Contrast agent dose reduction in computed tomography with deep learning using a conditional generative adversarial network

OBJECTIVES: To reduce the dose of intravenous iodine-based contrast media (ICM) in CT through virtual contrast-enhanced images using generative adversarial networks. METHODS: Dual-energy CTs in the arterial phase of 85 patients were randomly split into an 80/20 train/test collective. Four different...

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Detalles Bibliográficos
Autores principales: Haubold, Johannes, Hosch, René, Umutlu, Lale, Wetter, Axel, Haubold, Patrizia, Radbruch, Alexander, Forsting, Michael, Nensa, Felix, Koitka, Sven
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2021
Materias:
Imaging Informatics and Artificial Intelligence
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8270814/
https://www.ncbi.nlm.nih.gov/pubmed/33630160
http://dx.doi.org/10.1007/s00330-021-07714-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8270814/
https://www.ncbi.nlm.nih.gov/pubmed/33630160
http://dx.doi.org/10.1007/s00330-021-07714-2

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