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Glaucoma is the second leading cause of blindness worldwide. The risk of glaucoma can be determined by calculating the cup to disc ratio in retinal fundus images. To accurately detect the optic cup, kinks or bends in small and medium vessels are important indicators of the cup boundary. In this paper, we present a method of detecting such vessels, through the extraction of patches and generation of...
With the advances of computer technology, more and more computer-aided diagnosis (CAD) systems have been developed to provide the ldquosecond opinionrdquo. This paper reports an automatic fundus image classification technique that is designed to screen out the severely degraded fundus images that cannot be processed by traditional CAD systems. The proposed technique classifies fundus images based...
An approach to automatically diagnose nuclear cataract based on the slit-lamp image is proposed in this paper. Model-based approach is investigated to detect robust lens structure. Based on the detected lens structure, the mean intensity, the color information on the posterior subcapsular reflex and visual axis profile are extracted as the grading features. Support vector machine (SVM) regression...
Objective quantification of lens images is essential for cataract assessment and treatment. In this paper, bottom-up and top-down strategies are combined to detect the lens contour from the slit-lamp images. The center of the lens is localized by horizontal and vertical intensity profile clustering and the lens contour is estimated by fitting an ellipse. A modified active shape model (ASM) is further...
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