Fundus Image Feature Extraction in Diabetic Retinopathy: A Bibliometric Analysis Approach

Abstract

Diabetic retinopathy is the main cause of vision loss in diabetes patients. Eye fundus image analysis plays a critical role in identifying early signs of diabetic retinopathy. Rapid developments in the fields of digital image processing and artificial intelligence have brought about a revolution in fundus image feature extraction methods, enabling the identification of small details such as changes in blood vessels, the presence of microaneurysms, and exudates, all of which are important indicators of the progression of diabetic retinopathy. In this study, we used an analytical approach from Scopus and used bibliometrics with the Vosviewer application to map and assess research developments in fundus image feature extraction in the context of diabetic retinopathy. The results of the analysis of fundus image research on diabetic retinopathy show an increase in the number of publications every year, with India as the country with the most publications. Feature extraction techniques remain the focus of research, with several feature selection methods that can be used to detect diabetic retinopathy. In addition, the subject area of computer science is experiencing an increase in fundus image research of diabetic retinopathy, indicating the contribution of technology and related methods in the research of this disease.