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  Adaptive denoising for chemical exchange saturation transfer MR imaging

Breitling, J., Deshmane, A., Goerke, S., Korzowski, A., Herz, K., Ladd, M., et al. (2019). Adaptive denoising for chemical exchange saturation transfer MR imaging. NMR in Biomedicine, Epub ahead. doi:10.1002/nbm.4133.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0004-6D97-8 Version Permalink: http://hdl.handle.net/21.11116/0000-0004-6D98-7
Genre: Journal Article

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Breitling, J, Author
Deshmane, A1, 2, Author              
Goerke, S, Author
Korzowski, A, Author
Herz, K1, 2, Author              
Ladd, ME, Author
Scheffler, K1, 2, Author              
Bachert, P, Author
Zaiss, M1, 2, Author              
Affiliations:
1Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497796              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              

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 Abstract: High image signal–to–noise ratio (SNR) is required to reliably detect the inherently small chemical exchange saturation transfer (CEST) effects in vivo. In this study, it was demonstrated that identifying spectral redundancies of CEST data by principal component analysis (PCA) in combination with an appropriate data–driven extraction of relevant information can be used for an effective and robust denoising of CEST spectra. The relationship between the number of relevant principal components and SNR was studied on fitted in vivo Z–spectra with artificially introduced noise. Three different data–driven criteria to automatically determine the optimal number of necessary components were investigated. In addition, these criteria facilitate straightforward assessment of data quality that could provide guidance for CEST MR protocols in terms of SNR. Insights were applied to achieve a robust denoising of highly sampled low power Z–spectra of the human brain at 3 and 7 T. The median criterion provided the best estimation for the optimal number of components consistently for all three investigated artificial noise levels. Application of the denoising technique to in vivo data revealed a considerable increase in image quality for the amide and rNOE contrast with a considerable SNR gain. At 7 T the denoising capability was quantified to be comparable or even superior to an averaging of six measurements. The proposed denoising algorithm enables an efficient and robust denoising of CEST data by combining PCA with appropriate data–driven truncation criteria. With this generally applicable technique at hand, small CEST effects can be reliably detected without the need for repeated measurements.

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 Dates: 2019-07
 Publication Status: Published online
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 Identifiers: DOI: 10.1002/nbm.4133
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Title: NMR in Biomedicine
Source Genre: Journal
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Publ. Info: London : Heyden & Son
Pages: - Volume / Issue: Epub ahead Sequence Number: - Start / End Page: - Identifier: ISSN: 0952-3480
CoNE: https://pure.mpg.de/cone/journals/resource/954925574973