Segmentation and Localization of Optic Disc using Feature Match and Medial Axis Detection in Retinal Images

Abstract

Glaucoma is an eye disease that leads to vision loss without any major symptoms. Detecting the disease in time is important because it cannot be cured. Due to raised Intra-Ocular Pressure (IOP), the Optic Nerve Head (ONH) gets damaged and the assessment of ONH is more promising because it consists of Optic Disc (OD) and Optic Cup (OC) in retinal fundus image. OD and OC detection is important preprocessing step to diagnose glaucoma. In this paper, we proposed a segmentation of OD by FeatureMatch (FM) technique and OD is localized using medial axis detection. The correspondence between the OD reference image and any input image is found by FM. This correspondence provides a distribution of patches in the input image that are closest to patches in the reference image. The proposed work is evaluated using DRIONS-DB that consists of 110 images. The OD is correctly localized in more than 60 images. The performance measures such as Root Mean Square Error (RMSE) and Mean of Structural SIMilarity (MSSIM) are calculated. The average computational time for this proposed work is about 14 secs. The average RMSE of the proposed work is about 0.05389.