN requires only one input parameter and a value for this parameter is suggested to the user. The performance of algorithm is compared and analyzed using a number of measures which include sensitivity and specificity. The specificity and sensitivity of this method is 5.36 and 3.82 respectively.