Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Federated Learning for Medical Imaging: Principles, Algorithms, and Applications

Federated Learning for Medical Imaging: Principles, Algorithms, and Applications

Li, Xiaoxiao
Xu, Ziyue
Fu, Huazhu

Paperback

Series: The Miccai Society Book

Technology & EngineeringBiology

ISBN10: 0443236410
ISBN13: 9780443236419
Publisher: Academic Press
Published: Jun 2 2025
Pages: 230
Weight: 1.08
Height: 0.46 Width: 7.59 Depth: 9.22
Language: English

Federated Learning for Medical Imaging: Principles, Algorithms, and Applications gives a deep understanding of the technology of federated learning (FL), the architecture of a federated system, and the algorithms for FL. It shows how FL allows multiple medical institutes to collaboratively train and use a precise machine learning (ML) model without sharing private medical data via practical implantation guidance. The book includes real-world case studies and applications of FL, demonstrating how this technology can be used to solve complex problems in medical imaging. The book also provides an understanding of the challenges and limitations of FL for medical imaging, including issues related to data and device heterogeneity, privacy concerns, synchronization and communication, etc.

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