Comparison of deep learning-based reconstruction of PROPELLER Shoulder MRI with conventional reconstruction.

Journal: Skeletal radiology
Published Date:

Abstract

OBJECTIVE: To compare the image quality and agreement among conventional and accelerated periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) MRI with both conventional reconstruction (CR) and deep learning-based reconstruction (DLR) methods for evaluation of shoulder.

Authors

  • Seok Hahn
    Department of Radiology, Inje University College of Medicine, Haeundae Paik Hospital, Haeundae-ro 875, Busan, 48108, South Korea.
  • Jisook Yi
    Department of Radiology, Inje University College of Medicine, Haeundae Paik Hospital, Haeundae-ro 875, Busan, 48108, South Korea.
  • Ho-Joon Lee
    Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea.
  • Yedaun Lee
    From the Department of Computer Science, Hanyang University, Seoul, Republic of Korea (K.J.C.); Department of Radiology and Research Institute of Radiology (J.K.J., S.S.L., Y.S.S., W.H.S., H.S.K., J.Y., J.H.K., S.Y.K.) and Department of Diagnostic Pathology (E.S.Y.), Asan Medical Center, University of Ulsan College of Medicine, 88 Olympic-ro 43-gil, Songpa-gu, Seoul 05505, South Korea; Department of Radiology, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea (J.Y.C.); Department of Radiology, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Korea (Y.L.); and Department of Radiology, Hanyang University Medical Center, Hanyang University School of Medicine, Seoul, Korea (B.K.K.).
  • Joonsung Lee
    From the Department of Radiology and Research Institute of Radiology (M.K., H.S.K., H.J.K., J.E.P., S.J.K.), Department of Clinical Epidemiology and Biostatistics (S.Y.P.), and Department of Neurosurgery (Y.H.K.), University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-ro 43-gil, Songpa-Gu, Seoul 05505, South Korea; GE Healthcare Korea, Seoul, Korea (J.L.); GE Healthcare Canada, Calgary, Canada (M.R.L.); and Department of Radiology, University of Calgary, Calgary, Canada (M.R.L.).
  • Xinzeng Wang
    MR Clinical Solutions and Research Collaborations, GE Healthcare, Houston, TX, USA.
  • Maggie Fung
    GE Healthcare, Waukesha, Wisconsin, USA.