Keywords: New Trajectories & Spatial Encoding Methods, New Trajectories & Spatial Encoding Methods
Motivation: Quantitative MRI requires multiple acquisitions to sufficiently characterize a biophysical-model of interest, resulting in long scan times.
Goal(s): Propose a new general strategy for accelerating MRI using subvoxel-shifting as a means of encoding.
Approach: POSition Encoding (POSE) applies unique subvoxel-shifts along the acquisition parameter dimension, which is combined with a biophysical-model to generate accelerated and enhanced resolution biophysical-parameter maps. Using T1 quantification as an application, POSE was validated both numerically and experimentally.
Results: Results show that POSE 1) generates quantitative maps that agree well with the reference method, 2) has robust noise performance and 3) is applicable to any biophysical-model of interest.
Impact: POSE combines subvoxel-scale spatial encoding with biophysical-models to achieve enhanced resolution with acceleration. Its ease of implementation, robust noise performance and versatility makes it an attractive framework applicable to any quantitative biophysical-model of interest.
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