DRAC 2022: Diabetic Retinopathy Analysis Challenge

174 OCTA images for DR lesion segmentation (IRMA, NPA, NV), image quality assessment, and DR grading (3-class).

At a glance

Field	Value
Short name	drac22
Full name	DRAC 2022: Diabetic Retinopathy Analysis Challenge
Primary category	octa
Contained modalities	octa
Tasks	segmentation, classification, grading
Samples	174
Classes	3 (No DR, Non-proliferative DR, Proliferative DR)
Splits	train, test
Size	0.3 GB
Source-stated terms	CC BY 4.0
Normalized terms	cc-by
Descriptive screening label	Standard label without an explicit NC clause; not a permission finding
Terms scope	dataset_files
Access friction	self_service_authenticated
Route backend	Zenodo
Availability	available (checked 2026-07-21)
Acquisition support	standard_platform_supported
Legacy sample-loader status	Standard loader included

Notes

Available from Grand Challenge after free registration.

Access preflight and acquisition

CLI

# Read-only preflight
eyehub download drac22 --data-dir ./data --dry-run --json

# Explicit transfer, only when preflight reports supported behavior
eyehub download drac22 --data-dir ./data

Python

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

ds = REGISTRY.get_dataset('drac22')
print(preflight_dataset(ds, './data'))  # no transfer

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('drac22')
samples = ds.load(data_dir, split='test')
for s in samples[:5]:
    print(s.sample_id, s.label, s.image_path)

Citation

BibTeX

@misc{drac22,
  title  = { DRAC 2022: Diabetic Retinopathy Analysis Challenge },
  note   = { Qin et al., 'DRAC: Diabetic Retinopathy Analysis Challenge with Ultra-Wide Optical Coherence Tomography Angiography Images', Medical Image Analysis 2024 },
  year   = { 2024 },
  url    = { https://zenodo.org/records/10280359 },
}

Plain text

Qin et al., 'DRAC: Diabetic Retinopathy Analysis Challenge with Ultra-Wide Optical Coherence Tomography Angiography Images', Medical Image Analysis 2024.

Source-stated terms

• Raw source string: CC BY 4.0
• Normalized category: cc-by
• Apparent scope: dataset_files
• Descriptive screening label: Standard label without an explicit NC clause; not a permission finding

⚠️ 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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• rose: ROSE: Retinal OCT-Angiography Vessel Segmentation (229 records, cc-by)
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• ut_fsocta: UTHealth Fundus and Synthetic OCTA Dataset (count not reported records, unknown)