6 February 2018 Robotic drill guide positioning using known-component 3D–2D image registration
Thomas Yi, Vignesh Ramchandran, Jeffrey H. Siewerdsen, Ali Uneri
Author Affiliations +
Funded by: National Institute of Biomedical Imaging and Bioengineering (NIBIB), National Institutes of Health (NIH), National Institutes of Health, US National Institutes of Health (NIH)
Abstract
A method for x-ray image-guided robotic instrument positioning is reported and evaluated in preclinical studies of spinal pedicle screw placement with the aim of improving delivery of transpedicle K-wires and screws. The known-component (KC) registration algorithm was used to register the three-dimensional patient CT and drill guide surface model to intraoperative two-dimensional radiographs. Resulting transformations, combined with offline hand–eye calibration, drive the robotically held drill guide to target trajectories defined in the preoperative CT. The method was assessed in comparison with a more conventional tracker-based approach, and robustness to clinically realistic errors was tested in phantom and cadaver. Deviations from planned trajectories were analyzed in terms of target registration error (TRE) at the tooltip (mm) and approach angle (deg). In phantom studies, the KC approach resulted in TRE=1.51±0.51  mm and 1.01  deg±0.92  deg, comparable with accuracy in tracker-based approach. In cadaver studies with realistic anatomical deformation, the KC approach yielded TRE=2.31±1.05  mm and 0.66  deg±0.62  deg, with statistically significant improvement versus tracker (TRE=6.09±1.22  mm and 1.06  deg±0.90  deg). Robustness to deformation is attributed to relatively local rigidity of anatomy in radiographic views. X-ray guidance offered accurate robotic positioning and could fit naturally within clinical workflow of fluoroscopically guided procedures.
© 2018 Society of Photo-Optical Instrumentation Engineers (SPIE) 2329-4302/2018/$25.00 © 2018 SPIE
Thomas Yi, Vignesh Ramchandran, Jeffrey H. Siewerdsen, and Ali Uneri "Robotic drill guide positioning using known-component 3D–2D image registration," Journal of Medical Imaging 5(2), 021212 (6 February 2018). https://doi.org/10.1117/1.JMI.5.2.021212
Received: 18 September 2017; Accepted: 4 January 2018; Published: 6 February 2018
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CITATIONS
Cited by 18 scholarly publications and 2 patents.
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KEYWORDS
Robotics

Image registration

Calibration

Optical tracking

Surgery

Radiography

3D modeling

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