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Abstract #1203

Accurate, Rank-Adaptive Reconstruction of Undersampled Dynamic MRI Data Using Bayesian Information Criterion

Julia Velikina1 and Alexey Samsonov2

1Medical Physics, University of Wisconsin - Madison, Madison, WI, United States, 2Radiology, University of Wisconsin - Madison, Madison, WI, United States

Dynamic MRI must contend with imaging time limits imposed by physiological and physical constraints. Methods promoting low-rank solutions have become increasingly popular for dynamic MRI acceleration due to their ability to reconstruct from limited data. In this work we present a novel model-based reconstruction approach exploiting statistical machinery to spatially adapt the model to underlying signal. It overcomes deficiencies of low-rank techniques to preserve complex temporal dynamics of physiological processes.

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