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Susceptibility source separation from gradient echo data using magnitude decay modeling.

Alexey V DimovThanh D NguyenKelly McCabe GillenMelanie MarcillePascal SpincemailleDavid PittSusan A GauthierYi Wang
Published in: Journal of neuroimaging : official journal of the American Society of Neuroimaging (2022)
Separation of magnetic sources based solely on GRE complex data is feasible by combining magnitude decay rate modeling and phase-based QSM and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:msup><mml:mi>χ</mml:mi> <mml:mo>-</mml:mo></mml:msup> <mml:annotation>${\chi}^{-}$</mml:annotation></mml:semantics> </mml:math> change may serve as a biomarker for myelin recovery or damage in acute MS lesions.
Keyphrases
  • magnetic resonance
  • mass spectrometry
  • magnetic resonance imaging
  • liver failure
  • ms ms
  • machine learning
  • drinking water
  • liquid chromatography
  • single cell