Automated instrument-tracking for video-rate 4D intraoperative OCT imaging of ophthalmic surgical dynamics

Eric M. Tang; Mohamed T. El-Haddad; Shriji N. Patel; Yuankai K. Tao

doi:10.1117/12.2609010

7 March 2022 Automated instrument-tracking for video-rate 4D intraoperative OCT imaging of ophthalmic surgical dynamics

Eric M. Tang, Mohamed T. El-Haddad, Shriji N. Patel, Yuankai K. Tao

Proceedings Volume PC11948, Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XXVI; PC119480I (2022) https://doi.org/10.1117/12.2609010
Event: SPIE BiOS, 2022, San Francisco, California, United States

Abstract

Intraoperative OCT (iOCT) provides real-time imaging data that can be used to aid clinical decision-making and verify completion of surgical goals. However, video-rate 4D iOCT imaging of surgical dynamics is limited by the need to manually align the OCT field-of-view (FOV) to the region-of-interest, thus significantly impacting surgical workflow. Here, we demonstrate automated instrument-tracking at over 120 Hz. We present video-rate 4D imaging and tracking of 25G internal limiting membrane forceps at 16 volumes/second. The proposed method and improvements will facilitate the broad adoption of iOCT technology by providing real-time volumetric feedback on surgical dynamics and instrument-tissue interactions.

Conference Presentation

Citation Download Citation

Eric M. Tang, Mohamed T. El-Haddad, Shriji N. Patel, and Yuankai K. Tao "Automated instrument-tracking for video-rate 4D intraoperative OCT imaging of ophthalmic surgical dynamics", Proc. SPIE PC11948, Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XXVI, PC119480I (7 March 2022); https://doi.org/10.1117/12.2609010

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KEYWORDS

Optical coherence tomography

Imaging systems

Reflectometry

Coherence (optics)

Convolutional neural networks

Motion estimation

Real time imaging

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