Diabetic Retinopathy Grade Classification based on Fractal Analysis and Random Forest

Glaucoma which part of Diabetic Retinopathy is the disease which distorted the optical nerve system and resulted loss in vision. Fractal dimension is one of feature extraction that can been used in retinopathy fields due to the fractal dimension able to characterize the retinal vasculature. In this paper, we presented a research based on fractal dimension which not only distinguish the healthy subjects and diabetic retinopathy patients, but also severe level of diabetic retinopathy patients. By using MESSIDOR dataset and Random Forest as Classifier, we obtained the results that fractal dimensions are able to distinguish the healthy subjects and diabetic retinopathy patients, but it did not obtain satisfactory results for classifying the severity of diabetic retinopathy patients (grade level). Thus, future directions which need to be explore is the other features such as univariate, multivariate and other statistical features. It also needs to pay attention to red lesion detection to gain more information about diabetic retinopathy grade level.