An efficient grading algorithm for non-proliferative diabetic retinopathy using region based detection

The paper proposes an image processing algorithm to grade the severity of Non Proliferative Diabetic Retinopathy. For this disease the most important parameter to classify the stage of the disease is the proximity of abnormalities from the centre of Macula. The proposed algorithm provides an efficient grading technique by segmenting the fundus image into specific regions of interest and avoids redundancy in computation. Instead of detecting abnormalities for the whole fundus image, the proposed method emphasizes on the segmented regions for the abnormalities, thereby reducing the computation time significantly. Furthermore, this approach provides a simple and direct method to measure the severity of the disease. This region based segmentation also has the advantage of a mesh lesser computational load making this process suitable for real time applications. The accuracy of this region based segmentation method is more than 80% when tested in a database.