Duke OCT DME Dataset (Chiu BOE 2014)

110 OCT B-scans from 10 DME subjects with 8 layer boundaries and fluid region annotations by 2 clinicians.

At a glance

Field	Value
Short name	duke_chiu_boe
Full name	Duke OCT DME Dataset (Chiu BOE 2014)
First published	Unknown
Publication date precision	Unknown
Publication date evidence	Unknown
Publication date source field	Unknown
Publication date reviewed	Unknown
Primary category	oct
Resource role	current_dataset
Dataset family	duke_chiu_boe
Contained modalities	oct
Tasks	segmentation
Primary reported quantity	110 images
Classes	8 (ILM, NFL-GCL, IPL-INL, INL-OPL, OPL-ONL, IS-OS, OS-RPE, BM)
Splits	all
Size	0.1 GB
Source-stated terms	Research use (Duke University)
Normalized terms	research-only
Descriptive screening label	Research or challenge restriction recorded; check source
Terms scope	dataset_files
Access friction	anonymous_direct
Route backend	Direct HTTP
Availability	available (checked 2026-07-21)
Acquisition support	loader_implemented_not_live_tested
Legacy sample-loader status	Standard loader included

Reported quantities

Role	Count	Unit	Scope	Basis	Evidence
Primary	110	images	Primary quantity reported in the reviewed catalog source	legacy_catalog_field	people.duke.edu/~sf59

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.

Documented relationships

These links record source-supported lineage or overlap, not merely similar modality tags.

• mm_retinal_reason is derived from this record: The version-pinned official dataset card lists this record among the CFP or OCT sources used to construct MM-Retinal-Reason. (evidence)

Access information and download

CLI

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

# Download, only when preflight reports supported behavior
eyehub download duke_chiu_boe --data-dir ./data

Python

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

ds = REGISTRY.get_dataset('duke_chiu_boe')
print(preflight_dataset(ds, './data'))  # no download

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_chiu_boe')
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_chiu_boe,
  title  = { Duke OCT DME Dataset (Chiu BOE 2014) },
  note   = { Chiu et al., 'Kernel regression based segmentation of optical coherence tomography images with diabetic macular edema', Biomedical Optics Express 2014. DOI: 10.1364/BOE.6.001172 },
  year   = { 2014 },
  url    = { http://people.duke.edu/~sf59/Chiu_BOE_2014_dataset.htm },
}

Plain text

Chiu et al., 'Kernel regression based segmentation of optical coherence tomography images with diabetic macular edema', Biomedical Optics Express 2014. DOI: 10.1364/BOE.6.001172

Source-stated terms

• Raw source string: Research use (Duke University)
• 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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