Automated liver magnetic resonance elastography quality control and liver stiffness measurement using deep learning.

Journal: Abdominal radiology (New York)
Published Date: Mar 15, 2025

Abstract

PURPOSE: Magnetic resonance elastography (MRE) measures liver stiffness for fibrosis staging, but its utility can be hindered by quality control (QC) challenges and measurement variability. The objective of the study was to fully automate liver MRE QC and liver stiffness measurement (LSM) using a deep learning (DL) method.

Authors

  • Efe Ozkaya
  • Heriberto A Nieves-Vazquez
    Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA.
  • Murat Yüce
    Icahn School of Medicine at Mount Sinai Biomedical Engineering and Imaging Institute, New York, USA.
  • Kazuya Yasokawa
    Icahn School of Medicine Mount Sinai, BioMedical Engineering and Imaging Institute, New York, USA.
  • Emre Altinmakas
    Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Jun Ueda
  • Bachir Taouli
    BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA. bachir.taouli@mountsinai.org.

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