Automatic segmentation for magnetic resonance imaging guided individual elective lymph node irradiation in head and neck cancer patients

Automatic segmentation for magnetic resonance imaging guided individual elective lymph node irradiation in head and neck cancer patients

Background and purpose: In head and neck squamous cell carcinoma (HNSCC) patients, the radiation dose to nearby organs at risk can be reduced by restricting elective neck irradiation from lymph node levels to individual lymph nodes. However, manual delineation of every individual lymph node is time-...

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Bibliographic Details
Main Authors: Floris C.J. Reinders, Mark H.F. Savenije, Mischa de Ridder, Matteo Maspero, Patricia A.H. Doornaert, Chris H.J. Terhaard, Cornelis P.J. Raaijmakers, Kaveh Zakeri, Nancy Y. Lee, Eric Aliotta, Aneesh Rangnekar, Harini Veeraraghavan, Marielle E.P. Philippens
Format: Article
Language:English
Published: Elsevier 2024-10-01
Series:Physics and Imaging in Radiation Oncology
Subjects:
Deep learning
Artificial intelligence
Lymph nodes
Magnetic resonance imaging
Radiotherapy
Squamous cell carcinoma of head and neck
Online Access:http://www.sciencedirect.com/science/article/pii/S2405631624001258
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