Elias Kellner1, Bibek Dhital2,3, Valerij G Kiselev2, Marco Reisert2. 1. Department of Radiology, Medical Physics, University Medical Center Freiburg, Germany. elias.kellner@uniklinik-freiburg.de. 2. Department of Radiology, Medical Physics, University Medical Center Freiburg, Germany. 3. German Cancer Consortium (DKTK) & German Cancer Research Center (DKFZ), Heidelberg, Germany.
Abstract
PURPOSE: To develop a fast and stable method for correcting the gibbs-ringing artifact. METHODS: Gibbs-ringing is a well-known artifact which manifests itself as spurious oscillations in the vicinity of sharp image gradients at tissue boundaries. The origin can be seen in the truncation of k-space during MRI data-acquisition. Correction techniques like Gegenbauer reconstruction or extrapolation methods aim at recovering these missing data. Here, we present a simple and robust method which exploits a different view on the Gibbs-phenomenon: The truncation in k-space can be interpreted as a convolution of the underlying image with a sinc-function. As the image is reconstructed on a discretized grid, the severity of the ringing artifacts depends on how this grid is located with respect to the edge and the oscillation pattern of the function. We propose to reinterpolate the image based on local, subvoxel-shifts to sample the ringing pattern at the zero-crossings of the oscillating sinc-function. RESULTS: With the proposed method, the artifact can simply, effectively, and robustly be removed with a minimal amount of image smoothing. CONCLUSIONS: The robustness of the method suggests it as a suitable candidate for an implementation in the standard image processing pipeline in clinical routine. Magn Reson Med 76:1574-1581, 2016.
PURPOSE: To develop a fast and stable method for correcting the gibbs-ringing artifact. METHODS: Gibbs-ringing is a well-known artifact which manifests itself as spurious oscillations in the vicinity of sharp image gradients at tissue boundaries. The origin can be seen in the truncation of k-space during MRI data-acquisition. Correction techniques like Gegenbauer reconstruction or extrapolation methods aim at recovering these missing data. Here, we present a simple and robust method which exploits a different view on the Gibbs-phenomenon: The truncation in k-space can be interpreted as a convolution of the underlying image with a sinc-function. As the image is reconstructed on a discretized grid, the severity of the ringing artifacts depends on how this grid is located with respect to the edge and the oscillation pattern of the function. We propose to reinterpolate the image based on local, subvoxel-shifts to sample the ringing pattern at the zero-crossings of the oscillating sinc-function. RESULTS: With the proposed method, the artifact can simply, effectively, and robustly be removed with a minimal amount of image smoothing. CONCLUSIONS: The robustness of the method suggests it as a suitable candidate for an implementation in the standard image processing pipeline in clinical routine. Magn Reson Med 76:1574-1581, 2016.
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