Assessment of Deep Learning-Based Triage Application for Acute Ischemic Stroke on Brain MRI in the ER.

Journal: Academic radiology
Published Date: Jun 21, 2024

Abstract

RATIONALE AND OBJECTIVES: To assess a deep learning application (DLA) for acute ischemic stroke (AIS) detection on brain magnetic resonance imaging (MRI) in the emergency room (ER) and the effect of T2-weighted imaging (T2WI) on its performance.

Authors

  • Jimin Kim
    Department of Dental Anesthesiology, Seoul National University Dental Hospital, Seoul, Korea.
  • Se Won Oh
    Department of Radiology, Eunpyeong St. Mary's Hospital, The Catholic University of Korea College of Medicine, Seoul 03312, Korea. Electronic address: oasis1979@gmail.com.
  • Ha Young Lee
    Department of Radiology, Eunpyeong St. Mary's Hospital, The Catholic University of Korea College of Medicine, Seoul 03312, Korea.
  • Moon Hyung Choi
    Department of Radiology, Eunpyeong St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
  • Heiko Meyer
    Siemens Healthcare, Application Development, Erlangen, Germany.
  • Stefan Huwer
    Magnetic Resonance, Siemens Healthineers, Erlangen, Germany.
  • Gengyan Zhao
    Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA.
  • Eli Gibson
    Wellcome / EPSRC Centre for Interventional and Surgical Sciences (WEISS), University College London, UK; Centre for Medical Image Computing (CMIC), Departments of Medical Physics & Biomedical Engineering and Computer Science, University College London, UK.
  • Dongyeob Han
    Siemens Healthineers Ltd., Seoul, Republic of Korea.

Keywords

External Resources

Popular Topics
Recent Journals