Open AccessAutomated detection of optic disc in retinal fundus images using gabor filter kernels
Author(s) -
Baha Şen,
Kemal Akyol,
Şafak Bayır,
Hilal Kaya
Publication year - 2015
Publication title -
global journal of computer sciences
Language(s) - English
Resource type - Journals
ISSN - 2301-2587
DOI - 10.18844/gjcs.v5i1.32
Subject(s) - optic disc , fundus (uterus) , artificial intelligence , computer science , retinal , diabetic retinopathy , brightness , computer vision , retina , optic cup (embryology) , image processing , optic disk , optics , ophthalmology , medicine , physics , image (mathematics) , biology , biochemistry , phenotype , gene , eye development , diabetes mellitus , endocrinology
Identifying the position of the optic disc on the retinal fundus image is a technique that is often used in medical diagnosis, treatment and monitoring processes. Determination of the intensity of the bright colors that belongs to the optic disc on a normal retinal image by the help of image processing algorithms is a fairly easy process. However, determining the optic disc on a retinal image including the diabetic retinopathy disease is a more difficult process. The reason for this difficulty is the existence of many regions that have the same light intensity in different parts of the retina. In this study, a new method for supplying the automatic determination of the optic disc in a recursive manner is proposed. By the help of OpenCV library, automatic determination process of the optic disc on the retinal fundus images including the diabetic retinopathy disease, has been implemented. Circular regions with maximum brightness values in the retinal images that were normalized and passed through the denoising process were determined and these regions were analyzed if they are optic disc or not. This process basically consists of two steps: In the first step, the possible optic disc candidate regions were determined recursively and in the second step, by the help of Gabor filter kernels, these regions were analyzed and it’s provided to decide if they are optic disc or not. This study is based on a dataset that has 89 images including diabetic retinopathy disease. Performance of this system is tested on these images and also on the images that the red, green, blue color channels and Contrast Limited Adaptive Histogram Equalization (CLAHE) retinas were obtained. Most accurate determination of the position of the optic disc is obtained with retinas, implemented process CLAHE, including the best success rate of 89.88%. Keywords: Optic disc, diabetic retinopathy, recursively, circular region, gabor filter kernels.