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SLID: Slit-Lamp Image Dataset

~2,617 annotated slit-lamp frames covering anterior-segment anatomy + multi-lesion detection (cataract, corneal disease, conjunctivitis).

At a glance

FieldValue
Short nameslid
Full nameSLID: Slit-Lamp Image Dataset
Primary categorymultimodal
Contained modalitiesexternal_eye
Taskssegmentation, classification
Samples2,617
ClassesNot reported (Not reported)
Splitsall
Size1.0 GB
Source-stated termsSee repo (no LICENSE file as of 2026-06; assume research-only)
Normalized termsunknown
Descriptive screening labelUnknown or unclear; do not assume permission
Terms scopeunknown
Access frictionanonymous_direct
Route backendDirect HTTP
Availabilityavailable (checked 2026-07-21)
Acquisition supportloader_implemented_not_live_tested
Legacy sample-loader statusMetadata and access only

Notes

Modality EyeDataHub otherwise lacks (slit-lamp anterior-segment). Annotations CSV is at github.com/xumingyu-hub/SLID/raw/main/Annotations.csv.

Access preflight and acquisition

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

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

Upstream page: github.com/xumingyu-hub

Source-term evidence: github.com/xumingyu-hub

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

@misc{slid,
title = { SLID: Slit-Lamp Image Dataset },
note = { Xu et al., 'SLID: Slit-Lamp Image Dataset', Frontiers Digital Health 2025. doi:10.3389/fdgth.2025.1716501 },
year = { 2025 },
url = { https://github.com/xumingyu-hub/SLID },
}

Source-stated terms

  • Raw source string: See repo (no LICENSE file as of 2026-06; assume research-only)
  • Normalized category: unknown
  • Apparent scope: unknown
  • Descriptive screening label: Unknown or unclear; do not assume permission

⚠️ 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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