Virtual patient‐specific QA with DVH‐based metrics

We demonstrate a virtual pretreatment patient‐specific QA (PSQA) procedure that is capable of quantifying dosimetric effect on patient anatomy for both intensity modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT). A machine learning prediction model was developed to use linear...

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Detalles Bibliográficos
Autores principales: Lay, Lam M., Chuang, Kai‐Cheng, Wu, Yuyao, Giles, William, Adamson, Justus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Radiation Oncology Physics
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9680566/
https://www.ncbi.nlm.nih.gov/pubmed/35570395
http://dx.doi.org/10.1002/acm2.13639

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9680566/
https://www.ncbi.nlm.nih.gov/pubmed/35570395
http://dx.doi.org/10.1002/acm2.13639

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