From: Artificial intelligence in chorioretinal pathology through fundoscopy: a comprehensive review
Dataset | Number of Images | Pathologies | Link |
---|---|---|---|
Digital Retinal Images for Vessel Extraction (DRIVE) | 40 | 7 | |
Structured Analysis of the Retina (STARE) | 397 | 13 | |
Child Hearth Health Study in England (CHASE_DB1) | 28 | Healthy | |
High-Resolution Fundus Image Database (HRF) | 45 | DR, glaucoma | |
IOSTAR Retinal Vessel | 30 | N/A | http://www.retinacheck.org/download-iostar-retinal-vessel-segmentation-dataset |
Standard Diabetic Retinopathy Database Calibration Level 0 (DIARETDB0) | 130 | DR | |
Standard Diabetic Retinopathy Database Calibration Level 1 (DIARETDB1) | 89 | DR | |
Automated Retinal Image Analysis (ARIA) | 143 | AMD, DR | |
Age-Related Eye Disease Study 1/2 (AREDS1/2) | > 134,500 | AMD, cataract | https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000001.v3.p1 |
Methods to Evaluate Segmentation and Indexing Techniques in the Field of Retinal Ophthalmology 1 (MESSIDOR1) | 1,200 | DR | |
Methods to Evaluate Segmentation and Indexing Techniques in the Field of Retinal Ophthalmology 2 (MESSIDOR2) | 1,748 | DR | |
e-ophtha | 463 | DR |