A more effective CT synthesizer using transformers for cone-beam CT-guided adaptive radiotherapy

A more effective CT synthesizer using transformers for cone-beam CT-guided adaptive radiotherapy

PurposeThe challenge of cone-beam computed tomography (CBCT) is its low image quality, which limits its application for adaptive radiotherapy (ART). Despite recent substantial improvement in CBCT imaging using the deep learning method, the image quality still needs to be improved for effective ART a...

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Bibliographic Details
Main Authors: Xinyuan Chen, Yuxiang Liu, Bining Yang, Ji Zhu, Siqi Yuan, Xuejie Xie, Yueping Liu, Jianrong Dai, Kuo Men
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-08-01
Series:Frontiers in Oncology
Subjects:
adaptive radiotherapy
CBCT
deep learning
transformer
image quality
Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2022.988800/full

Internet

https://www.frontiersin.org/articles/10.3389/fonc.2022.988800/full

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