Detection of glaucoma based on cup-to-disc ratio using fundus images
by Imran Qureshi; Muhammad Attique Khan; Muhammad Sharif; Tanzila Saba; Jun Ma
International Journal of Intelligent Systems Technologies and Applications (IJISTA), Vol. 19, No. 1, 2020

Abstract: Glaucoma is a permanent damage of optic nerves which cause of partial or complete visual loss. This work presents a glaucoma detection scheme by measuring CDR from fundus photographs. The proposed system consists of image acquisition, feature extraction and glaucoma assessment steps. Image acquisition discusses the transformation of a RGB fundus image into grey form and enhancing the contrast of fundus features. While, boundary of optic disc and cup were segmented in feature extraction step. Finally, a cup-to-disc ratio of an exploited image will compute to assess glaucoma in the image. The proposed system is tested on 398 fundus images from four publicly available datasets, obtaining an average value of sensitivity 90.6%, specificity 97% and accuracy 96.1% in glaucoma diagnosis. The achieved results show the suitability of proposed art for glaucoma detection.

Online publication date: Fri, 14-Feb-2020

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