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ABSTRACT: Purpose
To determine how various compressed sensing (CS) models can accelerate alternating Look-Locker T1$$ {T}_1 $$ mapping.Methods
An alternating Look-Locker acquisition was retrospectively accelerated by factors of 1-12. The data was reconstructed into 12 images with multiple CS models, which utilized combinations of spatial total variation, locally low-rank regularization, and subspace constraints. Complex non-linear least squares signal fitting was performed to obtain the T1$$ {T}_1 $$ maps. The accelerated T1$$ {T}_1 $$ maps were compared against the T1$$ {T}_1 $$ map of a full data reference reconstruction.Results
A subspace-constrained reconstruction model with spatial total variation and locally low-rank regularization outperformed all other models as measu
SUBMITTER: Aarnio A
PROVIDER: S-EPMC12393196 | biostudies-literature | 2025 Nov
REPOSITORIES: biostudies-literature