Deep Learning for Automated Elective Lymph Node Level Segmentation for Head and Neck Cancer Radiotherapy

Deep Learning for Automated Elective Lymph Node Level Segmentation for Head and Neck Cancer Radiotherapy

Depending on the clinical situation, different combinations of lymph node (LN) levels define the elective LN target volume in head-and-neck cancer (HNC) radiotherapy. The accurate auto-contouring of individual LN levels could reduce the burden and variability of manual segmentation and be used regar...

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Bibliographic Details
Main Authors: Victor I. J. Strijbis, Max Dahele, Oliver J. Gurney-Champion, Gerrit J. Blom, Marije R. Vergeer, Berend J. Slotman, Wilko F. A. R. Verbakel
Format: Article
Language:English
Published: MDPI AG 2022-11-01
Series:Cancers
Subjects:
computed tomography
deep learning
head-and-neck cancer
lymph nodes
radiation oncology
auto-contouring
Online Access:https://www.mdpi.com/2072-6694/14/22/5501

Internet

https://www.mdpi.com/2072-6694/14/22/5501

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