Deep learning–based velocity antialiasing of 4D‐flow MRI

PURPOSE: To develop a convolutional neural network (CNN) for the robust and fast correction of velocity aliasing in 4D‐flow MRI. METHODS: This study included 667 adult subjects with aortic 4D‐flow MRI data with existing velocity aliasing (n = 362) and no velocity aliasing (n = 305). Additionally, 10...

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Detalles Bibliográficos
Autores principales: Berhane, Haben, Scott, Michael B., Barker, Alex J., McCarthy, Patrick, Avery, Ryan, Allen, Brad, Malaisrie, Chris, Robinson, Joshua D., Rigsby, Cynthia K., Markl, Michael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Research Articles—Computer Processing and Modeling
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9050855/
https://www.ncbi.nlm.nih.gov/pubmed/35381116
http://dx.doi.org/10.1002/mrm.29205

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9050855/
https://www.ncbi.nlm.nih.gov/pubmed/35381116
http://dx.doi.org/10.1002/mrm.29205

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