Paul Polak1,2, David Lindner1, Jannis Hanspach1, Michael Dwyer1, Niels Bergsland1, Nicola Bertolino1,2, Robert Zivadinov1,2, and Ferdinand Schweser1,2
1Neurology, Buffalo Neuroimaging Analysis Center, State University of New York at Buffalo, Buffalo, NY, United States, 2Molecular and Translational Imaging, Clinical Translational Research Center, Buffalo, NY, United States
Gradient “unwarping” is the removal of image distortions caused by non-linearity of the imaging gradient fields. Exasperated by increasing distance from isocenter, the unwarping process is applied to every image by the manufacturer and generally is a “black-box” process occurring near the end of the image processing pipeline. This is problematic for researchers who source their data from a more primitive step, e.g. from raw k-space, since this data is generally “warped”. Presented here is a method to reverse engineer the spherical harmonic coefficients that describe the warp field and are used by the vendor’s black-box process, allowing the researcher to perform the gradient unwarping off-line as a post-processing step.