{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,22]],"date-time":"2026-10-22T02:54:39Z","timestamp":1792637679583,"version":"4.5.0"},"reference-count":56,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T00:00:00Z","timestamp":1757548800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>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 2000 and 2022. These databases are analyzed through an in-depth examination of their images, enabling objective comparison using color space distances and Principal Component Analysis (PCA) based on 16 key statistical features. Finally, this review aims to support informed decision-making for researchers and practitioners involved in DR diagnosis and management, ultimately improving patient outcomes.<\/jats:p>","DOI":"10.3390\/s25185658","type":"journal-article","created":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T08:55:02Z","timestamp":1757580902000},"page":"5658","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Comprehensive Review of Open-Source Fundus Image Databases for Diabetic Retinopathy Diagnosis"],"prefix":"10.3390","volume":"25","author":[{"given":"Val\u00e9rian","family":"Conquer","sequence":"first","affiliation":[{"name":"IMT Mines Ales, 30100 Al\u00e8s, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thomas","family":"Lambolais","sequence":"additional","affiliation":[{"name":"EuroMov Digital Health in Motion, University Montpellier, IMT Mines Ales, 30100 Al\u00e8s, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6499-5655","authenticated-orcid":false,"given":"Gustavo","family":"Andrade-Miranda","sequence":"additional","affiliation":[{"name":"IMT Mines Ales, 30100 Al\u00e8s, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3458-0552","authenticated-orcid":false,"given":"Baptiste","family":"Magnier","sequence":"additional","affiliation":[{"name":"EuroMov Digital Health in Motion, University Montpellier, IMT Mines Ales, 30100 Al\u00e8s, France"},{"name":"Service de M\u00e9decine Nucl\u00e9aire, Centre Hospitalier Universitaire de N\u00eemes, Universit\u00e9 de Montpellier, 30000 N\u00eemes, France"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,9,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"American Diabetes Association (2010). 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