T1-weighted and T2-weighted MRI image synthesis with convolutional generative adversarial networks

BACKGROUND: The objective of this study was to propose an optimal input image quality for a conditional generative adversarial network (GAN) in T1-weighted and T2-weighted magnetic resonance imaging (MRI) images. MATERIALS AND METHODS: A total of 2,024 images scanned from 2017 to 2018 in 104 patient...

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Detalles Bibliográficos
Autores principales: Kawahara, Daisuke, Nagata, Yasushi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Via Medica 2021
Materias:
Research Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8086713/
https://www.ncbi.nlm.nih.gov/pubmed/33948300
http://dx.doi.org/10.5603/RPOR.a2021.0005

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8086713/
https://www.ncbi.nlm.nih.gov/pubmed/33948300
http://dx.doi.org/10.5603/RPOR.a2021.0005

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