Deep Learning for Patient-Specific Quality Assurance: Predicting Gamma Passing Rates for IMRT Based on Delivery Fluence Informed by log Files

Objectives: In this study, we propose a deep learning-based approach to predict Intensity-modulated radiation therapy (IMRT) quality assurance (QA) gamma passing rates using delivery fluence informed by log files. Methods: A total of 112 IMRT plans for chest cancers were planned and measured by port...

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Detalles Bibliográficos
Autores principales: Huang, Ying, Pi, Yifei, Ma, Kui, Miao, Xiaojuan, Fu, Sichao, Zhu, Zhen, Cheng, Yifan, Zhang, Zhepei, Chen, Hua, Wang, Hao, Gu, Hengle, Shao, Yan, Duan, Yanhua, Feng, Aihui, Zhuo, Weihai, Xu, Zhiyong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2022
Materias:
Novel Applications of Artificial Intelligence in Cancer Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9218492/
https://www.ncbi.nlm.nih.gov/pubmed/35726209
http://dx.doi.org/10.1177/15330338221104881

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9218492/
https://www.ncbi.nlm.nih.gov/pubmed/35726209
http://dx.doi.org/10.1177/15330338221104881

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