Optimization of deep learning-based denoising for arterial spin labeling: Effects of averaging and training strategies.

Journal: Magnetic resonance in medicine
Published Date: Aug 5, 2025

Abstract

PURPOSE: Systematic study of the effects of averaging and other relevant training strategies in deep learning (DL)-based denoising is required to optimize such processing pipelines for improving the quality of arterial spin labeling (ASL) images.

Authors

  • Jia Guo
    Department of Radiology, Stanford University, Stanford, CA, USA.
  • Arun Sharma
    Translational Bioinformatics Group, International Centre for Genetic Engineering and Biotechnology, Aruna Asaf Ali Marg, New Delhi, India.
  • Greg Zaharchuk
    Stanford University, Stanford CA 94305, USA.
  • Hossein Rahimzadeh
    Department of Bioengineering, University of California Riverside, Riverside, California, USA.
  • Naveed Ilyas
    Department of Biomedical Science and Engineering, Gwangju Institute of Science and Technology (GIST), Gwangju, 61005, Republic of Korea.

Keywords

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