A Deep Learning Algorithm to Identify Anatomical Landmarks on Computed Tomography of the Temporal Bone.

Journal: The journal of international advanced otology
Published Date: Oct 1, 2023

Abstract

BACKGROUND: Petrous temporal bone cone-beam computed tomography scans help aid diagnosis and accurate identification of key operative landmarks in temporal bone and mastoid surgery. Our primary objective was to determine the accuracy of using a deep learning convolutional neural network algorithm to augment identification of structures on petrous temporal bone cone-beam computed tomography. Our secondary objective was to compare the accuracy of convolutional neural network structure identification when trained by a senior versus junior clinician.

Authors

  • Zubair Hasan
    University of Sydney, Faculty of Medicine and Health, New South Wales, Australia; Department of Otolaryngology - Head and Neck Surgery, Westmead Hospital, New South Wales, Australia.
  • Seraphina Key
    Monash University, Faculty of Medicine, Nursing and Health Sciences, Victoria, Australia.
  • Michael Lee
    University of Sydney, Faculty of Medicine and Health, New South Wales, Australia.
  • Fiona Chen
    Department of Diagnostic Imaging, Rhode Island Hospital, Providence, RI, USA.
  • Layal Aweidah
    Department of Otolaryngology - Head and Neck Surgery, Westmead Hospital, New South Wales, Australia.
  • Aaron Esmaili
    Department of Otolaryngology, Sir Charles Gairdner Hospital, Nedlands, Australia.
  • Raymond Sacks
    Department of Otolaryngology, Head and Neck Surgery, Concord General Hospital, University of Sydney, Sydney, Australia.
  • Narinder Singh
    Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia.

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