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

Mallory J RaymondBiswajit BiswalRoyal M PipaliyaMark A RowleyTed A Meyer

Published in: Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery (2024)

This computer vision model can identify and track the drill and suction-irrigator from videos of intraoperative mastoidectomies performed by residents with excellent precision. It can now be employed to retrospectively study objective mastoidectomy measures of expert and resident surgeons, such as drill and suction-irrigator stroke concentration, economy of motion, speed, and coordination, setting the stage for characterization of objective expectations for safe and efficient mastoidectomies.

Keyphrases

deep learning
convolutional neural network
artificial intelligence
quality improvement
machine learning
atrial fibrillation
patient safety
patients undergoing
blood brain barrier
brain injury