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Optic Disc (OD) segmentation from retinal fundus images is important for many applications such as detecting other optic structures and early detection of glaucoma. One of the major problems in segmenting OD is the presence of Para-papillary Atrophy (PPA) which in many cases looks similar to the OD. Researchers have used many different features to distinguish between PPA and OD, however each of these...
Localization of the macula centre is an important step in retinal image analysis, in particular for macular disease. We propose the use of a superpixel-based approach for macular localization. Features are extracted from the superpixels, including a proposed feature which aims to describe the extent of the local region due to the superpixel influence. These features are used to calculate probability...
The optic nerve head (optic disc) plays an important role in the diagnosis of retinal diseases. Automatic localization and segmentation of the optic disc is critical towards a good computer-aided diagnosis (CAD) system. In this paper, we propose a method that combines edge detection, the Circular Hough Transform and a statistical deformable model to detect the optic disc from retinal fundus images...
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...
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