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: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Publishing Group
2021-09-01
|
| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-021-97995-w |