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Abstract #3736

Gradient Unwarping for Phase Imaging Reconstruction

Paul Polak 1 , Robert Zivadinov 1,2 , and Ferdinand Schweser 1,2

1 Department of Neurology, Buffalo Neuroimaging Analysis Center, State University of New York at Buffalo, Buffalo, NY, United States, 2 Molecular and Translational Imaging Center, MRI Center, Clinical and Translational Research Center, Buffalo, NY, United States

Images reconstructed by direct Fourier transform from k-space data are hindered by gradient non-linearities which result in imaging voxel distortions. Correction of these effects, or gradient unwarping, is provided by MR manufacturers near the end of their image reconstruction pipeline; however, this is typically applied only to multi-channel combined magnitude images. Advanced reconstruction techniques utilizing compressed sensing, non-Cartesian sampling or multi-channel phase images typically use data from a more primary step (i.e. k-space or single channel data), and are thus subject to gradient warping effects in the final reconstruction. We present here a technique to unwarp complex-valued MRI data which is then suitable for advanced phase imaging reconstruction.

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