Compensation for respiratory motion-induced signal loss and phase corruption in free-breathing self-navigated cine DENSE using deep learning.

Journal: Magnetic resonance in medicine
Published Date: May 1, 2023

Abstract

PURPOSE: To introduce a model that describes the effects of rigid translation due to respiratory motion in displacement encoding with stimulated echoes (DENSE) and to use the model to develop a deep convolutional neural network to aid in first-order respiratory motion compensation for self-navigated free-breathing cine DENSE of the heart.

Authors

  • Mohamad Abdi
    Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA.
  • Kenneth C Bilchick
    Department of Medicine, University of Virginia Health System, Charlottesville, VA, USA.
  • Frederick H Epstein
    Department of Biomedical Engineering, University of Virginia, Health System, Box 800759, Charlottesville, VA, 22908, USA. fhe6b@virginia.edu.

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