Description

The segmentation of Blood vessels in retinal images was helpful in the identification of diseases in the retinal diseases. Identifying and locating blood vessels in fundus images is a critical process since blood vessels were similar in intensity compared to other regions in the images. The extraction of blood vessels from retinal images is an important and challenging task in medical analysis and diagnosis. Retinal images usually have pathological noise and various texture backgrounds, which may cause difficulties in extraction. However, the line type feature of the blood vessels is not changed when the background textures of the image are different. Edge detection process is applied to the input image in order to identify the vessel regions initially. While applying edge detection process the regions other then blood vessels were also obtained from the images. The phase of the images were obtained and based on the obtained phase and the edge regions Lipschitz level set segmentation process is employed inorder to segment the blood vessels from the image. The performance of the process is measured based on performance metrics like Accuracy, Sensitivity, Specificity, Area Under Curve, Dice Coefficient.