Cyst-X: A Multi-Center MRI Benchmark and Federated Learning Framework for Malignancy-Risk Stratification of Pancreatic Cystic Neoplasm

Dataset: https://osf.io/74vfs/

Official implementation of Cyst-X, an end-to-end multi-center pipeline integrating state-of-the-art pancreas segmentation, federated optimization, and classical radiomics pipelines for automated malignancy risk stratification of intraductal papillary mucinous neoplasms (IPMNs).

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📌 Overview

Pancreatic cancer is projected to be the second-deadliest cancer by 2030, making early detection critical. IPMNs are key cancer precursors, but current consensus guidelines struggle to stratify malignancy risk accurately.

Cyst-X addresses this structural bottleneck by providing:

1. The Largest Multi-Center Pancreas MRI Resource: 1,461 abdominal MRI scans from 764 patients across seven international medical centers with expert annotations and pathology-anchored ground truth.
2. Advanced Pancreas Segmentation: Integrating PanSegNet (a linear self-attention transformer-based backbone) for high-fidelity region of interest (ROI) extraction.
3. Privacy-Preserving Federated Learning: Distributed risk classification training utilizing FedAvg and FedProx without exchanging raw clinical images.

📂 Repository Structure

Cyst-X/
├── Classification/          # Pipelines and frameworks for deep risk modeling
├── Segmentation/            # Pipeline and engines for pancreas ROI localization
└── README.md                # Main repository documentation hub