Keywords: Motion Correction, Acquisition Methods
Motivation: Ultra-low field (ULF) MRI technology offers affordable and accessible imaging but often requires long scan times to achieve sufficient signal-to-noise ratio (SNR). This increases the risk of image degradation and artifact due to patient motion, especially for those who cannot voluntarily remain still.
Goal(s): To enable motion-corrected brain MRI at ULF.
Approach: We combined alignedSENSE, a data-driven motion correction algorithm based on the SENSE model, with the self-navigated DISORDER phase encoding sampling trajectory to correct for within-scan motion. Additionally, we correct for within-scan phase variations that arise from other system imperfections.
Results: The proposed motion+phase correction improved image quality in all cases tested.
Impact: alignedSENSE, combined with phase correction, can effectively improve image quality without increasing scan time in ULF MRI systems without increasing scan time, making them more valuable for clinical use.
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