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Abstract #3099

Two-stage denoising of CEST MRI data by principal component analysis of spectral groups

Johannes Breitling1, Steffen Goerke1, Mark E. Ladd1, Peter Bachert1, and Andreas Korzowski1
1German Cancer Research Center (DKFZ), Heidelberg, Germany

In this study a novel method for the denoising of CEST MRI data is presented, combining the formation of subsets of similar spectra and the subsequent application of a principal component analysis. Exploiting only the subtle spectral differences of these reduced datasets – as opposed to using all spectra for the analysis – allows for a better identification and isolation of the obscured underlying spectral features. The proposed denoising resulted in an SNR gain by approximately a factor of four compared to the noisy initial data and an additional 14% compared to the conventional principal component analysis denoising.

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