Deep Learning-Based Detection of Intracranial Aneurysms in 3D TOF-MRA.

Journal: AJNR. American journal of neuroradiology
Published Date: Dec 20, 2018

Abstract

BACKGROUND AND PURPOSE: The rupture of an intracranial aneurysm is a serious incident, causing subarachnoid hemorrhage associated with high fatality and morbidity rates. Because the demand for radiologic examinations is steadily growing, physician fatigue due to an increased workload is a real concern and may lead to mistaken diagnoses of potentially relevant findings. Our aim was to develop a sufficient system for automated detection of intracranial aneurysms.

Authors

  • T Sichtermann
    From the Department of Diagnostic and Interventional Neuroradiology (T.S., A.F., R.S., N.T., J.F., M.W.), University Hospital RWTH Aachen, Aachen, Germany tsichtermann@ukaachen.de.
  • A Faron
    From the Department of Diagnostic and Interventional Neuroradiology (T.S., A.F., R.S., N.T., J.F., M.W.), University Hospital RWTH Aachen, Aachen, Germany.
  • R Sijben
    From the Department of Diagnostic and Interventional Neuroradiology (T.S., A.F., R.S., N.T., J.F., M.W.), University Hospital RWTH Aachen, Aachen, Germany.
  • N Teichert
    From the Department of Diagnostic and Interventional Neuroradiology (T.S., A.F., R.S., N.T., J.F., M.W.), University Hospital RWTH Aachen, Aachen, Germany.
  • J Freiherr
    From the Department of Diagnostic and Interventional Neuroradiology (T.S., A.F., R.S., N.T., J.F., M.W.), University Hospital RWTH Aachen, Aachen, Germany.
  • M Wiesmann
    From the Department of Diagnostic and Interventional Neuroradiology (T.S., A.F., R.S., N.T., J.F., M.W.), University Hospital RWTH Aachen, Aachen, Germany.

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