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Glaucoma is a leading cause of blindness with permanent damage to optic nerve head. ARGALI is an automated computer-aided diagnosis system designed for glaucoma detection via optic cup-to-disc ratio assessment. It employs several methods to determine the optic cup and disc from retinal images. Optic disc detection and segmentation works have been widely reported with high success rate. However, the...
The optic disc is an important feature in the retina. We propose a method for the detection of the optic disc based on a supervised learning scheme. The method employs pixel and local neighbourhood features extracted from the ROI of a digital retinal fundus photograph. A support vector machine based classification mechanism is used to classify each image point as belonging to the cup and retina. The...
This paper proposes a method to detect the macula in the retinal fundus image automatically. The method makes use of the optic disc height obtained from the ARGALI to define the region of interest. Regions of dark spots are then detected by finding the coordinates with the lowest pixel intensity and determining the average pixel neighbourhood intensities. These regions are ranked to determine the...
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