Deep learning image reconstruction algorithm for carotid dual-energy computed tomography angiography: evaluation of image quality and diagnostic performance

OBJECTIVES: To evaluate image quality and diagnostic performance of carotid dual-energy computed tomography angiography (DECTA) using deep learning image reconstruction (DLIR) compared with images using adaptive statistical iterative reconstruction-Veo (ASIR-V). METHODS: Carotid DECTA datasets of 28...

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Detalles Bibliográficos
Autores principales: Jiang, Chenyu, Jin, Dan, Liu, Zhuoheng, Zhang, Yan, Ni, Ming, Yuan, Huishu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Vienna 2022
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9701290/
https://www.ncbi.nlm.nih.gov/pubmed/36435892
http://dx.doi.org/10.1186/s13244-022-01308-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9701290/
https://www.ncbi.nlm.nih.gov/pubmed/36435892
http://dx.doi.org/10.1186/s13244-022-01308-2

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