Abstract #1359

Retrospective motion compensation for spiral brain imaging with a deep convolutional neural network

Quan Dou¹, Zhixing Wang¹, Xue Feng¹, John P. Mugler², and Craig H. Meyer¹

¹Biomedical Engineering, University of Virginia, Charlottesville, VA, United States, ²Radiology & Medical Imaging, University of Virginia, Charlottesville, VA, United States

Head motion can severely degrade the quality of MR brain images. A deep convolutional neural network was implemented in this study to retrospectively compensate for motion in spiral imaging. The network was trained on images with simulated motion artifacts and tested on both simulated and in vivo data. The image quality was improved after the motion correction.

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