E-ophtha (EX + MA): Exudate and Microaneurysm Segmentation
463 color fundus images with pixel-level segmentation: 82 with exudate (EX) + 381 with microaneurysm (MA) annotations. Standard DR lesion-segmentation benchmark.
At a glance
| Field | Value |
|---|---|
| Short name | e_ophtha |
| Full name | E-ophtha (EX + MA): Exudate and Microaneurysm Segmentation |
| Primary category | fundus |
| Contained modalities | fundus |
| Tasks | segmentation |
| Samples | 463 |
| Classes | 2 (Not reported) |
| Splits | all |
| Size | 1.0 GB |
| Source-stated terms | Research only (TeleOphta project; Kaggle mirror) |
| Normalized terms | research-only |
| Descriptive screening label | Research or challenge restriction recorded; check source |
| Terms scope | dataset_files |
| Access friction | controlled_or_manual |
| Route backend | Kaggle |
| Availability | available (checked 2026-07-21) |
| Acquisition support | manual_access_blocked |
| Legacy sample-loader status | Metadata and access only |
Notes
Official source (ADCIS) requires a request form. EyeDataHub uses the Kaggle community mirror. Verify license terms with the original ADCIS distribution before commercial use.
Access preflight and acquisition
- CLI
- Python
# This route requires upstream human action; no transfer starts.
eyehub download e_ophtha --data-dir ./data --dry-run --json
# Follow the official instructions shown by preflight.
from eyedatahub.acquisition import preflight_dataset
from eyedatahub.datasets.registry import REGISTRY
ds = REGISTRY.get_dataset('e_ophtha')
print(preflight_dataset(ds, './data')) # returns manual_access_blocked
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
- BibTeX
- Plain text
@misc{e_ophtha,
title = { E-ophtha (EX + MA): Exudate and Microaneurysm Segmentation },
note = { Decencière et al., 'TeleOphta: Machine Learning and Image Processing Methods for Teleophthalmology', IRBM 2013 },
year = { 2013 },
url = { https://www.kaggle.com/datasets/samriddhibagchi/e-ophtha-diabetic-retinopathy-datasets-ex-ma },
}
Decencière et al., 'TeleOphta: Machine Learning and Image Processing Methods for Teleophthalmology', IRBM 2013.
Source-stated terms
- Raw source string: Research only (TeleOphta project; Kaggle mirror)
- 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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