Deep Learning-Enhanced Parallel Imaging and Simultaneous Multislice Acceleration Reconstruction in Knee MRI.

Journal: Investigative radiology
Published Date: Jul 1, 2022

Abstract

OBJECTIVES: This study aimed to examine various combinations of parallel imaging (PI) and simultaneous multislice (SMS) acceleration imaging using deep learning (DL)-enhanced and conventional reconstruction. The study also aimed at comparing the diagnostic performance of the various combinations in internal knee derangement and provided a quantitative evaluation of image sharpness and noise using edge rise distance (ERD) and noise power (NP), respectively.

Authors

  • Minwoo Kim
    School of Electronics and Information Engineering, Korea Aerospace University, Goyang-si 10540, Korea. minwoo@kau.kr.
  • Sang-Min Lee
    Department of Orthopedics, Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan, Korea.
  • Chankue Park
    Department of Radiology, Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan, Korea.
  • Dongeon Lee
    From the School of Biomedical Convergence Engineering, College of Information and BioMedical Engineering, Pusan National University.
  • Kang Soo Kim
    Siemens Healthineers Ltd, Seoul.
  • Hee Seok Jeong
    Department of Radiology, Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan, Korea.
  • Shinyoung Kim
    Department of Radiology, Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan.
  • Min-Hyeok Choi
    Department of Preventive and Occupational & Environmental Medicine, Pusan National University Yangsan Hospital, Pusan National University, Yangsan, Korea.
  • Dominik Nickel
    MR Applications Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany.

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