Usefulness of a Metal Artifact Reduction Algorithm in Digital Tomosynthesis Using a Combination of Hybrid Generative Adversarial Networks

In this study, a novel combination of hybrid generative adversarial networks (GANs) comprising cycle-consistent GAN, pix2pix, and (mask pyramid network) MPN (CGpM-metal artifact reduction [MAR]), was developed using projection data to reduce metal artifacts and the radiation dose during digital tomo...

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Detalles Bibliográficos
Autores principales: Gomi, Tsutomu, Sakai, Rina, Hara, Hidetake, Watanabe, Yusuke, Mizukami, Shinya
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8467368/
https://www.ncbi.nlm.nih.gov/pubmed/34573971
http://dx.doi.org/10.3390/diagnostics11091629

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8467368/
https://www.ncbi.nlm.nih.gov/pubmed/34573971
http://dx.doi.org/10.3390/diagnostics11091629

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