Unbiased and reproducible liver MRI-PDFF estimation using a scan protocol-informed deep learning method.

Journal: European radiology
Published Date: Nov 5, 2024

Abstract

OBJECTIVE: To estimate proton density fat fraction (PDFF) from chemical shift encoded (CSE) MR images using a deep learning (DL)-based method that is precise and robust to different MR scanners and acquisition echo times (TEs).

Authors

  • Juan P Meneses
    Biomedical Imaging Center, Pontificia Universidad Católica de Chile, Santiago, Chile.
  • Ayyaz Qadir
    Department of Medical Imaging and Radiation Sciences, Monash University, Melbourne, VIC, Australia.
  • Nirusha Surendran
    Department of Medical Imaging and Radiation Sciences, Monash University, Melbourne, VIC, Australia.
  • Cristobal Arrieta
    i-HEALTH Millennium Institute for Intelligent Healthcare Engineering, Santiago, Chile.
  • Cristian Tejos
  • Marcelo E Andia
    i-HEALTH Millennium Institute for Intelligent Healthcare Engineering, Santiago, Chile.
  • Zhaolin Chen
    Monash Biomedical Imaging, Monash University, Building 220, Clayton Campus, 770 Blackburn Rd, Clayton, Victoria, 3168, Australia. zhaolin.chen@monash.edu.
  • Sergio Uribe

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