Fractal analysis of retinal vasculature in relation with retinal diseases – an machine learning approach

Abstract

Abstract Diabetic retinopathy (DR) is caused by diabetes mellitus. Vision loss occurs as a result of DR. The goal of this study was to use the DIARETDB-1, DIARETDB-0, STARE, MESSIDOR, E-ophtha-EX, and E-ophtha-MA databases to do Fourier fractal analysis and see how it is related to retinal illnesses. Following the extraction and inversion of colour channels, blood vessel augmentation was conducted. For the blood vessel enhanced image, the fractal dimension was determined. For DR patients and normal patients, measures such as standard deviation, mean, and significance were calculated. In the E-ophtha-EX database, significance was realized. In the DIARETDB-1, STARE, and DIARETDB-0 databases, the mean fractal value for normal patients is higher than for DR patients. The STARE database’s forecast of the association between fractal dimensions and various retinal disorders and the E-ophtha-EX database’s accomplishment of significance are the study’s main highlights. This study also improved the robustness of the blood vessel extraction there and increased the accuracy of its diagnosis.