Fast data-driven learning of parallel MRI sampling patterns for large scale problems

In this study, a fast data-driven optimization approach, named bias-accelerated subset selection (BASS), is proposed for learning efficacious sampling patterns (SPs) with the purpose of reducing scan time in large-dimensional parallel MRI. BASS is applicable when Cartesian fully-sampled k-space meas...

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Detalles Bibliográficos
Autores principales: Zibetti, Marcelo V. W., Herman, Gabor T., Regatte, Ravinder R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8481566/
https://www.ncbi.nlm.nih.gov/pubmed/34588478
http://dx.doi.org/10.1038/s41598-021-97995-w

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8481566/
https://www.ncbi.nlm.nih.gov/pubmed/34588478
http://dx.doi.org/10.1038/s41598-021-97995-w

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