Improving CBCT image quality to the CT level using RegGAN in esophageal cancer adaptive radiotherapy

OBJECTIVE: This study aimed to improve the image quality and CT Hounsfield unit accuracy of daily cone-beam computed tomography (CBCT) using registration generative adversarial networks (RegGAN) and apply synthetic CT (sCT) images to dose calculations in radiotherapy. METHODS: The CBCT/planning CT i...

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Detalles Bibliográficos
Autores principales: Wang, Hao, Liu, Xiao, Kong, Lingke, Huang, Ying, Chen, Hua, Ma, Xiurui, Duan, Yanhua, Shao, Yan, Feng, Aihui, Shen, Zhenjiong, Gu, Hengle, Kong, Qing, Xu, Zhiyong, Zhou, Yongkang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10133081/
https://www.ncbi.nlm.nih.gov/pubmed/36688953
http://dx.doi.org/10.1007/s00066-022-02039-5

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10133081/
https://www.ncbi.nlm.nih.gov/pubmed/36688953
http://dx.doi.org/10.1007/s00066-022-02039-5

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