Markerless Augmented Reality Registration for Surgical Guidance: A Multi-Anatomy Clinical Accuracy Study
Yue Yang, Fabian Necker, Christoph Leuze, Michelle Chen, Andrey Finegersh, Jake Lee, Vasu Divi, Bruce Daniel, Brian Hargreaves, Jie Ying Wu, Fred M Baik

TL;DR
This study develops and evaluates a markerless augmented reality registration system on a head-mounted display for surgical guidance, achieving sub-5mm accuracy across various anatomies in real surgical settings.
Contribution
It introduces a depth-only, markerless AR registration pipeline with human-in-the-loop initialization and global-to-local registration, validated in clinical surgeries without fiducials.
Findings
Achieved median errors of 3.2 to 5.3 mm across different anatomies.
Validated surface-tracing error metric with high agreement to CT ground truth.
Demonstrated clinical feasibility of AR guidance with near-clinical accuracy thresholds.
Abstract
Purpose: In this paper, we develop and clinically evaluate a depth-only, markerless augmented reality (AR) registration pipeline on a head-mounted display, and assess accuracy across small or low-curvature anatomies in real-life operative settings. Methods: On HoloLens 2, we align Articulated HAnd Tracking (AHAT) depth to Computed Tomography (CT)-derived skin meshes via (i) depth-bias correction, (ii) brief human-in-the-loop initialization, (iii) global and local registration. We validated the surface-tracing error metric by comparing "skin-to-bone" relative distances to CT ground truth on leg and foot models, using an AR-tracked tool. We then performed seven intraoperative target trials (feet x2, ear x3, leg x2) during the initial stage of fibula free-flap harvest and mandibular reconstruction surgery, and collected 500+ data per trial. Results: Preclinical validation showed tight…
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Taxonomy
TopicsAugmented Reality Applications · Surgical Simulation and Training · Reconstructive Surgery and Microvascular Techniques
