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Accelerated coronary MRI with sRAKI: A database-free self-consistent neural network k-space reconstruction for arbitrary undersampling
PURPOSE: To accelerate coronary MRI acquisitions with arbitrary undersampling patterns by using a novel reconstruction algorithm that applies coil self-consistency using subject-specific neural networks. METHODS: Self-consistent robust artificial-neural-networks for k-space interpolation (sRAKI) per...
Autores principales: | Hosseini, Seyed Amir Hossein, Zhang, Chi, Weingärtner, Sebastian, Moeller, Steen, Stuber, Matthias, Ugurbil, Kamil, Akçakaya, Mehmet |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7034900/ https://www.ncbi.nlm.nih.gov/pubmed/32084235 http://dx.doi.org/10.1371/journal.pone.0229418 |
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