Deriving Pulmonary Ventilation Images From Clinical 4D-CBCT Using a Deep Learning-Based Model

Deriving Pulmonary Ventilation Images From Clinical 4D-CBCT Using a Deep Learning-Based Model

PurposeThe current algorithms for measuring ventilation images from 4D cone-beam computed tomography (CBCT) are affected by the accuracy of deformable image registration (DIR). This study proposes a new deep learning (DL) method that does not rely on DIR to derive ventilation images from 4D-CBCT (CB...

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Bibliographic Details
Main Authors: Zhiqiang Liu, Yuan Tian, Junjie Miao, Kuo Men, Wenqing Wang, Xin Wang, Tao Zhang, Nan Bi, Jianrong Dai
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-05-01
Series:Frontiers in Oncology
Subjects:
4D-CBCT
pulmonary ventilation imaging
functional imaging
deep learning
image-guided radiotherapy
Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2022.889266/full

Internet

https://www.frontiersin.org/articles/10.3389/fonc.2022.889266/full

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