A Method for Diagnosing Diabetic Retinopathy Based on Ocular Fundus Imaging

Abstract

Introduction. Diabetic retinopathy is a complication of diabetes mellitus caused by high blood sugar levels damaging the retina. Diabetic retinopathy leads to changes in ocular blood vessels and the appearance of solid exudates and microaneurysms. When diagnosed and treated in the late stages, this disease can cause blindness. The most common diagnostic method for diabetic retinopathy is based on ocular fundus imaging. However, the background interference and low contrast of such images significantly hinders the timely detection of vascular lesions. Therefore, the development of a method for detecting signs of diabetic retinopathy, particularly in its early stages, presents a relevant research task.Aim. Development of a method for diagnosing diabetic retinopathy based on an analysis of ocular fundus images using the decision-tree approach.Materials and methods. Methods based on image segmentation with identifying characteristic features and their binary classification were used. A verified database was used to access the accuracy of the proposed method for detecting diabetic retinopathy.Results. A method for detecting signs of diabetic retinopathy was developed, which includes the segmentation of vessels, exudates and microaneurysms based on digital processing of ocular vascular images using binary classification. The developed method showed a high level of diagnostic accuracy. Thus, the sensitivity, specificity and accuracy of diabetic retinopathy detection comprised 87.14, 88.50 and 87.81 %, respectively.Conclusion. The developed method allows diabetic retinopathy to be diagnosed with sufficiently high accuracy. The method can also be used for supporting decision making when managing patients with diabetic retinopathy.