Convolutional Neural Network-Based Deep Learning Engine for Mastoidectomy Instrument Recognition and Movement Tracking.

Journal: Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
PMID: 38520201

Abstract

OBJECTIVE: To develop a convolutional neural network-based computer vision model to recognize and track 2 mastoidectomy surgical instruments-the drill and the suction-irrigator-from intraoperative video recordings of mastoidectomies.

Authors

  • Mallory J Raymond
    Department of Otolaryngology-Head and Neck Surgery, Medical University of South Carolina, Jacksonville, USA.
  • Biswajit Biswal
    Computer Science and Mathematics, South Carolina State University, Orangeburg, South Carolina, USA.
  • Royal M Pipaliya
    Department of Otolaryngology-Head and Neck Surgery, Medical University of South Carolina, Jacksonville, USA.
  • Mark A Rowley
    Department of Otolaryngology-Head and Neck Surgery, Medical University of South Carolina, Jacksonville, USA.
  • Ted A Meyer
    Department of Otolaryngology-Head and Neck Surgery, Medical University of South Carolina, Jacksonville, USA.

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