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Public Datasets - Retinal Fundus Color Photographs

TLDR;

Globally, vision impairment and vision-threatening conditions are a growing concern, affecting an estimated 2.2 billion people. This increasing prevalence places a significant health and economic burden on individuals and societies, a burden expected to worsen with population growth and aging demographics.

Retinal fundus color photographs (RFPs) contribute to timely intervention and effective management by enabling routine screening and monitoring. These non-invasive images provide a direct view of the retina, the light-sensitive tissue at the back of the eye, revealing crucial details about the microvasculature and its connection to the central nervous system. This makes RFPs invaluable for detecting not only ocular diseases but also systemic conditions like diabetes and hypertension.

The analysis of these images through computational tools and artificial intelligence (AI) holds immense promise for enhancing early detection, improving diagnostic accuracy, and facilitating effective management of vision and systemic health.

Public Datasets

Publicly accessible RFP datasets have contributed significantly to advancing research and facilitating clinical translation. Some of these public datasets capture a myriad of heterogeneities such asvariations in image acquisition across centers, different ethnicities and age groups, as well as diverse lesions or pathologies.

RFPs for Computer Vision tasks in Health Retinal fundus color photographs are an excellent starting point for computer vision tasks in health, offering a robust and well-supported entry point into computer vision for health. Their established clinical relevance, abundant data resources, and diverse content signals make them an ideal domain for both educational purposes and research.

Research Opportunities