Optic cup segmentation using adaptive threshold and morphological image processing
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Abstract
Glaucoma is a chronic optic neuropathy. It was predicted that people with bilateral blindness caused by glaucoma will increase each year. Hence, computer-aided diagnosis of glaucoma was proposed to assist ophthalmologist to conduct a fast and accurate glaucoma screening. One of the ocular examination in screening is optic nerve examination called disc damage likelihood scale (DDLS). It is important to find the optic disc and the optic cup to determine the narrowest width of the neuroretinal rim when using DDLS. To find the optic cup, this study proposed a segmentation scheme consisting of pre-process, segmentation, convex hull and morphological opening operation. In pre-process the blood vessel was removed to make the segmentation process of the optic cup easier. The segmentation process was done by using an adaptive thresholding followed by morphological image processing such as convex hull, opening and erosion. This algorithm was applied on Magrabia dataset and attained accuracy, specificity and sensitivity of 99.50%, 99.75% and 75.19% respectively.
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