Optimizing MRF-ASL scan design for precise quantification of brain hemodynamics using neural network regression.

Journal: Magnetic resonance in medicine
Published Date: Jun 1, 2020

Abstract

PURPOSE: Arterial Spin Labeling (ASL) is a quantitative, non-invasive alternative for perfusion imaging that does not use contrast agents. The magnetic resonance fingerprinting (MRF) framework can be adapted to ASL to estimate multiple physiological parameters simultaneously. In this work, we introduce an optimization scheme to increase the sensitivity of the ASL fingerprint. We also propose a regression based estimation framework for MRF-ASL.

Authors

  • Anish Lahiri
    Department of Electrical and Computer Engineering, University of Michigan, Ann Arbor, Michigan, USA.
  • Jeffrey A Fessler
    Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, 48109 USA.
  • Luis Hernandez-Garcia
    Functional MRI Laboratory Biomedical Engineering University of Michigan Ann Arbor MI USA.

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