FA-GAN: Fused attentive generative adversarial networks for MRI image super-resolution

High-resolution magnetic resonance images can provide fine-grained anatomical information, but acquiring such data requires a long scanning time. In this paper, a framework called the Fused Attentive Generative Adversarial Networks(FA-GAN) is proposed to generate the super- resolution MR image from...

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Detalles Bibliográficos
Autores principales: Jiang, Mingfeng, Zhi, Minghao, Wei, Liying, Yang, Xiaocheng, Zhang, Jucheng, Li, Yongming, Wang, Pin, Huang, Jiahao, Yang, Guang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Science 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8453331/
https://www.ncbi.nlm.nih.gov/pubmed/34411966
http://dx.doi.org/10.1016/j.compmedimag.2021.101969

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8453331/
https://www.ncbi.nlm.nih.gov/pubmed/34411966
http://dx.doi.org/10.1016/j.compmedimag.2021.101969

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