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Abstract #3743

Ultra-Low-Field MRI Noise Suppression Using a Data Consistency Constraint

Fa-Hsuan Lin1, 2, Yi-Cheng Hsu3, Panu Vesanen2, Jaako O. Nieminen2, Koos C. J. Zevenhoven2, Juhani Dabek2, Lauri T. Parkkonen2, Risto J. Ilmoniemi2

1Institute of Biomedical Engineering, National Taiwan University, Taipei, Taiwan; 2Department of Biomedical Engineering and Computational Science, Aalto University, Espoo, Finland; 3Department of Mathematics, Nnational Taiwan University, Taipei, Taiwan

To mitigate the challenge of low SNR in ultra-low-field (ULF) MRI (typically B0 ~ 100 &[mu]T), we exploit the simultaneous measurements from multiple superconductive quantum interference device (SQUID) sensors to enforce a linear dependency among local k-space data points across coils. Experimental data using 47 SQUID sensors demonstrate that this data consistency (DC) constraint can improve the ULF MRI peak SNR by 2 fold.