Using an artificial neural network for fast mapping of the oxygen extraction fraction with combined QSM and quantitative BOLD.

Journal: Magnetic resonance in medicine
PMID: 31273828

Abstract

PURPOSE: To apply an artificial neural network (ANN) for fast and robust quantification of the oxygen extraction fraction (OEF) from a combined QSM and quantitative BOLD analysis of gradient echo data and to compare the ANN to a traditional quasi-Newton (QN) method for numerical optimization.

Authors

  • Simon Hubertus
    Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
  • Sebastian Thomas
    Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
  • Junghun Cho
    Department of Biomedical Engineering, Cornell University, Ithaca, New York.
  • Shun Zhang
    Department of Radiology, Weill Cornell Medical College, New York, New York.
  • Yi Wang
    Department of Neurology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, China.
  • Lothar Rudi Schad
    Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.

Keywords

External Resources

Popular Topics
Recent Journals