Comprehensive Review of Open-Source Fundus Image Databases for Diabetic Retinopathy Diagnosis.

ABSTRACT: Databases play a crucial role in training, validating, and comparing AI models for detecting retinal diseases, as well as in clinical research, technology development, and healthcare professional training. Diabetic retinopathy (DR), a common diabetes complication, is a leading cause of vision impairment and blindness worldwide. Early detection and management are essential to prevent irreversible vision loss. Fundus photography, known for being economical and non-contact, is a widely applicable gold standard method that offers a convenient way to diagnose and grade DR. This paper presents a comprehensive review of 22 open-source fundus retinal image databases commonly used in DR research, highlighting their main characteristics and key features. Most of these datasets were released between

SUBMITTER: Conquer V 

PROVIDER: S-EPMC12473202 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature