A computer aided system for grading of maculopathy

In medical imaging, digital images are analyzed to develop computer aided diagnostic (CAD) systems using state of the art image processing and pattern recognition techniques. Diabetic maculopathy is one of the retinal abnormalities in which diabetic patient suffers from severe vision loss due to affected macula. In this paper, we propose an automated system for the grading of diabetic maculopathy to assist the ophthalmologists in early detection of the disease. We present a three stage system consisting of macula detection, exudate extraction and grading of maculopathy. First stage uses optic disc and blood vessels to extract macula from retinal image. Exudate extraction stage extracts all possible exudates from retina using filter bank and support vector machines. Finally, the system grades the input image in different stages of maculopathy by using the macular coordinates and exudate feature set. The evaluation of proposed system is performed by using publicly available standard retinal image databases.