Open AccessReal-time corneal segmentation and 3D needle tracking in intrasurgical OCT
Author(s) -
Brenton Keller,
Mark Draelos,
Gao Tang,
Sina Farsiu,
Anthony N. Kuo,
Kris Hauser,
Joseph A. Izatt
Publication year - 2018
Publication title -
biomedical optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.362
H-Index - 86
ISSN - 2156-7085
DOI - 10.1364/boe.9.002716
Subject(s) - optical coherence tomography , microscope , artificial intelligence , segmentation , computer vision , computer science , biomedical engineering , medicine , optics , ophthalmology , pathology , physics
Ophthalmic procedures demand precise surgical instrument control in depth, yet standard operating microscopes supply limited depth perception. Current commercial microscope-integrated optical coherence tomography partially meets this need with manually-positioned cross-sectional images that offer qualitative estimates of depth. In this work, we present methods for automatic quantitative depth measurement using real-time, two-surface corneal segmentation and needle tracking in OCT volumes. We then demonstrate these methods for guidance of ex vivo deep anterior lamellar keratoplasty (DALK) needle insertions. Surgeons using the output of these methods improved their ability to reach a target depth, and decreased their incidence of corneal perforations, both with statistical significance. We believe these methods could increase the success rate of DALK and thereby improve patient outcomes.