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Abstract #3522

Aliasing Artifact Reduction in Spiral Real-Time MRI

Ye Tian1, Yongwan Lim1, Ziwei Zhao1, Dani Byrd2, Shrikanth Narayanan1,2, and Krishna S. Nayak1
1Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, United States, 2Department of Linguistics, University of Southern California, Los Angeles, CA, United States

Mid-sagittal spiral MRI of speech production often suffers from a distinct and disruptive aliasing artifact arising from a spurious signal outside the FOV. In this work, we determine that the spurious signal is caused by gradient nonlinearity and an ineffective anti-aliasing filter in spiral readout. We propose and evaluate two methods to mitigate the artifact, termed the large FOV (LF) method and the estimation-subtraction (ES) method. Qualitative evaluation score from two speech experts using a 5-level Likert scale improved 1.25 and 1.35 with 228.8% and 6.9% increment of reconstruction time for the LF and ES methods, respectively.

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