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Abstract #3483

Framework to Identify Motion-Related Artifacts in Non-Diffusion Weighted Reference Images

Douglas C Dean III1 and Andrew L Alexander1,2

1Waisman Center, University of Wisconsin Madison, Madison, WI, United States, 2Medical Physics, University of Wisconsin Madison, Madison, WI, United States

Motion related artifacts can significantly degrade the quality of quantitative measures estimated from diffusion weighted images. Here, we present a method to identify images with significant motion artifact by inspecting the high and low frequency domain from a 1-D Fourier transform along the phase-encode direction of the data. Our results demonstrate the feasibility of such an approach for identifying images with significant motion artifacts, which can ultimately be used to improve the quality of diffusion parameter estimates. This framework may provide a more objective approach to identify images affected by motion-artifact compared to traditional visual inspection.

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