Development of a deep learning-based error detection system without error dose maps in the patient-specific quality assurance of volumetric modulated arc therapy

To detect errors in patient-specific quality assurance (QA) for volumetric modulated arc therapy (VMAT), we proposed an error detection method based on dose distribution analysis using unsupervised deep learning approach and analyzed 161 prostate VMAT beams measured with a cylindrical detector. For...

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Detalles Bibliográficos
Autores principales: Kimura, Yuto, Kadoya, Noriyuki, Oku, Yohei, Jingu, Keiichi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Regular paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10354858/
https://www.ncbi.nlm.nih.gov/pubmed/37177789
http://dx.doi.org/10.1093/jrr/rrad028

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10354858/
https://www.ncbi.nlm.nih.gov/pubmed/37177789
http://dx.doi.org/10.1093/jrr/rrad028

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