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 |
| Publication date | 2022-07-08 |
| Date basis | Initial dataset release |
| Publication date precision | day |
| Publication date evidence | drac22.grand-challenge.org/Timeline |
| Publication date source field | official DRAC22 challenge timeline: training sets for Tasks 2 and 3 released |
| Publication date reviewed | 2026-09-11 |
| Date notes | DRAC22 official timeline records Task 2 and Task 3 training-set release on 2022-07-08, before Task 1 training on 2022-08-02 and testing sets for all tasks on 2022-08-08. Zenodo record 10280359 (metadata publication_date year 2023) is a later archive, not the resource-level initial release. |
| Primary category | octa |
| Resource role | current_dataset |
| Dataset family | drac22 |
| Contained modalities | octa |
| Tasks | segmentation, classification, grading |
| Primary reported quantity | 174 images |
| 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 |
Reported quantities
| Role | Count | Unit | Scope | Basis | Evidence |
|---|---|---|---|---|---|
| Primary | 174 | 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
Available from Grand Challenge after free registration.
Access information and download
- CLI
- Python
# Read-only preflight
eyehub download drac22 --data-dir ./data --dry-run --json
# Download, only when preflight reports supported behavior
eyehub download drac22 --data-dir ./data
from eyedatahub.acquisition import preflight_dataset
from eyedatahub.datasets.registry import REGISTRY
ds = REGISTRY.get_dataset('drac22')
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('drac22')
samples = ds.load(data_dir, split='test')
for s in samples[:5]:
print(s.sample_id, s.label, s.image_path)
Citation
- BibTeX
- Plain text
@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 },
}
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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