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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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| Опубликовано в: : | Eur Radiol |
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| Главные авторы: | , , , , , , , , |
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
Springer Berlin Heidelberg
2021
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| Предметы: | |
| Online-ссылка: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8270814/ https://ncbi.nlm.nih.gov/pubmed/33630160 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s00330-021-07714-2 |
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