Deep Learning-Based Software Improves Clinicians' Detection Sensitivity of Aneurysms on Brain TOF-MRA.

Journal: AJNR. American journal of neuroradiology
Published Date:

Abstract

BACKGROUND AND PURPOSE: The detection of cerebral aneurysms on MRA is a challenging task. Recent studies have used deep learning-based software for automated detection of aneurysms on MRA and have reported high performance. The purpose of this study was to evaluate the incremental value of using deep learning-based software for the detection of aneurysms on MRA by 2 radiologists, a neurosurgeon, and a neurologist.

Authors

  • B Sohn
    From the Department of Radiology, Research Institute of Radiological Science and Center for Clinical Imaging Data Science (I.S., H.K., S.S.A., B.S., S.-K.L.), Yonsei University College of Medicine, Seoul, Korea.
  • K-Y Park
    Department of Neurosurgery (K.-Y.P.), Yonsei University College of Medicine, Seoul, South Korea.
  • J Choi
    School of Mechanical Engineering, Yonsei University, Seoul, Republic of Korea.
  • J H Koo
    From the Department of Radiology (B.S., J.C., J.H.K., K.H., B.J., S.Y.W., J.C., H.S.C., S.-K.L.), Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, South Korea.
  • K Han
    From the Department of Radiology (B.S., J.C., J.H.K., K.H., B.J., S.Y.W., J.C., H.S.C., S.-K.L.), Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, South Korea.
  • B Joo
    From the Department of Radiology (B.S., J.C., J.H.K., K.H., B.J., S.Y.W., J.C., H.S.C., S.-K.L.), Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, South Korea.
  • S Y Won
    From the Department of Radiology (B.S., J.C., J.H.K., K.H., B.J., S.Y.W., J.C., H.S.C., S.-K.L.), Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, South Korea.
  • J Cha
    From the Department of Radiology (B.S., J.C., J.H.K., K.H., B.J., S.Y.W., J.C., H.S.C., S.-K.L.), Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, South Korea.
  • H S Choi
    From the Department of Radiology (B.S., J.C., J.H.K., K.H., B.J., S.Y.W., J.C., H.S.C., S.-K.L.), Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, South Korea chlgustjr1@gmail.com.
  • S-K Lee
    From the Department of Radiology, Research Institute of Radiological Science and Center for Clinical Imaging Data Science (I.S., H.K., S.S.A., B.S., S.-K.L.), Yonsei University College of Medicine, Seoul, Korea.