Gibbs-ringing artifact removal based on local subvoxel-shifts
Open accessAbstract
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. © 2015 International Society for Magnetic Resonance in Medicine.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
MRtrix3 offers image analysis methods less specific to dMRI, including image filtering and calculation, statistics, image denoising, Gibbs ringing suppression, intensity normalisation, and diffeomorphic image registration.
“MRtrix3 also offers image analysis methods less specific to dMRI such as image filtering and calculation, statistics, image denoising (Veraart et al., 2016) and Gibbs ringing suppression (Kellner et al., 2016) , intensity normalisation (Raffelt et al., 2017a) and diffeomorphic image registration (Raffelt et al., 2011) .”
From MRtrix3: A fast, flexible and open software framework for medical image processing and visualisation (2019) · cites this paper as Kellner et al., 2016
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
No references could be resolved yet.
Research works printed but not linked: 12
- Gottlieb D, Shu CW, Solomonoff A, Vandeven H. On the Gibbs phe- nomenon I: recovering exponential accuracy from the Fourier partial sum of a nonperiodic analytic function. J Comput Appl Math 1992; 43:81-98.
- Gottlieb D, Shu CW. On the Gibbs phenomenon and its resolution. SIAM Rev 1997;39:644-668.
- Jerri AJ. Lanczos-like r-factors for reducing the Gibbs phenomenon in general orthogonal expansions and other representations. J Comput Anal Appl 2000;2:111-127.
- Archibald R, Gelb A. A method to reduce the Gibbs ringing artifact in MRI scans while keeping tissue boundary integrity. IEEE Trans Med Imaging 2002;21:305-319.
- Boyd JP. Trouble with Gegenbauer reconstruction for defeating Gibbs phenomenon: Runge phenomenon in the diagonal limit of Gegenba- uer polynomial approximations. J Comput Phys 2005;204:253-264.
- Block KT, Uecker M, Frahm J. Suppression of MRI truncation artifacts using total variation constrained data extrapolation. Int J Biomed Imag- ing 2008;2008. Available at: http://dx.doi.org/10.1155/2008/184123. · DOI
- Perrone D, Aelterman J, Pi zurica A, Jeurissen B, Philips W, Leemans A. The effect of Gibbs ringing artifacts on measures derived from dif- fusion MRI. NeuroImage 2015;120:441-455.
- Veraart J, Fieremans E, Jelescu IO, Knoll F, Novikov DS. Gibbs ringing in diffusion MRI. Magn Reson Med 2016;76:301-314.
- Shizgal BD, Jung JH. Towards the resolution of the Gibbs phenomena. J Comput Appl Math 2003;161:41-65.
- Feng Q, Huang X, Feng Y. A fast algorithm to reduce Gibbs ringing arti- fact based on the Chebyshev polynomials. J Image Graph 2006;8:013.
- Amartur S, Haacke EM. Modified iterative model based on data extrapolation method to reduce Gibbs ringing. J Magn Reson Imaging. 1991;1:307-317.
- Constable R, Henkelman R. Data extrapolation for truncation artifact removal. Magn Reson Med 1991;17:108-118.
Cited by
Sorted by citations
MRtrix3: A fast, flexible and open software framework for medical image processing and visualisation
Tournier, J.-D., Smith, R., Raffelt, D., Tabbara, R., Dhollander, T., Pietsch, M., Christiaens, D., Jeurissen, B., Yeh, C.-H., & Connelly, A. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.116137 · Cited by 2,974 · see citing works
Lead-DBS v2: Towards a comprehensive pipeline for deep brain stimulation imaging
Horn, A., Li, N., Dembek, T. A., Kappel, A., Boulay, C., Ewert, S., Tietze, A., Husch, A., Perera, T., Neumann, W.-J., et al. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2018.08.068 · Cited by 739 · see citing works
Self-citationSANDI: a compartment‐based model for non‐invasive apparent soma and neurite imaging by diffusion MRI
Palombo, M., Ianus, A., Guerreri, M., Nunes, D., Alexander, D. C., Shemesh, N., & Zhang, H. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.116835 · Cited by 349 · see citing works
Jelescu, I. O., de Skowronski, A., Geffroy, F., Palombo, M., & Novikov, D. S. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119277 · Cited by 177 · see citing works
Coenen, V. A., Schumacher, L. V., Kaller, C., Schlaepfer, T. E., Reinacher, P. C., Egger, K., Urbach, H., & Reisert, M. (2018) · NeuroImage Clinical · doi:10.1016/j.nicl.2018.03.019 · Cited by 127 · see citing works
Self-citationAyoub, R., Ruddy, R. M., Cox, E., Oyefiade, A., Derkach, D., Laughlin, S., Ades-aron, B., Shirzadi, Z., Fieremans, E., MacIntosh, B. J., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-0985-2 · Cited by 117 · see citing works
Kelly, C. J., Christiaens, D., Batalle, D., Makropoulos, A., Cordero‐Grande, L., Steinweg, J. K., O'Muircheartaigh, J., Khan, H., Lee, G., Victor, S., et al. (2019) · Journal of the American Heart Association · doi:10.1161/jaha.118.009893 · Cited by 72 · see citing works
