Application of a deep learning algorithm for three-dimensional T1-weighted gradient-echo imaging of gadoxetic acid-enhanced MRI in patients at a high risk of hepatocellular carcinoma.

Journal: Abdominal radiology (New York)
Published Date: Dec 14, 2023

Abstract

PURPOSE: To evaluate the efficacy of a vendor-specific deep learning reconstruction algorithm (DLRA) in enhancing image quality and focal lesion detection using three-dimensional T1-weighted gradient-echo images in gadoxetic acid-enhanced liver magnetic resonance imaging (MRI) in patients at a high risk of hepatocellular carcinoma.

Authors

  • Jae Hyun Kim
    Department of Pharmaceutical Chemistry, University of Kansas, Lawrence, Kansas 66047; Macromolecule and Vaccine Stabilization Center, University of Kansas, Lawrence, Kansas 66047.
  • Jeong Hee Yoon
  • Se Woo Kim
    Department of Radiology, Seoul National University Hospital, Seoul, Korea.
  • Junghoan Park
    Department of Radiology, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, South Korea.
  • Seong Hwan Bae
    Department of Radiology, Soonchunhyang University Seoul Hospital, Seoul, Republic of Korea.
  • Jeong Min Lee

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