Ms. Stephanie Williams Profile

Stephanie Williams

at Univ Health Network

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Proceedings Article | 6 March 2023 Presentation + Paper

Evaluation of AR image tracking for AR-guided surgical applications

Jimmy Qiu, Trinette Wright, Daniel Lin, Stephanie Williams, Stefan Hofer, Blake Murphy

Proceedings Volume 12368, 1236802 (2023) https://doi.org/10.1117/12.2648490

KEYWORDS: Augmented reality, 3D tracking, Optical tracking, Navigation systems, Image registration, 3D printing

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Augmented reality (AR) image tracking may be used in AR-guided surgical applications for real-time guidance and quantitative feedback. With AR-guided applications allowing for broader accessibility compared to specialized systems used in traditional surgical image-guidance, we evaluated the measurement errors of monocular AR image tracking against current gold standard infrared optical and electromagnetic (EM) tracking. A measurement stylus was designed and 3D printed, allowing for monocular AR image tracking using a Logitech C920 camera, infrared optical tracking with Northern Digital Inc. (NDI) Vicra, and EM tracking with NDI Aurora through corresponding sensor attachments. A measurement phantom was also designed and 3D printed, consisting of 3 measurement planes with 81 measurement points in each plane, totaling 243 measurement points across a 16 cm x 16 cm x 18 cm measurement volume. Pivot calibration was performed using random sample consensus (RANSAC) sphere fitting to calculate the offsets between sensor attachments to stylus tip across each tracking system. Measurements of the stylus tip were collected across the measurement phantom for each tracking system. Each system’s fiducial registration error was quantified using the collected tip positions through rigid registration between the tracking system and the designed phantom points from CAD. Fiducial registration errors were 1.19 mm, 0.59 mm, and 0.51 mm for monocular AR, infrared optical, and EM tracking. Monocular AR image tracking presents a cost effective and accessible solution for surgical guidance applications. Errors close to 1 mm may be suitable for scenarios such as surgical simulators in competency-based education and AR-based planning.

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