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Abstract #1803

Performance of SQUID Sensor Arrays for MRI of the Brain

Koos Zevenhoven1, Risto J. Ilmoniemi1

1Department of Biomedical Engineering & Computational Science (BECS), Aalto University, Helsinki, Finland

While the state of the art in MRI has moved into multiple-tesla magnetic fields, another approach, ultra-low-field (ULF) MRI, has emerged, where the precession field is in the microtesla range. This is made possibly by pulsed pre-polarization fields and highly sensitive superconducting quantum interference device (SQUID) sensors. While ULF MRI has advantages in improved T1 contrast and compatibility with other techniques such as biomagnetic measurements, the SNR of the images is still low for applications. In the absence of applicable studies, we describe and demonstrate approaches to analyzing and optimizing SQUID sensor arrays for ULF MRI.