Automatic identification of diabetic retinopathy stages by using fundus images and visibility graph method

Abstract

Diabetic retinopathy (DR) is one of the problems caused due to the diabetes disease in which the retina is damaged because fluid leaks into the retina from the blood vessels. In extreme cases, the patient may loss vision. Therefore, determination of DR grades has an important role in the treatment process of the disease and preventing vision loss. Different image processing based methods have been proposed to detect the different stages of DR automatically. In this paper, a method based on Radon transform (RT) and visibility graph (VG) was proposed to automatically discriminate grades 0 (normal), 1, 2 and 3 of the DR from fundus images. The proposed method is summarized in two stages: feature extraction and classification. In this study, for the first time, the VG method was employed in the image processing field for feature extraction. Then, these features were given to error-correcting output codes (ECOC) method for classification purposes. The proposed method was easy enjoying an accuracy of 97.92%, a sensitivity of 95.83% and a specificity of 98.61%. The VG based method can be a very easy, cheap, and effective test for the automatic grading of DR stages and it can apply in other image processing application.