Cyst-X: A Multi-Center Pancreas MRI Dataset for IPMN Segmentation and Malignancy-Risk Stratification

Pancreatic cystic neoplasms, including Intraductal Papillary Mucinous Neoplasms (IPMNs), are increasingly detected due to advancements in imaging technologies and growing awareness. Early diagnosis and accurate characterization of IPMNs are essential for guiding appropriate clinical management and reducing unnecessary interventions.

To support research in this domain, we present Cyst-X, the largest multi-center pancreas MRI resource to date. It comprises 723 T1-weighted (T1W) and 738 T2-weighted (T2W) abdominal MRI scans from 764 distinct patients collected across seven international clinical centers:

• New York University Langone Health (NYU)
• Mayo Clinic Florida (MCF)
• Northwestern University (NU)
• Allegheny Health Network (AHN)
• Mayo Clinic Arizona (MCA)
• Istanbul University Faculty of Medicine (IU)
• Erasmus Medical Center (EMC)

📁 Dataset Directory Structure

Cyst-X/
├── classification/
│   ├── t1/
│   │   ├── images/                  # 723 preprocessed pancreatic ROIs
│   │   └── visualizations/
│   ├── t2/
│   │   ├── images/                  # 738 preprocessed pancreatic ROIs
│   │   └── visualizations/
│   ├── IPMN_labels_t1_total.xlsx
│   ├── IPMN_labels_t2_total.xlsx
│   ├── IPMN_labels_total.xlsx
│   ├── t1_split.csv
│   └── t2_split.csv
├── segmentation/
│   ├── t1/
│   │   ├── images/                  # 723 full-volume MRI scans
│   │   ├── masks/                   # Corresponding pancreas masks
│   │   └── visualizations/
│   └── t2/
│       ├── images/                  # 738 full-volume MRI scans
│       ├── masks/                   # Corresponding pancreas masks
│       └── visualizations/
└── data splits/                     # Previously published splits, retained for reference

The classification/ and segmentation/ directories are stored directly at the repository root. This release uses the active Cyst-X-v2.3 data. The classification ROIs were generated from N4-corrected images using the reference masks.

Use classification/t1_split.csv and classification/t2_split.csv for the current five-fold classification experiments. The paired T1W/T2W experiments follow the T1 patient fold assignments. The older files under data splits/ are retained for reference and should not replace these current split files.

Intermediate Cyst-X-RAS and Cyst-X-n4 directories are not included in this release. Preprocessing code is maintained in the GitHub code repository.

The current release (main, tagged v2) corrects image–mask orientation mismatches present in some v1 cases. N4 bias-field correction is applied during classification preprocessing. The original release remains available under the v1 tag.