Deep learning-based image reconstruction for the multi-arterial phase images: improvement of the image quality to assess the small hypervascular hepatic tumor on gadoxetic acid-enhanced liver MRI.

Journal: Abdominal radiology (New York)
PMID:

Abstract

PURPOSE: To evaluated the impact of a deep learning (DL)-based image reconstruction on multi-arterial-phase magnetic resonance imaging (MA-MRI) for small hypervascular hepatic masses in patients who underwent gadoxetic acid-enhanced liver MRI.

Authors

  • Su Min Yun
    Department of Radiology, Biomedical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine, Busan, Korea.
  • Seung Baek Hong
    Department of Radiology, Pusan National University Hospital, Busan, Korea.
  • Nam Kyung Lee
    Department of Radiology, Biomedical Research Institute, Pusan National University Hospital, and Pusan National University School of Medicine, Pusan National University, #179, Gudeok-Ro, Seo-Gu, Busan, 49241, Republic of Korea. leenk77@hanmail.net.
  • Suk Kim
    Department of Radiology, Biomedical Research Institute, Pusan National University Hospital, and Pusan National University School of Medicine, Pusan National University, #179, Gudeok-Ro, Seo-Gu, Busan, 49241, Republic of Korea.
  • Yea Hee Ji
    Department of Radiology, Biomedical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine, Busan, Korea.
  • Hyung Il Seo
    Department of Surgery, Pusan National University, Pusan, South Korea.
  • Young Mok Park
    Department of Surgery, Biomedical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine, Busan, Korea.
  • Byeong Gwan Noh
    Department of Surgery, Biomedical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine, Busan, Korea.
  • Marcel Dominik Nickel
    MR Application Predevelopment, Siemens Healthineers AG, Erlangen, Germany.