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UMN Parhi Lab AMD OCT Fluid Segmentation Dataset

600 Spectralis OCT B-scans from 24 exudative AMD subjects. Three fluid region classes: IRF, SRF, PED. Dual expert annotation.

At a glance

FieldValue
Short nameumn_parhi_oct
Full nameUMN Parhi Lab AMD OCT Fluid Segmentation Dataset
Primary categoryoct
Contained modalitiesoct
Taskssegmentation
Samples600
Classes3 (IRF, SRF, PED)
Splitsall
Size0.5 GB
Source-stated termsAcademic research use (University of Minnesota)
Normalized termsresearch-only
Descriptive screening labelResearch or challenge restriction recorded; check source
Terms scopedataset_files
Access frictionanonymous_direct
Route backendDirect HTTP
Availabilityavailable (checked 2026-07-21)
Acquisition supportloader_implemented_not_live_tested
Legacy sample-loader statusStandard loader included

Access preflight and acquisition

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

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

Upstream page: people.ece.umn.edu/users

Source-term evidence: people.ece.umn.edu/users

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

Citation

@misc{umn_parhi_oct,
title = { UMN Parhi Lab AMD OCT Fluid Segmentation Dataset },
note = { Parhi Lab OCT AMD Fluid Dataset. http://people.ece.umn.edu/users/parhi/data-and-code/ },
url = { http://people.ece.umn.edu/users/parhi/.DATA/OCT/DME/UMNDataset.mat },
}

Source-stated terms

  • Raw source string: Academic research use (University of Minnesota)
  • 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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