A 4D-CBCT correction network based on contrastive learning for dose calculation in lung cancer

Abstract Objective This study aimed to present a deep-learning network called contrastive learning-based cycle generative adversarial networks (CLCGAN) to mitigate streak artifacts and correct the CT value in four-dimensional cone beam computed tomography (4D-CBCT) for dose calculation in lung cance...

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Bibliographic Details

Published in:	Radiation Oncology
Main Authors:	Nannan Cao, Ziyi Wang, Jiangyi Ding, Heng Zhang, Sai Zhang, Liugang Gao, Jiawei Sun, Kai Xie, Xinye Ni
Format:	Article
Language:	English
Published:	BMC 2024-02-01
Subjects:	4D-CBCT Deep learning Image quality correction Lung cancer
Online Access:	https://doi.org/10.1186/s13014-024-02411-y