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OCTID: OCT Image Database

500 OCT images: NORMAL (206), AMD (50), CSC (128), DR (59), MH (57). High-resolution B-scans for 5-class classification.

At a glance

FieldValue
Short nameoctid
Full nameOCTID: OCT Image Database
First published2018-12-19
Publication date precisionday
Publication date evidenceborealisdata.ca/api
Publication date source fieldBorealis Dataverse API search: published_at / versionState
Publication date reviewed2026-09-11
Primary categoryoct
Resource rolecurrent_dataset
Dataset familyoctid
Contained modalitiesoct
Tasksclassification
Primary reported quantity500 images
Classes5 (NORMAL, AMD, CSC, DR, MH)
Splitsall
Size0.3 GB
Source-stated termsCC0 1.0 Universal
Normalized termscc0
Descriptive screening labelStandard label without an explicit NC clause; not a permission finding
Terms scopedataset_files
Access frictionself_service_authenticated
Route backendManual (upstream-gated)
Availabilityavailable (checked 2026-07-21)
Acquisition supportguided_instructions_only
Legacy sample-loader statusStandard loader included

Reported quantities

RoleCountUnitScopeBasisEvidence
Primary500imagesPrimary quantity reported in the reviewed catalog sourcelegacy_catalog_fieldborealisdata.ca/dataverse

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.

Notes

Freely available from Borealis Data Repository. No account required.

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)
  • multieye is derived from this record: The MultiEYE paper names this record as one of the public fundus or OCT sources assembled for the benchmark. (evidence)
  • x_pcr is derived from this record: Source labels in the version-pinned public X-PCR deposit identify this catalog record as upstream material. (evidence)

Access information and download

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

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

Upstream page: borealisdata.ca/dataverse

Source-term evidence: borealisdata.ca/dataverse

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

Citation

@misc{octid,
title = { OCTID: OCT Image Database },
note = { Gholami et al., 'OCTID: Optical Coherence Tomography Image Database', Elsevier 2020 },
year = { 2020 },
url = { https://borealisdata.ca/dataverse/OCTID },
}

Source-stated terms

  • Raw source string: CC0 1.0 Universal
  • 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.

Similar resources by shared modality

  • syn_oct: SYN-OCT Synthetic Glaucoma OCT Dataset (200,000 images, cc-by)
  • multieye: MultiEYE: OCT-Enhanced Fundus Multi-Disease Benchmark (103,959 images, mit)
  • eyecare_100k: Eyecare-100K: Multimodal Ophthalmology VQA Corpus (102,000 question answer pairs, unknown)
  • kermany_oct: Kermany OCT 2018: Retinal OCT Image Classification (84,484 images, cc-by)
  • lmod_plus: LMOD+ Multimodal Ophthalmology Benchmark (32,633 annotated instances, unknown)
  • harvard_fairvision: Harvard-FairVision (AMD + DR + Glaucoma, paired SLO + OCT) (30,000 participants, cc-by-nc-nd)
  • mario: MARIO: AMD-Progression Longitudinal OCT (MICCAI 2024) (30,000 images, cc-by)
  • mmrdr: MMRDR: Multi-Modal Retinal Diabetic Retinopathy Dataset (24,460 images, cc-by)