The dosimetric impact of deep learning-based auto-segmentation of organs at risk on nasopharyngeal and rectal cancer

The dosimetric impact of deep learning-based auto-segmentation of organs at risk on nasopharyngeal and rectal cancer

Abstract Purpose To investigate the dosimetric impact of deep learning-based auto-segmentation of organs at risk (OARs) on nasopharyngeal and rectal cancer. Methods and materials Twenty patients, including ten nasopharyngeal carcinoma (NPC) patients and ten rectal cancer patients, who received radio...

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Bibliographic Details
Main Authors: Hongbo Guo, Jiazhou Wang, Xiang Xia, Yang Zhong, Jiayuan Peng, Zhen Zhang, Weigang Hu
Format: Article
Language:English
Published: BMC 2021-06-01
Series:Radiation Oncology
Subjects:
Treatment planning
Dosimetric
Deep learning
Auto-segmentation
Online Access:https://doi.org/10.1186/s13014-021-01837-y

Internet

https://doi.org/10.1186/s13014-021-01837-y

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