Abstract #4276

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

Keerthi Sravan Ravi^1,2, 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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