Dong, J. W., Jelescu, I. O., Ades-Aron, B., Novikov, D. S., Friedman, K., Babb, J. S., Osorio, R. S., Galvin, J. E., Shepherd, T. M., & Fieremans, E. (2020) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2020.01.009 · Cited by 70 · see citing works
Progressive agrammatic aphasia without apraxia of speech as a distinct syndrome
Tetzloff, K. A., Duffy, J. R., Clark, H. M., Utianski, R. L., Strand, E. A., Machulda, M. M., Botha, H., Martin, P. R., Schwarz, C. G., Senjem, M. L., et al. (2019) · Brain · doi:10.1093/brain/awz157 · Cited by 55 · see citing works
Surova, Y., Lampinen, B., Nilsson, M., Lätt, J., Hall, S., Widner, H., study, S. B., van Westen, D., & Hansson, O. (2016) · PLOS ONE · doi:10.1371/journal.pone.0157755 · Cited by 51 · see citing works
White matter biomarkers from fast protocols using axially symmetric diffusion kurtosis imaging
Hansen, B., Khan, A. R., Shemesh, N., Lund, T. E., Sangill, R., Eskildsen, S. F., Østergaard, L., & Jespersen, S. N. (2017) · NMR in Biomedicine · doi:10.1002/nbm.3741 · Cited by 46 · see citing works
Ianuş, A., Carvalho, J., Fernandes, F. F., Cruz, R., Chavarrias, C., Palombo, M., & Shemesh, N. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119135 · Cited by 40 · see citing works
Zarkali, A., McColgan, P., Leyland, L. A., Lees, A. J., & Weil, R. S. (2022) · Journal of Neurology, Neurosurgery & Psychiatry · doi:10.1136/jnnp-2021-326630 · Cited by 32 · see citing works
Maternal depressive symptoms, neonatal white matter, and toddler social-emotional development
Lautarescu, A., Bonthrone, A. F., Pietsch, M., Batalle, D., Cordero-Grande, L., Tournier, J.-D., Christiaens, D., Hajnal, J. V., Chew, A., Falconer, S., et al. (2022) · Translational Psychiatry · doi:10.1038/s41398-022-02073-y · Cited by 29 · see citing works
Chung, S., Wang, X., Fieremans, E., Rath, J. F., Amorapanth, P., Foo, F.-Y. A., Morton, C. J., Novikov, D. S., Flanagan, S. R., & Lui, Y. W. (2019) · American Journal of Neuroradiology · doi:10.3174/ajnr.a6146 · Cited by 31 · see citing works
Callow, D. D., Won, J., Pena, G. S., Jordan, L. S., Arnold-Nedimala, N. A., Kommula, Y., Nielson, K. A., & Smith, J. C. (2021) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2021.645258 · Cited by 27 · see citing works
Raven, E. P., Veraart, J., Kievit, R. A., Genc, S., Ward, I. L., Hall, J., Cunningham, A., Doherty, J., van den Bree, M. B. M., & Jones, D. K. (2023) · Molecular Psychiatry · doi:10.1038/s41380-023-02178-w · Cited by 21 · see citing works
D'Mello, A. M., Frosch, I. R., Meisler, S. L., Grotzinger, H., Perrachione, T. K., & Gabrieli, J. D. E. (2023) · The Journal of Neuroscience · doi:10.1523/jneurosci.0608-22.2023 · Cited by 14 · see citing works
Nguyen‐Duc, J., de Riedmatten, I., Spencer, A. P. C., Perot, J., Olszowy, W., & Jelescu, I. (2025) · Human Brain Mapping · doi:10.1002/hbm.70110 · Cited by 11 · see citing works
Scattered slice shard reconstruction for motion correction in multi-shell diffusion MRI
Christiaens, D., Cordero-Grande, L., Pietsch, M., Hutter, J., Price, A. N., Hughes, E. J., Vecchiato, K., Deprez, M., Edwards, A. D., Hajnal, J. V., et al. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2020.117437 · Cited by 4 · see citing works
- Authors
- Kellner, E., Dhital, B., Kiselev, V. G., & Reisert, M.
- Affiliations
- University Medical Center Freiburg (DE)
- German Cancer Research Center (DE)
- Corresponding author
- Kellner, Elias
- Venue
- Magnetic Resonance in Medicine
- Publisher
- Wiley
- Published
- 2015-11-24
- Volume
- 76
- Issue
- 5
- Pages
- 1574-1581
- ISSN
- 0740-3194 (ISSN-L)
- 1522-2594
- OpenAlex
- W1895268124
- Cited by
- 1,478
- References
- 0
- Citations by year
- 2026: 198 · 2025: 286 · 2024: 207 · 2023: 182 · 2022: 186 · 2021: 171 · 2020: 117 · 2019: 69 · 2018: 43 · 2017: 13 · 2016: 6
- FWCI
- 16.75
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Magnetic Resonance in Medicine (publishedVersion)
- PubMed (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Funders
- Deutsche Forschungsgemeinschaft (DFG) (RE 3286/2-1, KI1089/3-2)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image and Signal Denoising Methods
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Medical Imaging Techniques and Applications
- Keywords
- Gibbs phenomenon, sinc function, zero crossings, image smoothing
- MeSH terms
- Algorithms, Fourier Analysis, Image Enhancement, Image Interpretation, Computer-Assisted, Magnetic Resonance Imaging, Signal Processing, Computer-Assisted, Artifacts, Phantoms, Imaging
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
