Automatic Detection and Diagnosis of Diabetic Retinopathy

Abstract
A computer aided detection and diagnostic system has been developed for diabetic retinopathy (DR). The system detects the fovea, blood vessel network, optic disk, as well as bright and dark lesions associated with DR. The diagnosis is based on the number, type and location of abnormalities relative to the fovea. Detection of normal retinal components was done as part of the overall system development and the work has been reported in literature. Lesion detection is accomplished through the process of eliminating the normal retinal components: blood vessels, fovea and optic disk. Remaining objects in the retinal image include the background and abnormalities if present. The image is partitioned in two regions: fovea and non-fovea, which have different backgrounds. Filtering and statistical adaptive thresholding are applied throughout the remaining data. The diagnostics and final system's layer is a knowledge-based system.

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