OCHID: OCT Choroidal Image Dataset

A collection of 640 retinal OCT images with expert choroidal region annotations for choroid segmentation.

At a glance

Field	Value
Short name	ochid
Full name	OCHID: OCT Choroidal Image Dataset
Primary category	oct
Contained modalities	oct
Tasks	segmentation
Samples	640
Classes	2 (background, choroid)
Splits	all
Size	Not reported
Source-stated terms	Research only: academic research use by request
Normalized terms	research-only
Descriptive screening label	Research or challenge restriction recorded; check source
Terms scope	dataset_files
Access friction	author_contact
Route backend	Manual (upstream-gated)
Availability	available (checked 2026-07-21)
Acquisition support	manual_access_blocked
Legacy sample-loader status	Metadata and access only

Notes

The official project page asks academic users to request the dataset by email. It does not provide a standard license.

Access preflight and acquisition

CLI

# This route requires upstream human action; no transfer starts.
eyehub download ochid --data-dir ./data --dry-run --json
# Follow the official instructions shown by preflight.

Python

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

ds = REGISTRY.get_dataset('ochid')
print(preflight_dataset(ds, './data'))  # returns manual_access_blocked

Upstream page: imed.nimte.ac.cn/OCHID.html

Source-term evidence: imed.nimte.ac.cn/OCHID.html

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

@misc{ochid,
  title  = { OCHID: OCT Choroidal Image Dataset },
  note   = { Yan Q, Gu Y, Zhao J, et al. Automatic choroid layer segmentation in OCT images via context efficient adaptive network. Appl Intell. 2023;53:5554-5566. doi:10.1007/s10489-022-03723-w },
  year   = { 2023 },
  url    = { https://imed.nimte.ac.cn/OCHID.html },
}

Plain text

Yan Q, Gu Y, Zhao J, et al. Automatic choroid layer segmentation in OCT images via context efficient adaptive network. Appl Intell. 2023;53:5554-5566. doi:10.1007/s10489-022-03723-w

Source-stated terms

• Raw source string: Research only: academic research use by request
• 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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