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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