Fast data-driven learning of parallel MRI sampling patterns for large scale problems
Abstract 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-s...
Main Authors: | Marcelo V. W. Zibetti, Gabor T. Herman, Ravinder R. Regatte |
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Format: | Article |
Language: | English |
Published: |
Nature Publishing Group
2021-09-01
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Series: | Scientific Reports |
Online Access: | https://doi.org/10.1038/s41598-021-97995-w |
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