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Abstract #4657

Pseudo-Cartesian k-Space Interpolation Using Artificial Neural Networks

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

This work aims to extend the RAKI method for artificial intelligence-based k-space interpolation to non-Cartesian acquisitions. It was tested in radial acquisitions up to acceleration factors of 7. This method performs similarly well, or better than total-variation regularized sensitivity encoding.

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