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Abstract #2809

Gibbs ringing removal in diffusion MRI using second order total variation minimization

Jelle Veraart 1 , Florian Knoll 1 , Jan Sijbers 2 , Els Fieremans 1 , and Dmitry S. Novikov 1

1 Center for Biomedical Imaging, NYU Langone Medical Center, New York, NY, United States, 2 iMinds - Vision Lab, University of Antwerp, Antwerp, Belgium

MR images are typically distorted with spurious signal that appear near sharp edges in the images. This Gibbs artifact results from the truncation of the k-space. Although the artifacts has a significant impact on the quantification of diffusion MR indices, it is often ignored or only reduced by smoothing the data at the expense of image blurring. The present work demonstrates that extrapolating the data in k-space beyond the measured part by means of second order total generalization variation minimization allows for a suppression of truncation artifacts without compromising resolution or modeling the image as a piecewise constant function.

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