Year: 2015
Type: article
Abstract: PURPOSE: To study and reduce the effect of Gibbs ringing artifact on computed diffusion parameters. METHODS: We reduce the ringing by extrapolating the k-space of each diffusion weighted image beyond the measured part by selecting an adequate regularization term. We evaluate several regularization terms and tune the regularization parameter to find the best compromise between anatomical accuracy of the reconstructed image and suppression of the Gibbs artifact. RESULTS: We demonstrate empirically and analytically that the Gibbs artifact, which is typically observed near sharp edges in magnetic resonance images, has a significant impact on the quantification of diffusion model parameters, even for infinitesimal diffusion weighting. We find the second order total generalized variation to be a good choice for the penalty term to regularize the extrapolation of the k-space, as it provides a parsimonious representation of images, a practically full suppression of Gibbs ringing, and the absence of staircasing artifacts typical for total variation methods. CONCLUSIONS: Regularized extrapolation of the k-space data significantly reduces truncation artifacts without compromising spatial resolution in comparison to the default option of window filtering. In particular, accuracy of estimating diffusion tensor imaging and diffusion kurtosis imaging parameters improves so much that unconstrained fits become possible. Magn Reson Med 76:301-314, 2016. © 2015 Wiley Periodicals, Inc.
Source: Magnetic Resonance in Medicine
DOI: 10.1002/mrm.25866
Institutions: University of Antwerp, iMinds, NYU Langone Health, New York University
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: bronze
Funders: Belgian American Educational Foundation, Belgian Federal Science Policy Office, Fonds Wetenschappelijk Onderzoek, Vlaamse regering, National Institutes of Health, McDonnell Center for Systems Neuroscience, National Institute on Aging, National Institute of Mental Health, National Institute of Neurological Disorders and Stroke, National Institute of Biomedical Imaging and Bioengineering, NIH Blueprint for Neuroscience Research
Awards: Mapping the Human Connectome: Structure, Function, and Heritability, G3848525072, G3986837662, G4076092645, Integrated cerebral networks for perception, cognition and action in human and non-human primates (CEREBNET)., G6389824285, G8299918676, G9000011738, G9000045400, G9000089182, G9000201180, Center for Advanced Imaging Innovation and Research (CAI2R)
OpenAlex ID: W2142554529