Feature Tracking and Segmentation in Real Time via Deep Learning in Vitreoretinal Surgery: A Platform for Artificial Intelligence-Mediated Surgical Guidance.

Journal: Ophthalmology. Retina
Published Date: Mar 1, 2023

Abstract

PURPOSE: This study investigated whether a deep-learning neural network can detect and segment surgical instrumentation and relevant tissue boundaries and landmarks within the retina using imaging acquired from a surgical microscope in real time, with the goal of providing image-guided vitreoretinal (VR) microsurgery.

Authors

  • Rogerio Garcia Nespolo
    Department of Ophthalmology and Visual Sciences - Illinois Eye and Ear Infirmary, University of Illinois at Chicago, Chicago, Illinois; Richard and Loan Hill Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, Illinois.
  • Darvin Yi
    Stanford University, Department of Radiology, Stanford, CA.
  • Emily Cole
    Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, Oregon.
  • Daniel Wang
    Department of Ophthalmology and Visual Sciences - Illinois Eye and Ear Infirmary, University of Illinois at Chicago, Chicago, Illinois.
  • Alexis Warren
    Department of Ophthalmology and Visual Sciences - Illinois Eye and Ear Infirmary, University of Illinois at Chicago, Chicago, Illinois.
  • Yannek I Leiderman
    Department of Ophthalmology and Visual Sciences - Illinois Eye and Ear Infirmary, University of Illinois at Chicago, Chicago, Illinois; Richard and Loan Hill Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, Illinois. Electronic address: yannek@uic.edu.

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