Using the robust principal component analysis algorithm to remove RF spike artifacts from MR images. Issue 6 (20th July 2015)
- Record Type:
- Journal Article
- Title:
- Using the robust principal component analysis algorithm to remove RF spike artifacts from MR images. Issue 6 (20th July 2015)
- Main Title:
- Using the robust principal component analysis algorithm to remove RF spike artifacts from MR images
- Authors:
- Campbell‐Washburn, Adrienne E.
Atkinson, David
Nagy, Zoltan
Chan, Rachel W.
Josephs, Oliver
Lythgoe, Mark F.
Ordidge, Roger J.
Thomas, David L. - Abstract:
- Abstract : Purpose: Brief bursts of RF noise during MR data acquisition ("k‐space spikes") cause disruptive image artifacts, manifesting as stripes overlaid on the image. RF noise is often related to hardware problems, including vibrations during gradient‐heavy sequences, such as diffusion‐weighted imaging. In this study, we present an application of the Robust Principal Component Analysis (RPCA) algorithm to remove spike noise from k‐space.Methods : Corrupted k‐space matrices were decomposed into their low‐rank and sparse components using the RPCA algorithm, such that spikes were contained within the sparse component and artifact‐free k‐space data remained in the low‐rank component. Automated center refilling was applied to keep the peaked central cluster of k‐space from misclassification in the sparse component.Results : This algorithm was demonstrated to effectively remove k‐space spikes from four data types under conditions generating spikes: (i) mouse heart T1 mapping, (ii) mouse heart cine imaging, (iii) human kidney diffusion tensor imaging (DTI) data, and (iv) human brain DTI data. Myocardial T1 values changed by 86.1 ± 171 ms following despiking, and fractional anisotropy values were recovered following despiking of DTI data.Conclusion : The RPCA despiking algorithm will be a valuable postprocessing method for retrospectively removing stripe artifacts without affecting the underlying signal of interest. Magn Reson Med 75:2517–2525, 2016. © 2015 The Authors. MagneticAbstract : Purpose: Brief bursts of RF noise during MR data acquisition ("k‐space spikes") cause disruptive image artifacts, manifesting as stripes overlaid on the image. RF noise is often related to hardware problems, including vibrations during gradient‐heavy sequences, such as diffusion‐weighted imaging. In this study, we present an application of the Robust Principal Component Analysis (RPCA) algorithm to remove spike noise from k‐space.Methods : Corrupted k‐space matrices were decomposed into their low‐rank and sparse components using the RPCA algorithm, such that spikes were contained within the sparse component and artifact‐free k‐space data remained in the low‐rank component. Automated center refilling was applied to keep the peaked central cluster of k‐space from misclassification in the sparse component.Results : This algorithm was demonstrated to effectively remove k‐space spikes from four data types under conditions generating spikes: (i) mouse heart T1 mapping, (ii) mouse heart cine imaging, (iii) human kidney diffusion tensor imaging (DTI) data, and (iv) human brain DTI data. Myocardial T1 values changed by 86.1 ± 171 ms following despiking, and fractional anisotropy values were recovered following despiking of DTI data.Conclusion : The RPCA despiking algorithm will be a valuable postprocessing method for retrospectively removing stripe artifacts without affecting the underlying signal of interest. Magn Reson Med 75:2517–2525, 2016. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. … (more)
- Is Part Of:
- Magnetic resonance in medicine. Volume 75:Issue 6(2016)
- Journal:
- Magnetic resonance in medicine
- Issue:
- Volume 75:Issue 6(2016)
- Issue Display:
- Volume 75, Issue 6 (2016)
- Year:
- 2016
- Volume:
- 75
- Issue:
- 6
- Issue Sort Value:
- 2016-0075-0006-0000
- Page Start:
- 2517
- Page End:
- 2525
- Publication Date:
- 2015-07-20
- Subjects:
- spike noise -- robust principal component analysis -- stripe artifact
Nuclear magnetic resonance -- Periodicals
Electron paramagnetic resonance -- Periodicals
616.07548 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1522-2594 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/mrm.25851 ↗
- Languages:
- English
- ISSNs:
- 0740-3194
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5337.798000
British Library DSC - BLDSS-3PM
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- 2240.xml