Skip to main content

PALM — iChallenge Pathologic Myopia

1200 fundus images for pathologic myopia classification and optic disc / lesion segmentation. 50 % PM / 50 % non-PM.

At a glance

FieldValue
Short namepalm
Full namePALM — iChallenge Pathologic Myopia
Primary categoryfundus
Contained modalitiesfundus
Tasksclassification, segmentation
Samples1,200
Classes2 (non-PM, PM)
Splitstrain, val, test
Size1.5 GB
Source-stated termsChallenge data-use agreement (IEEE DataPort)
Normalized termsresearch-only
Descriptive screening labelResearch or challenge restriction recorded; check source
Terms scopechallenge_participation
Access frictioncontrolled_or_manual
Route backendGoogle Drive
Availabilityavailable (checked 2026-07-21)
Acquisition supportmanual_access_blocked
Legacy sample-loader statusStandard loader included

Access preflight and acquisition

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

Upstream page: drive.google.com/file

Source-term evidence: drive.google.com/file

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

Citation

@misc{palm,
title = { PALM — iChallenge Pathologic Myopia },
note = { Fu H. et al., 'PALM: Pathologic Myopia Challenge', MICCAI 2019 Workshop },
year = { 2019 },
url = { https://drive.google.com/file/d/14XWD6kX0dVRfAyEc7FkZGKZibWEkvnyv/view },
}

Source-stated terms

  • Raw source string: Challenge data-use agreement (IEEE DataPort)
  • Normalized category: research-only
  • Apparent scope: challenge_participation
  • 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.

  • airogs: AIROGS: AI for Robust Glaucoma Screening (113,893 records, cc-by-nc-nd)
  • eyecare_100k: Eyecare-100K: Multimodal Ophthalmology VQA Corpus (102,000 records, unknown)
  • justraigs: JustRAIGS: Just Referral AI Glaucoma Screening Dataset (101,442 records, cc-by-nc-nd)
  • eyepacs: EyePACS — Diabetic Retinopathy Detection (Kaggle 2015) (88,702 records, research-only)
  • multieye: MultiEYE: OCT-Enhanced Fundus Multi-Disease Benchmark (58,036 records, mit)
  • angioreport: AngioReport Fundus Angiography Report Dataset (55,361 records, unknown)
  • ffa_ir: FFA-IR Medical Report Dataset (47,247 records, unknown)
  • bidr: BiDR: Diabetic Retinopathy Diagnosis Dataset (35,126 records, unknown)