AIROGS: AI for Robust Glaucoma Screening

~113,893 color fundus images labelled as referable glaucoma (RG), no referable glaucoma (NRG), or ungradable. Large-scale, multi-ethnic, multi-site screening dataset.

At a glance

Field	Value
Short name	airogs
Full name	AIROGS: AI for Robust Glaucoma Screening
First published	2021-12-01
Publication date precision	day
Publication date evidence	airogs.grand-challenge.org/Updates
Publication date source field	official challenge Updates: Training data available
Publication date reviewed	2026-09-11
Primary category	fundus
Resource role	current_dataset
Dataset family	airogs
Contained modalities	fundus
Tasks	classification
Primary reported quantity	113,893 images
Classes	2 (NRG, RG)
Splits	train, test
Size	40.0 GB
Source-stated terms	CC BY-NC-ND 4.0
Normalized terms	cc-by-nc-nd
Descriptive screening label	Explicit noncommercial clause recorded; check source
Terms scope	dataset_files
Access friction	anonymous_direct
Route backend	Direct HTTP
Availability	available (checked 2026-07-21)
Acquisition support	guided_instructions_only
Legacy sample-loader status	Standard loader included

Reported quantities

Role	Count	Unit	Scope	Basis	Evidence
Primary	113,893	images	Primary quantity reported in the reviewed catalog source	legacy_catalog_field	zenodo.org/records

Counts retain their source-reported units. Additional rows can describe components, paired items, or derivative copies and are not automatically added to the primary quantity.

Notes

Training set (~101k images) on Zenodo. Test set distributed through Grand Challenge. Requires free account for Grand Challenge.

Documented relationships

These links record source-supported lineage or overlap, not merely similar modality tags.

• smdg is derived from this record: The official SMDG source table lists this catalog record among the 19 standardized source domains. (evidence)

Access information and download

CLI

# Read-only preflight
eyehub download airogs --data-dir ./data --dry-run --json

# Download, only when preflight reports supported behavior
eyehub download airogs --data-dir ./data

Python

from eyedatahub.acquisition import preflight_dataset
from eyedatahub.datasets.registry import REGISTRY

ds = REGISTRY.get_dataset('airogs')
print(preflight_dataset(ds, './data'))  # no download

Upstream page: zenodo.org/records

Source-term evidence: zenodo.org/records

Loader example

This entry includes a standard DatasetSample loader.

from pathlib import Path
from eyedatahub.datasets.registry import REGISTRY

data_dir = Path('~/.eyedatahub/data').expanduser()
ds = REGISTRY.get_dataset('airogs')
samples = ds.load(data_dir, split='test')
for s in samples[:5]:
    print(s.sample_id, s.label, s.image_path)

Citation

BibTeX

@misc{airogs,
  title  = { AIROGS: AI for Robust Glaucoma Screening },
  note   = { De Vente et al., 'AIROGS: Artificial Intelligence for Robust Glaucoma Screening Challenge', TMI 2023 },
  year   = { 2023 },
  url    = { https://zenodo.org/records/5793241 },
}

Plain text

De Vente et al., 'AIROGS: Artificial Intelligence for Robust Glaucoma Screening Challenge', TMI 2023.

Source-stated terms

• Raw source string: CC BY-NC-ND 4.0
• Normalized category: cc-by-nc-nd
• Apparent scope: dataset_files
• Descriptive screening label: Explicit noncommercial clause recorded; check source

⚠️ Source-stated terms, scope, and normalized labels are curation metadata, not legal advice or a permission finding. Review the current official source before transfer or reuse.

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