CT-Based Pelvic T(1)-Weighted MR Image Synthesis Using UNet, UNet++ and Cycle-Consistent Generative Adversarial Network (Cycle-GAN)

BACKGROUND: Computed tomography (CT) and magnetic resonance imaging (MRI) are the mainstay imaging modalities in radiotherapy planning. In MR-Linac treatment, manual annotation of organs-at-risk (OARs) and clinical volumes requires a significant clinician interaction and is a major challenge. Curren...

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Detalles Bibliográficos
Autores principales: Kalantar, Reza, Messiou, Christina, Winfield, Jessica M., Renn, Alexandra, Latifoltojar, Arash, Downey, Kate, Sohaib, Aslam, Lalondrelle, Susan, Koh, Dow-Mu, Blackledge, Matthew D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Oncology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8363308/
https://www.ncbi.nlm.nih.gov/pubmed/34395244
http://dx.doi.org/10.3389/fonc.2021.665807

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8363308/
https://www.ncbi.nlm.nih.gov/pubmed/34395244
http://dx.doi.org/10.3389/fonc.2021.665807

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