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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