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PANORAMA - Public Training & Development Dataset
Contrast-enhanced (portal-venous) abdominal CT for pancreatic ductal adenocarcinoma (PDAC) detection, from the PANORAMA challenge organised by the Diagnostic Image Analysis Group (DIAG), Radboud UMC. This is the largest public PDAC CT dataset and the first public PDAC detection challenge.
Mirror of the official public training/development cohort only. The hidden validation and test sets used for the challenge leaderboard are not part of this release.
Contents (2238 cases)
Source (level) |
Cases |
|---|---|
| Dutch centres (Radboud UMC + UMC Groningen) | 1964 |
MSD Task07 Pancreas (level=MSD_dataset) |
194 |
NIH Clinical Center Pancreas-CT (level=NIH_dataset) |
80 |
| Total | 2238 (676 PDAC / 1562 non-PDAC) |
images/ 2238 CT volumes, {pid}_{sid}_0000.nii.gz
labels/manual/ 482 expert-delineated masks (gold lesion tier)
labels/automatic/ 1756 fully-automatic masks
clinical_information.csv per-case metadata (+ .xlsx original)
data/ preview parquet for the Dataset Viewer
Ground-truth annotation tiers
6-class voxel masks: 0 background, 1 PDAC lesion, 2 veins, 3 arteries,
4 pancreas parenchyma, 5 pancreatic duct, 6 common bile duct.
labels/manual/(482 cases) - GOLD STANDARD lesion reference. PDAC lesions manually delineated in ITK-SNAP by trained investigators under an expert radiologist (20+ yrs pancreatic-cancer experience). Use these for lesion benchmarking (lesion_gt_gold = True/annotation_tier = manual).labels/automatic/(1756 cases) - weak/auto. Lesion (where present) and all anatomy classes (2-6, every case) were generated automatically by the Alves et al. (2021) algorithm. Treat as weak supervision.
Cross-dataset overlap (evaluation hazard)
This cohort embeds 194 cases from MSD Task07 Pancreas and 80 from the
NIH Pancreas-CT collection. If you benchmark against Angelou0516/msd-pancreas
or Angelou0516/pancreas-ct, exclude these via the level column
(MSD_dataset / NIH_dataset) or the derived external_source column to avoid
leakage. (No per-case ID map back to the original collections is published.)
License & citation
CC BY-NC 4.0 (non-commercial). Source: official DIAG/Radboud Zenodo records
(imaging) + github.com/DIAGNijmegen/panorama_labels (annotations).
Alves, N., Schuurmans, M., Rutkowski, D., Yakar, D., Haldorsen, I., Liedenbaum, M., Molven, A., Vendittelli, P., Litjens, G., Hermans, J., & Huisman, H. (2024). The PANORAMA Study Protocol: Pancreatic Cancer Diagnosis - Radiologists Meet AI. Zenodo. https://doi.org/10.5281/zenodo.10599559