Identification of Diabetic Retinopathy in Fundus Images Using Image Processing Techniques
Diabetic Retinopathy (DR) is a medical condition which occurs to diabetic patients. The damage is caused to the retina of the diabetic patients which may lead to blindness if left unattended. It is a serious sight-threatening condition that can occur to the diabetic patients. Study shows that about 80% of the people who have had diabetes for 20 years or more suffer from diabetic retinopathy and also that about 90% of them can be prevented if proper treatment and monitoring of eyes is given. In this paper, the proposed model is to segment the fundus images by applying image processing techniques on them and classify the exudates based on the severity of the disease. The noise in the image is removed first, the optic disc and blood vessels are detected and removed, and then it becomes easier to detect the exudates as to how severe the retinal condition of a person is. This method is tried and tested on a number of data sets including a variety of retinal fundus images of varying quality. The end result is to come up with an effective model to detect exudates in the retinal images.
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