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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