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Abstract #1279

Harnessing Embedded Linux and Python for Stand-Alone MRI Applications

Pascal P Stang 1,2 and Greig Scott 2

1 Procyon Engineering, San Jose, CA, United States, 2 Electrical Engineering, Stanford University, Stanford, CA, United States

Advances in RF electronics, high-speed data converters, and multi-core processors have long fueled high-end MRI techniques such as parallel imaging and real-time scanning, yet these same technology advances can also be leveraged to benefit small-scale MR. We present a compact stand-alone MRI console powered by embedded Linux and programmed in Python to investigate the potential of such a platform to deliver modern performance and versatility for NMR/MRI applications constrained in size, power, cost, or user interface. Potential applications include desktop scanners, chemical spectroscopy and relaxometery, RF ablation control, and interventional device safety monitoring.

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