Deep learning based detection of intracranial aneurysms on digital subtraction angiography: A feasibility study.

Journal: The neuroradiology journal
Published Date: Jul 7, 2020

Abstract

BACKGROUND: Digital subtraction angiography is the gold standard for detecting and characterising aneurysms. Here, we assess the feasibility of commercial-grade deep learning software for the detection of intracranial aneurysms on whole-brain anteroposterior and lateral 2D digital subtraction angiography images.

Authors

  • Nicolin Hainc
    Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Switzerland.
  • Manoj Mannil
  • Vaia Anagnostakou
    Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Switzerland.
  • Hatem Alkadhi
  • Christian Blüthgen
    1 Institut für Diagnostische und Interventionelle Radiologie, Universitätsspital Zürich.
  • Lorenz Wacht
    Department of Radiology, City Hospital Triemli, Zurich, Switzerland.
  • Andrea Bink
    Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Switzerland.
  • Shakir Husain
    Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Switzerland.
  • Zsolt Kulcsár
    Clinical Neuroscience Center, University Hospital Zurich, Zurich, Switzerland.
  • Sebastian Winklhofer
    Department of Neuroradiology, University Hospital Zurich, Zurich, Switzerland.

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