ADAM — Automatic Detection of AMD Challenge
1200 fundus images for AMD classification, five-class lesion segmentation, fovea/optic disc localisation.
At a glance
| Field | Value |
|---|---|
| Short name | adam_challenge |
| Full name | ADAM — Automatic Detection of AMD Challenge |
| First published | 2018-10-20 |
| Publication date precision | day |
| Publication date evidence | amd.grand-challenge.org/Home |
| Publication date source field | Official ADAM/iChallenge-AMD challenge Updates: Training images and annotations are released |
| Publication date reviewed | 2026-09-11 |
| Primary category | fundus |
| Resource role | current_dataset |
| Dataset family | adam_challenge |
| Contained modalities | fundus |
| Tasks | classification, segmentation |
| Primary reported quantity | 1,200 images |
| Classes | 2 (non-AMD, AMD) |
| Splits | train, val, test |
| Size | 1.5 GB |
| Source-stated terms | Challenge data-use agreement (IEEE DataPort) |
| Normalized terms | research-only |
| Descriptive screening label | Research or challenge restriction recorded; check source |
| Terms scope | challenge_participation |
| Access friction | controlled_or_manual |
| Route backend | Google Drive |
| Availability | available (checked 2026-07-21) |
| Acquisition support | manual_access_blocked |
| Legacy sample-loader status | Standard loader included |
Reported quantities
| Role | Count | Unit | Scope | Basis | Evidence |
|---|---|---|---|---|---|
| Primary | 1,200 | images | Primary quantity reported in the reviewed catalog source | legacy_catalog_field | drive.google.com/file |
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.
Access information and download
- CLI
- Python
# This route requires upstream human action; no transfer starts.
eyehub download adam_challenge --data-dir ./data --dry-run --json
# Follow the official instructions shown by preflight.
from eyedatahub.acquisition import preflight_dataset
from eyedatahub.datasets.registry import REGISTRY
ds = REGISTRY.get_dataset('adam_challenge')
print(preflight_dataset(ds, './data')) # returns manual_access_blocked
Upstream page: drive.google.com/file
Source-term evidence: drive.google.com/file
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('adam_challenge')
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{adam_challenge,
title = { ADAM — Automatic Detection of AMD Challenge },
note = { Fang H. et al., 'ADAM Challenge: Detecting AMD from Fundus Images', IEEE TMI 2022 },
year = { 2022 },
url = { https://drive.google.com/file/d/1Uz5x0aqXb0aecjzNWQ4522oCxaRDZxBt/view },
}
Fang H. et al., 'ADAM Challenge: Detecting AMD from Fundus Images', IEEE TMI 2022.
Source-stated terms
- Raw source string: Challenge data-use agreement (IEEE DataPort)
- Normalized category:
research-only - Apparent scope:
challenge_participation - Descriptive screening label: Research or challenge restriction 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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