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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