CT-based auto-segmentation of multiple target volumes for all-in-one radiotherapy in rectal cancer patients

CT-based auto-segmentation of multiple target volumes for all-in-one radiotherapy in rectal cancer patients

Abstract Background This study aimed to evaluate the clinical feasibility and performance of CT-based auto-segmentation models integrated into an All-in-One radiotherapy workflow for rectal cancer. Methods This study included 312 rectal cancer patients, with 272 used to train three nnU-Net models fo...

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Bibliographic Details
Main Authors: Xuemin Li, Luqi Wang, Mengying Yang, Xianan Li, Ting Zhao, Mingqing Wang, Siyi Lu, Yunsong Ji, Wei Zhang, Lecheng Jia, Ran Peng, Junjie Wang, Hao Wang
Format: Article
Language:English
Published: BMC 2025-08-01
Series:Radiation Oncology
Subjects:
Rectal cancer
Neoadjuvant radiotherapy
Deep learning
Auto-segmentation
Online adaptive radiotherapy
All-in-One radiotherapy
Online Access:https://doi.org/10.1186/s13014-025-02694-9
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https://doi.org/10.1186/s13014-025-02694-9

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