Table 1 Commonly Used Public Fundus Datasets for AI Applications

Digital Retinal Images for Vessel Extraction (DRIVE)

40

7

https://drive.grand-challenge.org/

Structured Analysis of the Retina (STARE)

397

13

http://cecas.clemson.edu/~ahoover/stare/

Child Hearth Health Study in England (CHASE_DB1)

28

Healthy

https://blogs.kingston.ac.uk/retinal/chasedb1/

High-Resolution Fundus Image Database (HRF)

45

DR, glaucoma

https://www5.cs.fau.de/research/data/fundus-images/

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

http://www.it.lut.fi/project/imageret/diaretdb0/

Standard Diabetic Retinopathy Database Calibration Level 1 (DIARETDB1)

89

DR

http://www.it.lut.fi/project/imageret/diaretdb1/index.html

Automated Retinal Image Analysis (ARIA)

143

AMD, DR

http://www.damianjjfarnell.com/?page_id=276

Age-Related Eye Disease Study 1/2 (AREDS1/2)

> 134,500

AMD, cataract

https://0-www-ncbi-nlm-nih-gov.brum.beds.ac.uk/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

https://www.adcis.net/en/third-party/messidor/

Methods to Evaluate Segmentation and Indexing Techniques in the Field of Retinal Ophthalmology 2 (MESSIDOR2)

1,748

DR

https://www.adcis.net/en/third-party/messidor2/

e-ophtha

463

DR

https://www.adcis.net/en/third-party/e-ophtha/