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Abstract #1962

Deep Spatiotemporal Phase Unwrapping of Phase-Contrast MRI Data

Jiacheng Jason He1, Christopher Sandino1, David Zeng1, Shreyas Vasanawala1,2, and Joseph Cheng2

1Electrical Engineering, Stanford University, Stanford, CA, United States, 2Radiology, Stanford University, Stanford, CA, United States

This work demonstrates the advantage temporal information provides for deep phase unwrapping of phase-contrast MRI data. Using a patch-based, three-dimensional ResNet architecture, our model performs better than state-of-the-art single-step algorithms. Our deep spatiotemporal phase unwrapping model continues the quest to lower Venc values to increase dynamic range and velocity-to-noise ratio (VNR) of 4D flow data by providing a robust method for phase unwrapping.

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