Using RegGAN to generate synthetic CT images from CBCT images acquired with different linear accelerators

Using RegGAN to generate synthetic CT images from CBCT images acquired with different linear accelerators

Abstract Background The goal was to investigate the feasibility of the registration generative adversarial network (RegGAN) model in image conversion for performing adaptive radiation therapy on the head and neck and its stability under different cone beam computed tomography (CBCT) models. Methods...

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Bibliographic Details
Main Authors: Zhenkai Li, Qingxian Zhang, Haodong Li, Lingke Kong, Huadong Wang, Benzhe Liang, Mingming Chen, Xiaohang Qin, Yong Yin, Zhenjiang Li
Format: Article
Language:English
Published: BMC 2023-09-01
Series:BMC Cancer
Subjects:
Radiotherapy
Deep learning
CBCT
sCT
RegGAN
Online Access:https://doi.org/10.1186/s12885-023-11274-7

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