Search Results for author: Rajesh N. Keswani

Found 3 papers, 1 papers with code

IPMN Risk Assessment under Federated Learning Paradigm

no code implementations • 8 Nov 2024 • 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

In this study, we develop a federated learning framework for multi-center IPMN classification utilizing a comprehensive pancreas MRI dataset.

Classification Federated Learning

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Adaptive Aggregation Weights for Federated Segmentation of Pancreas MRI

no code implementations • 29 Oct 2024 • Hongyi Pan, Gorkem Durak, Zheyuan Zhang, Yavuz Taktak, Elif Keles, Halil Ertugrul Aktas, Alpay Medetalibeyoglu, Yury Velichko, Concetto Spampinato, Ivo Schoots, Marco J. Bruno, Rajesh N. Keswani, Pallavi Tiwari, Candice Bolan, Tamas Gonda, Michael G. Goggins, Michael B. Wallace, Ziyue Xu, Ulas Bagci

Federated learning (FL) enables collaborative model training across institutions without sharing sensitive data, making it an attractive solution for medical imaging tasks.

Federated Learning MRI segmentation +2

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Large-Scale Multi-Center CT and MRI Segmentation of Pancreas with Deep Learning

1 code implementation • 20 May 2024 • Zheyuan Zhang, Elif Keles, Gorkem Durak, Yavuz Taktak, Onkar Susladkar, Vandan Gorade, Debesh Jha, Asli C. Ormeci, Alpay Medetalibeyoglu, Lanhong Yao, Bin Wang, Ilkin Sevgi Isler, Linkai Peng, Hongyi Pan, Camila Lopes Vendrami, Amir Bourhani, Yury Velichko, Boqing Gong, Concetto Spampinato, Ayis Pyrros, Pallavi Tiwari, Derk C. F. Klatte, Megan Engels, Sanne Hoogenboom, Candice W. Bolan, Emil Agarunov, Nassier Harfouch, Chenchan Huang, Marco J. Bruno, Ivo Schoots, Rajesh N. Keswani, Frank H. Miller, Tamas Gonda, Cemal Yazici, Temel Tirkes, Baris Turkbey, Michael B. Wallace, Ulas Bagci

We also collected CT scans of 1, 350 patients from publicly available sources for benchmarking purposes.

Benchmarking MRI segmentation +2

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