Volumetric modulated arc therapy dose prediction and deliverable treatment plan generation for prostate cancer patients using a densely connected deep learning model

BACKGROUND AND PURPOSE: Radiation therapy treatment planning is a manual, time-consuming task that might be accelerated using machine learning algorithms. In this study, we aimed to evaluate if a triplet-based deep learning model can predict volumetric modulated arc therapy (VMAT) dose distributions...

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Detalles Bibliográficos
Autores principales: Lempart, Michael, Benedek, Hunor, Jamtheim Gustafsson, Christian, Nilsson, Mikael, Eliasson, Niklas, Bäck, Sven, Munck af Rosenschöld, Per, Olsson, Lars E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Original Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8353474/
https://www.ncbi.nlm.nih.gov/pubmed/34401537
http://dx.doi.org/10.1016/j.phro.2021.07.008

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8353474/
https://www.ncbi.nlm.nih.gov/pubmed/34401537
http://dx.doi.org/10.1016/j.phro.2021.07.008

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