What is the optimal input information for deep learning-based pre-treatment error identification in radiotherapy?

BACKGROUND AND PURPOSE: Deep learning (DL) provides high sensitivity for detecting and identifying errors in pre-treatment radiotherapy quality assurance (QA). This work’s objective was to systematically evaluate the impact of different dose comparison and image preprocessing methods on DL model per...

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Detalles Bibliográficos
Autores principales: Wolfs, Cecile J.A., Verhaegen, Frank
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Original Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9465434/
https://www.ncbi.nlm.nih.gov/pubmed/36106060
http://dx.doi.org/10.1016/j.phro.2022.08.007

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9465434/
https://www.ncbi.nlm.nih.gov/pubmed/36106060
http://dx.doi.org/10.1016/j.phro.2022.08.007

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