Predicting the hypoxic volume of head and neck tumors from fluorodeoxyglucose positron emission tomography images using artificial intelligence

Predicting the hypoxic volume of head and neck tumors from fluorodeoxyglucose positron emission tomography images using artificial intelligence

Background and purpose: Tumor hypoxia is linked to lower local control rates and increased distant disease progression during head and neck (HN) radiotherapy. 18F-fluoromisonidazole (18F-FMISO) positron emission tomography (PET) imaging measured hypoxia can aid dose selection for HN patients, but it...

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Bibliographic Details
Main Authors: Wei Zhao, Milan Grkovski, Heiko Schoder, Aditya P. Apte, John Humm, Nancy Y. Lee, Joseph O. Deasy, Harini Veeraraghavan
Format: Article
Language:English
Published: Elsevier 2025-04-01
Series:Physics and Imaging in Radiation Oncology
Subjects:
FMISO
FDG
Deep learning
Hypoxia
Head and neck cancer
Generative adversarial network
Online Access:http://www.sciencedirect.com/science/article/pii/S2405631625000740
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