Physics-informed deep learning approach to quantification of human brain metabolites from magnetic resonance spectroscopy data.

Journal: Computers in biology and medicine
Published Date:

Abstract

PURPOSE: While the recommended analysis method for magnetic resonance spectroscopy data is linear combination model (LCM) fitting, the supervised deep learning (DL) approach for quantification of MR spectroscopy (MRS) and MR spectroscopic imaging (MRSI) data recently showed encouraging results; however, supervised learning requires ground truth fitted spectra, which is not practical. Moreover, this work investigates the feasibility and efficiency of the LCM-based self-supervised DL method for the analysis of MRS data.

Authors

  • Amirmohammad Shamaei
    Institute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czech Republic.
  • Jana Starcukova
    Institute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czech Republic.
  • Zenon Starcuk
    Institute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czech Republic.