3D point cloud analysis of structured light registration in computer-assisted navigation in spinal surgeries

Shaurya Gupta; Daipayan Guha; Raphael Jakubovic; Victor X. D. Yang M.D.

doi:10.1117/12.2255907

8 February 2017 3D point cloud analysis of structured light registration in computer-assisted navigation in spinal surgeries

Shaurya Gupta, Daipayan Guha, Raphael Jakubovic, Victor X. D. Yang M.D.

Author Affiliations +

Proceedings Volume 10050, Clinical and Translational Neurophotonics; 100500J (2017) https://doi.org/10.1117/12.2255907
Event: SPIE BiOS, 2017, San Francisco, California, United States

Abstract

Computer-assisted navigation is used by surgeons in spine procedures to guide pedicle screws to improve placement accuracy and in some cases, to better visualize patient’s underlying anatomy. Intraoperative registration is performed to establish a correlation between patient’s anatomy and the pre/intra-operative image. Current algorithms rely on seeding points obtained directly from the exposed spinal surface to achieve clinically acceptable registration accuracy. Registration of these three dimensional surface point-clouds are prone to various systematic errors. The goal of this study was to evaluate the robustness of surgical navigation systems by looking at the relationship between the optical density of an acquired 3D point-cloud and the corresponding surgical navigation error. A retrospective review of a total of 48 registrations performed using an experimental structured light navigation system developed within our lab was conducted. For each registration, the number of points in the acquired point cloud was evaluated relative to whether the registration was acceptable, the corresponding system reported error and target registration error. It was demonstrated that the number of points in the point cloud neither correlates with the acceptance/rejection of a registration or the system reported error. However, a negative correlation was observed between the number of the points in the point-cloud and the corresponding sagittal angular error. Thus, system reported total registration points and accuracy are insufficient to gauge the accuracy of a navigation system and the operating surgeon must verify and validate registration based on anatomical landmarks prior to commencing surgery.

Conference Presentation

Citation Download Citation

Shaurya Gupta, Daipayan Guha, Raphael Jakubovic, and Victor X. D. Yang M.D. "3D point cloud analysis of structured light registration in computer-assisted navigation in spinal surgeries", Proc. SPIE 10050, Clinical and Translational Neurophotonics, 100500J (8 February 2017); https://doi.org/10.1117/12.2255907

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