Feasibility of Continual Deep Learning-Based Segmentation for Personalized Adaptive Radiation Therapy in Head and Neck Area

Feasibility of Continual Deep Learning-Based Segmentation for Personalized Adaptive Radiation Therapy in Head and Neck Area

This study investigated the feasibility of deep learning-based segmentation (DLS) and continual training for adaptive radiotherapy (RT) of head and neck (H&N) cancer. One-hundred patients treated with definitive RT were included. Based on 23 organs-at-risk (OARs) manually segmented in initial pl...

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Bibliographic Details
Main Authors: Nalee Kim, Jaehee Chun, Jee Suk Chang, Chang Geol Lee, Ki Chang Keum, Jin Sung Kim
Format: Article
Language:English
Published: MDPI AG 2021-02-01
Series:Cancers
Subjects:
head and neck cancer
deep learning
auto segmentation
artificial intelligence
adaptive radiation therapy
Online Access:https://www.mdpi.com/2072-6694/13/4/702

Internet

https://www.mdpi.com/2072-6694/13/4/702

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