Optic disc and cup segmentation by automatic thresholding with morphological operation for glaucoma evaluation

Abstract

This research proposes a robust method for disc localization and cup segmentation that incorporates masking to avoid misclassifying areas as well as forming the structure of the cup based on edge detection. Our method has been evaluated using two fundus image datasets, namely: D-I and D-II comprising of 60 and 38 images, respectively. The proposed method of disc localization achieves an average $$F_{\mathrm{score}}$$ of 0.96 and average boundary distance of 7.7 for D-I, and 0.96 and 9.1, respectively, for D-II. The cup segmentation method attains an average $$F_{\mathrm{score}}$$ of 0.88 and average boundary distance of 13.8 for D-I, and 0.85 and 18.0, respectively, for D-II. The estimation errors (mean ± standard deviation) of our method for the value of vertical cup-to-disc diameter ratio against the result of the boundary by the expert of D-I and D-II have similar value, namely $$0.04 \pm 0.04$$ . Overall, the result of our method indicates its robustness for glaucoma evaluation.