Duke RPE-Drusen Complex OCT Dataset

OCT data from 384 subjects, including 269 with AMD and 115 normal subjects, with 38,400 B-scans and derived total retina and RPE-drusen complex thickness measurements.

At a glance

Field	Value
Short name	duke_rpedc
Full name	Duke RPE-Drusen Complex OCT Dataset
Primary category	oct
Contained modalities	oct
Tasks	segmentation, classification, measurement
Samples	384
Classes	2 (normal, amd)
Splits	all
Size	20.0 GB
Source-stated terms	Research only: research and educational use; commercialization and redistribution prohibited
Normalized terms	research-only
Descriptive screening label	Research or challenge restriction recorded; check source
Terms scope	dataset_files
Access friction	anonymous_direct
Route backend	Manual (upstream-gated)
Availability	available (checked 2026-07-21)
Acquisition support	guided_instructions_only
Legacy sample-loader status	Standard loader included

Notes

The source describes more than 20 GB of subject data, segmentation boundaries, and thickness maps.

Access preflight and acquisition

CLI

# Read-only preflight
eyehub download duke_rpedc --data-dir ./data --dry-run --json

# Explicit transfer, only when preflight reports supported behavior
eyehub download duke_rpedc --data-dir ./data

Python

from eyedatahub.acquisition import preflight_dataset
from eyedatahub.datasets.registry import REGISTRY

ds = REGISTRY.get_dataset('duke_rpedc')
print(preflight_dataset(ds, './data'))  # no transfer

Upstream page: people.duke.edu/~sf59

Source-term evidence: people.duke.edu/~sf59

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('duke_rpedc')
samples = ds.load(data_dir, split='all')
for s in samples[:5]:
    print(s.sample_id, s.label, s.image_path)

Citation

BibTeX

@misc{duke_rpedc,
  title  = { Duke RPE-Drusen Complex OCT Dataset },
  note   = { Farsiu S, Chiu SJ, O'Connell RV, et al. Quantitative classification of eyes with and without intermediate age-related macular degeneration using optical coherence tomography. Ophthalmology. 2014;121:162-172. doi:10.1016/j.ophtha.2013.07.013 },
  year   = { 2014 },
  url    = { https://people.duke.edu/~sf59/RPEDC_Ophth_2013_dataset.htm },
}

Plain text

Farsiu S, Chiu SJ, O'Connell RV, et al. Quantitative classification of eyes with and without intermediate age-related macular degeneration using optical coherence tomography. Ophthalmology. 2014;121:162-172. doi:10.1016/j.ophtha.2013.07.013

Source-stated terms

• Raw source string: Research only: research and educational use; commercialization and redistribution prohibited
• Normalized category: research-only
• Apparent scope: dataset_files
• 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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