Deep learning methods for enhancing cone‐beam CT image quality toward adaptive radiation therapy: A systematic review

The use of deep learning (DL) to improve cone‐beam CT (CBCT) image quality has gained popularity as computational resources and algorithmic sophistication have advanced in tandem. CBCT imaging has the potential to facilitate online adaptive radiation therapy (ART) by utilizing up‐to‐date patient ana...

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Detalles Bibliográficos
Autores principales: Rusanov, Branimir, Hassan, Ghulam Mubashar, Reynolds, Mark, Sabet, Mahsheed, Kendrick, Jake, Rowshanfarzad, Pejman, Ebert, Martin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
EMERGING IMAGING AND THERAPY MODALITIES
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9543319/
https://www.ncbi.nlm.nih.gov/pubmed/35789489
http://dx.doi.org/10.1002/mp.15840

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9543319/
https://www.ncbi.nlm.nih.gov/pubmed/35789489
http://dx.doi.org/10.1002/mp.15840

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