Comprehensive 3D OCT Dataset for AMD and DME
Swept-source OCT volumes for AMD and DME with three-dimensional pigment epithelial detachment and intraretinal-fluid masks.
At a glance
| Field | Value |
|---|---|
| Short name | amd_dme_3d_oct |
| Full name | Comprehensive 3D OCT Dataset for AMD and DME |
| Primary category | oct |
| Contained modalities | oct |
| Tasks | segmentation, classification |
| Samples | 224 |
| Classes | Not reported (Not reported) |
| Splits | all |
| Size | 19.65 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 | anonymous_direct |
| Route backend | Figshare |
| Availability | available (checked 2026-07-21) |
| Acquisition support | standard_platform_supported |
| Legacy sample-loader status | Metadata and access only |
Notes
The release contains 122 AMD and 102 DME volumes. Of these, 104 volumes are labeled (62 AMD and 42 DME) and 120 are unlabeled.
Access preflight and acquisition
- CLI
- Python
# Read-only preflight
eyehub download amd_dme_3d_oct --data-dir ./data --dry-run --json
# Explicit transfer, only when preflight reports supported behavior
eyehub download amd_dme_3d_oct --data-dir ./data
from eyedatahub.acquisition import preflight_dataset
from eyedatahub.datasets.registry import REGISTRY
ds = REGISTRY.get_dataset('amd_dme_3d_oct')
print(preflight_dataset(ds, './data')) # no transfer
Upstream page: https://doi.org/10.6084/m9.figshare.30582035.v1
Source-term evidence: https://doi.org/10.6084/m9.figshare.30582035.v1
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{amd_dme_3d_oct,
title = { Comprehensive 3D OCT Dataset for AMD and DME },
note = { Huang W, Qin L, Xu M, et al. Comprehensive 3D Optical Coherence Tomography Dataset for AMD and DME: Facilitating Deep-Learning-Based 3D Segmentation. Scientific Data. 2026;13:224. doi:10.1038/s41597-025-06497-1 },
year = { 2026 },
url = { https://doi.org/10.6084/m9.figshare.30582035.v1 },
}
Huang W, Qin L, Xu M, et al. Comprehensive 3D Optical Coherence Tomography Dataset for AMD and DME: Facilitating Deep-Learning-Based 3D Segmentation. Scientific Data. 2026;13:224. doi:10.1038/s41597-025-06497-1
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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