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IPMN Risk Assessment under Federated Learning Paradigm

2024-11-08 · Hongyi Pan, Ziliang Hong, Gorkem Durak, Elif Keles, Halil Ertugrul Aktas, Yavuz Taktak, Alpay Medetalibeyoglu, Zheyuan Zhang, Yury Velichko, Concetto Spampinato, Ivo Schoots, Marco J. Bruno, Pallavi Tiwari, Candice Bolan, Tamas Gonda, Frank Miller, Rajesh N. Keswani, Michael B. Wallace, Ziyue Xu, Ulas Bagci

Accurate classification of Intraductal Papillary Mucinous Neoplasms (IPMN) is essential for identifying high-risk cases that require timely intervention. In this study, we develop a federated learning framework for multi-center IPMN classification utilizing a comprehensive pancreas MRI dataset. This dataset includes 652 T1-weighted and 655 T2-weighted MRI images, accompanied by corresponding IPMN risk scores from 7 leading medical institutions, making it the largest and most diverse dataset for IPMN classification to date. We assess the performance of DenseNet-121 in both centralized and federated settings for training on distributed data. Our results demonstrate that the federated learning approach achieves high classification accuracy comparable to centralized learning while ensuring data privacy across institutions. This work marks a significant advancement in collaborative IPMN classification, facilitating secure and high-accuracy model training across multiple centers.

📄 PDF Abstract BibTeX arXiv:2411.05697

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Tasks

Classification Federated Learning

Neural Transformers for Intraductal Papillary Mucosal Neoplasms (IPMN) Classification in MRI images

2022-06-21 · Federica Proietto Salanitri, Giovanni Bellitto, Simone Palazzo, Ismail Irmakci 외

Early detection of precancerous cysts or neoplasms, i.e., Intraductal Papillary Mucosal Neoplasms (IPMN), in pancreas is a challenging and complex task, and it may lead to a more favourable outcome. Once detected, gradin…

Deep Multi-Modal Classification of Intraductal Papillary Mucinous Neoplasms (IPMN) with Canonical Correlation Analysis

2017-10-26 · Sarfaraz Hussein, Pujan Kandel, Juan E. Corral, Candice W. Bolan 외

Pancreatic cancer has the poorest prognosis among all cancer types. Intraductal Papillary Mucinous Neoplasms (IPMNs) are radiographically identifiable precursors to pancreatic cancer; hence, early detection and precise r…

General Classification Multi-modal Classification Prognosis

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

2025-07-29 · Hongyi Pan, Gorkem Durak, Elif Keles, Ziliang Hong 외 arxiv

Pancreatic cancer is projected to be the second-deadliest cancer by 2030, making early detection critical. Intraductal papillary mucinous neoplasms (IPMNs), key cancer precursors, present a clinical dilemma, as current g…

Federated Learning

Radiomics Boosts Deep Learning Model for IPMN Classification

2023-09-11 · Lanhong Yao, Zheyuan Zhang, Ugur Demir, Elif Keles 외

Intraductal Papillary Mucinous Neoplasm (IPMN) cysts are pre-malignant pancreas lesions, and they can progress into pancreatic cancer. Therefore, detecting and stratifying their risk level is of ultimate importance for e…

Classification Decision Making Deep Learning

INN: Inflated Neural Networks for IPMN Diagnosis

2019-06-30 · Rodney LaLonde, Irene Tanner, Katerina Nikiforaki, Georgios Z. Papadakis 외

Intraductal papillary mucinous neoplasm (IPMN) is a precursor to pancreatic ductal adenocarcinoma. While over half of patients are diagnosed with pancreatic cancer at a distant stage, patients who are diagnosed early enj…