Real‐time cardiovascular MR with spatio‐temporal artifact suppression using deep learning–proof of concept in congenital heart disease

PURPOSE: Real‐time assessment of ventricular volumes requires high acceleration factors. Residual convolutional neural networks (CNN) have shown potential for removing artifacts caused by data undersampling. In this study, we investigated the ability of CNNs to reconstruct highly accelerated radial...

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Detalles Bibliográficos
Autores principales: Hauptmann, Andreas, Arridge, Simon, Lucka, Felix, Muthurangu, Vivek, Steeden, Jennifer A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2018
Materias:
Full Papers—Imaging Methodology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6492123/
https://www.ncbi.nlm.nih.gov/pubmed/30194880
http://dx.doi.org/10.1002/mrm.27480

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6492123/
https://www.ncbi.nlm.nih.gov/pubmed/30194880
http://dx.doi.org/10.1002/mrm.27480

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