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The number of individuals who develop Diabetic Retinopathy (DR) has increased significantly in recent years. Early detection and diagnosis is essential to prevent the vision loss. Ophthalmologist need to analyze mass retinal images to discover the anomalies, for example, spilling veins, retinal swelling(macular edema), greasy stores on the retina (exudates), and changes in the veins. Early detection of DR from retinal images is a challenging task. Medical image examination is the most effective method for diagnosis of DR. Computer Aided Diagnosis (CAD) systems, which can be used in clinical environments assists an ophthalmologist in diagnosing and detecting DR. This paper aims to investigate, the state of art regarding CAD for DR. The review focus on major techniques in image processing and data mining that are employed for developing a CAD system for DR. This survey also comes up with a common analysis of the current CAD system according to the employed modalities for DR diagnosis or detection. Future research works are discussed to develop efficient CAD systems for DR diagnosis or detection. Index Terms— Computer Aided Detection, Classification, Diabetic Retinopathy, Feature Extraction, Image Processing, Preprocessing. |
