Moorfields nAMD Quantitative OCT Biomarker Dataset
Anonymized clinical metadata and automated 3D OCT segmentation volumes for neovascular age-related macular degeneration.
At a glance
| Field | Value |
|---|---|
| Short name | dryad_namd_oct_quant |
| Full name | Moorfields nAMD Quantitative OCT Biomarker Dataset |
| Primary category | tabular |
| Contained modalities | tabular, oct |
| Tasks | regression, prognosis, fairness_analysis |
| Samples | 2,966 |
| Classes | Not reported (Not reported) |
| Splits | all |
| Size | 0.0032 GB |
| Source-stated terms | CC0 1.0 |
| Normalized terms | cc0 |
| Descriptive screening label | Standard label without an explicit NC clause; not a permission finding |
| Terms scope | dataset_files |
| Access friction | anonymous_direct |
| Route backend | Dryad |
| Availability | available (checked 2026-07-21) |
| Acquisition support | standard_platform_supported |
| Legacy sample-loader status | Metadata and access only |
Notes
Contains derived OCT feature volumes and metadata for 2,473 first-treated and 493 second-treated eyes. Raw OCT scans are not part of this Dryad release.
Access preflight and acquisition
- CLI
- Python
# Read-only preflight
eyehub download dryad_namd_oct_quant --data-dir ./data --dry-run --json
# Explicit transfer, only when preflight reports supported behavior
eyehub download dryad_namd_oct_quant --data-dir ./data
from eyedatahub.acquisition import preflight_dataset
from eyedatahub.datasets.registry import REGISTRY
ds = REGISTRY.get_dataset('dryad_namd_oct_quant')
print(preflight_dataset(ds, './data')) # no transfer
Upstream page: https://doi.org/10.5061/dryad.2rbnzs7m4
Source-term evidence: https://doi.org/10.5061/dryad.2rbnzs7m4
Loader status
This catalog record provides metadata and access instructions, but it does not yet include a standard DatasetSample loader. Inspect the source file structure or contribute a loader before using it in a training pipeline.
Citation
- BibTeX
- Plain text
@misc{dryad_namd_oct_quant,
title = { Moorfields nAMD Quantitative OCT Biomarker Dataset },
note = { Moraes G, Fu DJ, Wilson M, et al. Quantitative analysis of optical coherence tomography for neovascular age-related macular degeneration using deep learning. Dryad. 2020. doi:10.5061/dryad.2rbnzs7m4 },
year = { 2020 },
url = { https://doi.org/10.5061/dryad.2rbnzs7m4 },
}
Moraes G, Fu DJ, Wilson M, et al. Quantitative analysis of optical coherence tomography for neovascular age-related macular degeneration using deep learning. Dryad. 2020. doi:10.5061/dryad.2rbnzs7m4
Source-stated terms
- Raw source string: CC0 1.0
- Normalized category:
cc0 - 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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