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Proceedings Paper

Virtual rigid body: a new optical tracking paradigm in image-guided interventions
Author(s): Alexis Cheng; David S. Lee; Nishikant Deshmukh; Emad M. Boctor
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Paper Abstract

Tracking technology is often necessary for image-guided surgical interventions. Optical tracking is one the options, but it suffers from line of sight and workspace limitations. Optical tracking is accomplished by attaching a rigid body marker, having a pattern for pose detection, onto a tool or device. A larger rigid body results in more accurate tracking, but at the same time large size limits its usage in a crowded surgical workspace. This work presents a prototype of a novel optical tracking method using a virtual rigid body (VRB). We define the VRB as a 3D rigid body marker in the form of pattern on a surface generated from a light source. Its pose can be recovered by observing the projected pattern with a stereo-camera system. The rigid body's size is no longer physically limited as we can manufacture small size light sources. Conventional optical tracking also requires line of sight to the rigid body. VRB overcomes these limitations by detecting a pattern projected onto the surface. We can project the pattern onto a region of interest, allowing the pattern to always be in the view of the optical tracker. This helps to decrease the occurrence of occlusions. This manuscript describes the method and results compared with conventional optical tracking in an experiment setup using known motions. The experiments are done using an optical tracker and a linear-stage, resulting in targeting errors of 0.38mm±0.28mm with our method compared to 0.23mm±0.22mm with conventional optical markers. Another experiment that replaced the linear stage with a robot arm resulted in rotational errors of 0.50±0.31° and 2.68±2.20° and the translation errors of 0.18±0.10 mm and 0.03±0.02 mm respectively.

Paper Details

Date Published: 18 March 2015
PDF: 8 pages
Proc. SPIE 9415, Medical Imaging 2015: Image-Guided Procedures, Robotic Interventions, and Modeling, 94150Y (18 March 2015); doi: 10.1117/12.2081657
Show Author Affiliations
Alexis Cheng, Johns Hopkins Univ. (United States)
David S. Lee, Johns Hopkins Univ. (United States)
Nishikant Deshmukh, Johns Hopkins Univ. (United States)
Emad M. Boctor, Johns Hopkins Univ. (United States)


Published in SPIE Proceedings Vol. 9415:
Medical Imaging 2015: Image-Guided Procedures, Robotic Interventions, and Modeling
Robert J. Webster; Ziv R. Yaniv, Editor(s)

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