| --- |
| license: cc-by-nc-4.0 |
| task_categories: |
| - image-segmentation |
| tags: |
| - medical-imaging |
| - ct |
| - pancreas |
| - pancreatic-cancer |
| - pdac |
| pretty_name: PANORAMA (Pancreatic Cancer Diagnosis - Radiologists Meet AI) |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| dataset_info: |
| features: |
| - name: study_id |
| dtype: string |
| - name: patient_id |
| dtype: string |
| - name: annotation_tier |
| dtype: string |
| - name: label |
| dtype: string |
| - name: level |
| dtype: string |
| - name: external_source |
| dtype: string |
| - name: num_slices |
| dtype: int32 |
| - name: image |
| dtype: image |
| - name: mask |
| dtype: image |
| - name: overlay |
| dtype: image |
| splits: |
| - name: train |
| num_bytes: 614182147 |
| num_examples: 2238 |
| download_size: 611706093 |
| dataset_size: 614182147 |
| --- |
| |
| # 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 |
|
|
