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Abstract #0471

Application of a k-Space Interpolating Artificial Neural Network to In-Plane Accelerated Simultaneous Multislice Imaging for Motion Monitoring

Nikolai J Mickevicius1, Eric S Paulson1, and Andrew S Nencka2

1Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI, United States, 2Radiology, Medical College of Wisconsin, Milwaukee, WI, United States

A scan-specific deep learning approach to Cartesian k-space interpolation was extended to in-plane accelerated simultaneous multislice imaging. This method yields images more accurate and less noisy reconstructions than conventional SMS parallel imaging algorithms, particularly as acceleration factors approach the number of receive coils. Furthermore, the models trained in one particular motion state are applicable to test data from a different motion state. This suggests that this method will be useful for cine imaging.

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