Impact of an artificial intelligence deep‐learning reconstruction algorithm for CT on image quality and potential dose reduction: A phantom study

BACKGROUND: Recently, computed tomography (CT) manufacturers have developed deep‐learning‐based reconstruction algorithms to compensate for the limitations of iterative reconstruction (IR) algorithms, such as image smoothing and the spatial resolution's dependence on contrast and dose levels. P...

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Detalles Bibliográficos
Autores principales: Greffier, Joël, Si‐Mohamed, Salim, Frandon, Julien, Loisy, Maeliss, de Oliveira, Fabien, Beregi, Jean Paul, Dabli, Djamel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
DIAGNOSTIC IMAGING (IONIZING AND NON‐IONIZING)
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9544990/
https://www.ncbi.nlm.nih.gov/pubmed/35696272
http://dx.doi.org/10.1002/mp.15807

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9544990/
https://www.ncbi.nlm.nih.gov/pubmed/35696272
http://dx.doi.org/10.1002/mp.15807

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