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International Journal of Biomedical Imaging
Volume 2008 (2008), Article ID 184123, 8 pages
Research Article

Suppression of MRI Truncation Artifacts Using Total Variation Constrained Data Extrapolation

Biomedizinische NMR Forschungs GmbH, Max-Planck-Institut für biophysikalische Chemie, 37070 Göttingen, Germany

Received 8 January 2008; Revised 21 April 2008; Accepted 5 August 2008

Academic Editor: David Wilson

Copyright © 2008 Kai Tobias Block et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The finite sampling of k-space in MRI causes spurious image artifacts, known as Gibbs ringing, which result from signal truncation at the border of k-space. The effect is especially visible for acquisitions at low resolution and commonly reduced by filtering at the expense of image blurring. The present work demonstrates that the simple assumption of a piecewise-constant object can be exploited to extrapolate the data in k-space beyond the measured part. The method allows for a significant reduction of truncation artifacts without compromising resolution. The assumption translates into a total variation minimization problem, which can be solved with a nonlinear optimization algorithm. In the presence of substantial noise, a modified approach offers edge-preserving denoising by allowing for slight deviations from the measured data in addition to supplementing data. The effectiveness of these methods is demonstrated with simulations as well as experimental data for a phantom and human brain in vivo.