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Miscellaneous 2019

Data-Driven Spectral Feature Extraction in 9.4T CEST MRI data of the human brain

{Model-based extraction of features, e.g. Lorentzian fitting of Z-spectra, in CEST MRI can be limited by the underlying model assumptions. Here we analyzed high spectral resolution Z-spectra acquired at 9.4T in five healthy subjects and one tumor patient using principal component analysis, a purely data-driven statistical procedure. Projection of Z-spectra onto principle components from a group of healthy subjects provides several relevant contrasts which reveal anatomical detail and correlate with Gadolinium uptake signatures in a brain tumor patient.}

Author(s): Schuppert, M and Deshmane, A and Herz, K and Scheffler, K and Zaiss, M
Book Title: ISMRM 27th Annual Meeting & Exhibition
Year: 2019
Bibtex Type: Miscellaneous (misc)
Electronic Archiving: grant_archive

BibTex 

@misc{item_3054624,
  title = {{Data-Driven Spectral Feature Extraction in 9.4T CEST MRI data of the human brain}},
  booktitle = {{ISMRM 27th Annual Meeting \& Exhibition}},
  abstract = {{Model-based extraction of features, e.g. Lorentzian fitting of Z-spectra, in CEST MRI can be limited by the underlying model assumptions. Here we analyzed high spectral resolution Z-spectra acquired at 9.4T in five healthy subjects and one tumor patient using principal component analysis, a purely data-driven statistical procedure. Projection of Z-spectra onto principle components from a group of healthy subjects provides several relevant contrasts which reveal anatomical detail and correlate with Gadolinium uptake signatures in a brain tumor patient.}},
  year = {2019},
  slug = {item_3054624},
  author = {Schuppert, M and Deshmane, A and Herz, K and Scheffler, K and Zaiss, M}
}