Dose reduction potential of vendor-agnostic deep learning model in comparison with deep learning–based image reconstruction algorithm on CT: a phantom study

OBJECTIVES: To compare the dose reduction potential (DRP) of a vendor-agnostic deep learning model (DLM, ClariCT.AI) with that of a vendor-specific deep learning–based image reconstruction algorithm (DLR, TrueFidelity™). METHODS: Computed tomography (CT) images of a multi-sized image quality phantom...

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Detalles Bibliográficos
Autores principales: Choi, Hyunsu, Chang, Won, Kim, Jong Hyo, Ahn, Chulkyun, Lee, Heejin, Kim, Hae Young, Cho, Jungheum, Lee, Yoon Jin, Kim, Young Hoon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2021
Materias:
Computed Tomography
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8364308/
https://www.ncbi.nlm.nih.gov/pubmed/34390372
http://dx.doi.org/10.1007/s00330-021-08199-9

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8364308/
https://www.ncbi.nlm.nih.gov/pubmed/34390372
http://dx.doi.org/10.1007/s00330-021-08199-9

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