Range probing as a quality control tool for CBCT‐based synthetic CTs: In vivo application for head and neck cancer patients

PURPOSE: Cone‐beam CT (CBCT)‐based synthetic CTs (sCT) produced with a deep convolutional neural network (DCNN) show high image quality, suggesting their potential usability in adaptive proton therapy workflows. However, the nature of such workflows involving DCNNs prevents the user from having dire...

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Detalles Bibliográficos
Autores principales: Seller Oria, Carmen, Thummerer, Adrian, Free, Jeffrey, Langendijk, Johannes A., Both, Stefan, Knopf, Antje C., Meijers, Arturs
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
EMERGING IMAGING AND THERAPY MODALITIES
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8456797/
https://www.ncbi.nlm.nih.gov/pubmed/34077554
http://dx.doi.org/10.1002/mp.15020

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8456797/
https://www.ncbi.nlm.nih.gov/pubmed/34077554
http://dx.doi.org/10.1002/mp.15020

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