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Abstract #4276

Single board computer as a satellite-linked, deep learning capable pocket MR workstation: a feasibility study

Keerthi Sravan Ravi1,2, John Thomas Vaughan Jr.2, and Sairam Geethanath2
1Biomedical Engineering, Columbia University, New York, NY, United States, 2Columbia Magnetic Resonance Research Center, New York, NY, United States

This work shows the feasibility of employing a Raspberry Pi (RPi) single-board computer as a deep learning capable MR workstation. RPi’s ability to run a Tensorflow-Lite optimized brain tumour segmentation model is demonstrated. A comparison of data upload across fixed broadband, cellular broadband (LTE, 3G) and satellite terminal methods of internet access is presented. Finally, the setup described in this work is compared with a conventional fixed MRI workstation and a portable MRI workstation.

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