Extraction of Retinal Blood Vessels from Fundus Images for Diabetic Retinopathy

Abstract

Diabetic retinopathy is the leading cause of the blindness in the working age population. If the disease is detected early and treated promptly, many of the visual; loss can be prevented. This paper describes the developmentof an automatic fundus image processing and analytic system to facilitate diagnosis of the ophthalmologists. The algorithms to detect the optic disc, blood vessels and exudates are investigated. The optic disc is identified by the method ofsobel edge detector and LSR is candidate area. The blood vessels and the exudates are extracted by Kirsch’s method in the different color components of the color fundus image. The processing results of the proposed methods are also presented. More than thirty fundus images have been tested and the results of the system seem promising and useful to clinical work. The segmentation of retinal blood vessels in the retina is critical step in diagnosis of diabetic retinopathy. After execution of the algorithm, the area-based operator is applied to highlight the blood vessels. To validate the algorithm, the results are compared with the ground truth of the high-resolution fundus images dataset. Upon comparison, it is inferred that the propose algorithm segments the blood vessels with more accuracy than the existing algorithms.