AMD-SD: OCT Wet AMD Lesion Segmentation Dataset
3,049 OCT B-scan images (1,140×380 px) from 138 wet AMD patients (156 eyes) with pixel-level annotations for 5 lesion classes: Subretinal Fluid (SRF), Intraretinal Fluid (IRF), Ellipsoid Zone Continuity (EZC), Subretinal Hyperreflective Material (SHRM), and Pigment Epithelial Detachment (PED).
At a glance
| Field | Value |
|---|---|
| Short name | amd_sd |
| Full name | AMD-SD: OCT Wet AMD Lesion Segmentation Dataset |
| Primary category | oct |
| Contained modalities | oct |
| Tasks | segmentation |
| Samples | 3,049 |
| Classes | 5 (SRF, IRF, EZC, SHRM, PED) |
| Splits | train, val |
| Size | 2.0 GB |
| Source-stated terms | CC BY-NC-ND 4.0 |
| Normalized terms | cc-by-nc-nd |
| Descriptive screening label | Explicit noncommercial clause recorded; check source |
| Terms scope | dataset_files |
| Access friction | self_service_authenticated |
| Route backend | Kaggle |
| Availability | available (checked 2026-07-21) |
| Acquisition support | standard_platform_supported |
| Legacy sample-loader status | Standard loader included |
Notes
Official split: training.txt / validation.txt at dataset root. Images in AMD-SD/images/<patient_id>/<scan>.png. Primary source: Figshare collection 7157554; mirror on Kaggle: gaoweihao/amd-sd.
Access preflight and acquisition
- CLI
- Python
# Read-only preflight
eyehub download amd_sd --data-dir ./data --dry-run --json
# Explicit transfer, only when preflight reports supported behavior
eyehub download amd_sd --data-dir ./data
from eyedatahub.acquisition import preflight_dataset
from eyedatahub.datasets.registry import REGISTRY
ds = REGISTRY.get_dataset('amd_sd')
print(preflight_dataset(ds, './data')) # no transfer
Upstream page: kaggle.com/datasets
Source-term evidence: kaggle.com/datasets
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('amd_sd')
samples = ds.load(data_dir, split='train')
for s in samples[:5]:
print(s.sample_id, s.label, s.image_path)
Citation
- BibTeX
- Plain text
@misc{amd_sd,
title = { AMD-SD: OCT Wet AMD Lesion Segmentation Dataset },
note = { Hu Y et al., 'AMD-SD: An Optical Coherence Tomography Image Dataset for wet AMD Lesions Segmentation', Scientific Data 11, 1014 (2024). doi:10.1038/s41597-024-03844-6 },
year = { 2024 },
url = { https://www.kaggle.com/datasets/gaoweihao/amd-sd },
}
Hu Y et al., 'AMD-SD: An Optical Coherence Tomography Image Dataset for wet AMD Lesions Segmentation', Scientific Data 11, 1014 (2024). doi:10.1038/s41597-024-03844-6
Source-stated terms
- Raw source string: CC BY-NC-ND 4.0
- Normalized category:
cc-by-nc-nd - Apparent scope:
dataset_files - Descriptive screening label: Explicit noncommercial clause 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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