Segmentation of Chronic Subdural Hematomas Using 3D Convolutional Neural Networks.

Journal: World neurosurgery
Published Date: Apr 1, 2021

Abstract

OBJECTIVE: Chronic subdural hematomas (cSDHs) are an increasingly prevalent neurologic disease that often requires surgical intervention to alleviate compression of the brain. Management of cSDHs relies heavily on computed tomography (CT) imaging, and serial imaging is frequently obtained to help direct management. The volume of hematoma provides critical information in guiding therapy and evaluating new methods of management. We set out to develop an automated program to compute the volume of hematoma on CT scans for both pre- and postoperative images.

Authors

  • Ryan T Kellogg
    Department of Neurological Surgery, University of Washington, Seattle, Washington, USA. Electronic address: rtk4u@virginia.edu.
  • Jan Vargas
    Division of Neurosurgery, Prisma Health, Greenville, South Carolina, USA.
  • Guilherme Barros
    Department of Neurological Surgery, University of Washington, Seattle, Washington, USA.
  • Rajeev Sen
    Department of Neurological Surgery, University of Washington, Seattle, Washington, USA.
  • David Bass
    Department of Neurological Surgery, University of Washington, Seattle, Washington, USA.
  • J Ryan Mason
    Department of Radiology, University of Washington, Seattle, Washington, USA.
  • Michael Levitt
    Department of Neurological Surgery, University of Washington, Seattle, Washington, USA.

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