M. A. Amer, M. Rihan, S. El-Agooz, Noha A. El-Hag, W. El-shafai, F. El-Samie, A. Khalaf, Ghada M. El-Banby, M. Abdelhamed
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Anomaly Detection System for Retinal Images Based on Area Classifier
Diabetic Retinopathy (DR) is a disease of the eye for diabetics, and it can lead to a lack of vision if leaved untreated. The proposed approach in this paper is used to help for detecting and classifying the DR. It is applied to detect non-proliferative DR by identifying micro-aneurysms and hemorrhages. Firstly, the pre-processing step is applied. It consists of extracting the green channel, removing the optic disc (OD) and normalizing the background. Then, h-maxima transformation is performed. After that, threshold segmentation is applied to detect the hemorrhages and micro-aneurysms, accurately. Finally, an area classifier is used for the classification process to discriminate dark spot lesions.