Abstract
Diabetic maculopathy is a disease that may affect central vision and lead to blindness in severe cases. In this direction, the proposed automated system for grading the severity level of diabetic maculopathy can assist the ophthalmologists in early detection and diagnosis of the disease. Presence of exudates in the macular region is an important indication of maculopathy. The macula is localized based on its distance and position with respect to the optic disc. The macular region is then divided into three concentric geometric windows. Based on the presence of exudates in a particular window, the severity level of maculopathy is identified. If exudates are present in the innermost region then it is classified as severe case. Presence of exudates in the outermost region is classified as mild case. The moderate case is the one with exudates present in the middle region. The proposed work has been tested on retinal images with different levels of maculopathy from different databases (DIARETDB0, Messidor, DIARETDB1) and images obtained from a local eye hospital. The proposed method achieves a sensitivity of 96.2 % in correctly grading the different stages of maculopathy.
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