Skip to main content

GLEAM Multimodal Glaucoma Staging Dataset

SLO, circumpapillary OCT, and visual-field pattern-deviation maps with four-class glaucoma labels.

At a glance

FieldValue
Short namegleam
Full nameGLEAM Multimodal Glaucoma Staging Dataset
First publishedUnknown
Publication date precisionUnknown
Publication date evidenceUnknown
Publication date source fieldUnknown
Publication date reviewedUnknown
Primary categoryoct
Resource rolecurrent_dataset
Dataset familygleam
Contained modalitiesoct
Tasksclassification, staging
Primary reported quantity3,600 images
ClassesNot reported (Not reported)
Splitsall
SizeNot reported
Source-stated termsCC BY-NC-ND 4.0
Normalized termscc-by-nc-nd
Descriptive screening labelExplicit noncommercial clause recorded; check source
Terms scopedataset_files
Access frictionself_service_authenticated
Route backendKaggle
Availabilityavailable (checked 2026-08-02)
Acquisition supportstandard_platform_supported
Legacy sample-loader statusMetadata and access only

Reported quantities

RoleCountUnitScopeBasisEvidence
Primary3,600imagesThree image modalities for each of 1,200 distinct samples in the all_samples directory The 4,320 additional JPG files under split directories repeat samples for model-development partitions and are not additional source images.derived_from_reported_componentskaggle.com/datasets
Additional1,200recordsDistinct tri-modal glaucoma samples Each sample contains one SLO image, one OCT thickness map, and one visual-field pattern-deviation map.official_source_descriptionkaggle.com/datasets
Additional841participantsSource-reported patient cohortofficial_source_descriptionkaggle.com/datasets

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

Source reports 1,200 tri-modal samples from 841 patients. Complete-deposit inspection confirmed three unique images per sample; copies under split directories are not counted again.

Access information and download

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

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

Upstream page: kaggle.com/datasets

Source-term evidence: kaggle.com/datasets

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{gleam,
title = { GLEAM Multimodal Glaucoma Staging Dataset },
note = { Repository dataset record. zhangyiyinge/gleam-dataset },
url = { https://www.kaggle.com/datasets/zhangyiyinge/gleam-dataset },
}

Source-stated terms

  • Raw source string: CC BY-NC-ND 4.0
  • Normalized category: cc-by-nc-nd
  • Apparent scope: dataset_files
  • Descriptive screening label: Explicit noncommercial clause 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.

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)