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  Denoising high-field multi-dimensional MRI with local complex PCA

Bazin, P.-L., Alkemade, A., van der Zwaag, W., Caan, M., Mulder, M., & Forstmann, B. U. (2019). Denoising high-field multi-dimensional MRI with local complex PCA. Frontiers in Neuroscience, 13: 1066. doi:10.3389/fnins.2019.01066.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0005-5563-C Version Permalink: http://hdl.handle.net/21.11116/0000-0005-7AAF-E
Genre: Journal Article

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 Creators:
Bazin, Pierre-Louis1, 2, Author              
Alkemade, Anneke1, Author
van der Zwaag, Wietske3, Author
Caan, Matthan4, Author
Mulder, Martijn1, 5, Author
Forstmann, Birte U.1, Author              
Affiliations:
1Department of Psychology, University of Amsterdam, the Netherlands, ou_persistent22              
2Department Neurophysics (Weiskopf), MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_2205649              
3Spinoza Centre for Neuroimaging, University of Amsterdam, the Netherlands, ou_persistent22              
4Centre for Brain and Learning, VU University Medical Center, Amsterdam, the Netherlands, ou_persistent22              
5Department of Psychology, Utrecht University, the Netherlands, ou_persistent22              

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Free keywords: Denoising; Ultra-high field MRI; Quantitative MRI; Local PCA; Complex MRI signal
 Abstract: Modern high field and ultra high field magnetic resonance imaging (MRI) experiments routinely collect multi-dimensional data with high spatial resolution, whether multi-parametric structural, diffusion or functional MRI. While diffusion and functional imaging have benefited from recent advances in multi-dimensional signal analysis and denoising, structural MRI has remained untouched. In this work, we propose a denoising technique for multi-parametric quantitative MRI, combining a highly popular denoising method from diffusion imaging, over-complete local PCA, with a reconstruction of the complex-valued MR signal in order to define stable estimates of the noise in the decomposition. With this approach, we show signal to noise ratio (SNR) improvements in high resolution MRI without compromising the spatial accuracy or generating spurious perceptual boundaries.

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Language(s): eng - English
 Dates: 2019-07-152019-09-242019-10-09
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: Peer
 Identifiers: DOI: 10.3389/fnins.2019.01066
Other: eCollection 2019
PMID: 31649500
PMC: PMC6794471
 Degree: -

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Project name : -
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Funding program : VICI Grant
Funding organization : Netherlands Organisation for Scientific Research (NWO)
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Grant ID : -
Funding program : STW grant
Funding organization : Netherlands Organisation for Scientific Research (NWO)

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Title: Frontiers in Neuroscience
  Other : Front Neurosci
Source Genre: Journal
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Publ. Info: Lausanne, Switzerland : Frontiers Research Foundation
Pages: - Volume / Issue: 13 Sequence Number: 1066 Start / End Page: - Identifier: ISSN: 1662-4548
ISSN: 1662-453X
CoNE: https://pure.mpg.de/cone/journals/resource/1662-4548