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Alternating Learning Approach for Variational Networks and Undersampling Pattern in Parallel MRI Applications
The quality of the VNs and SPs was compared against other approaches, including joint learning methods and VN learning with fixed variable density Poisson-disc SPs, using two different datasets and different acceleration factors (AF).
Fast Data-Driven Learning of MRI Sampling Pattern for Large Scale Problems
Purpose: 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.
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