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Abstract #4604

Pileup Artifact Correction Near Metal Implants Using Deep Neural Networks and Spectral K-Space Modulation

Kevin Koch1, Robin Karr1, and Andrew Nencka1

1Radiology, Medical College of Wisconsin, Milwaukee, WI, United States

Three-dimensional multispectral imaging (3D-MSI) techniques used for metal artifact correction can provide relatively clear images near most metallic implants. However, within localized regions near some implants, 3D-MSI demonstrate residual artifacts that are unlike any other artifact previously seen in MR images. These confounding features in 3D-MSI are known as “pileup” or “ring” artifacts. In this study, we present a novel approach to residual artifact correction in 3D-MSI that relies on 1) deep neural networks, 2) physical modeling of local gradients, and 3) k-space modulation and replacement of spectral data in compromised regions

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