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Design and validation of a large, open-source library of rigid-body markers for surgical navigation (Conference Presentation)
Author(s): Alisa J. V. Brown; Ali Uneri; Tharindu De Silva; Jeffrey H. Siewerdsen

Paper Abstract

Purpose: Rigid-body markers are a common component of surgical tracking systems, but there is a limited number of commercially available, valid marker designs, presenting a limitation to researchers developing novel navigation systems. This work presents the development and validation of a large, open-source library of rigid-body markers for passive marker tracking systems. Methods: Ten groups of rigid-body tool designs were generated according to an algorithm based on intra- and inter-body design constraints. Validation studies were performed using a Polaris Vicra tracker (NDI) to compare the performance of each rigid body to a standard commercially available reference tool, including: tool-tip pivot calibration; measurement of fiducial registration error (FRE) on a computer-controlled bench; and measurement of target registration error (TRE) on a CT head phantom. Results: The resulting library of rigid-body markers includes 10 groups - one with 10 markers and nine with 6. Each group includes one tool geometrically equivalent to a common commercially available rigid body (NDI #8700339)1. Pivot tests showed tool-tip calibration ~0.4 mm, indistinguishable from the reference tool. FRE was ~0.15 mm, again meeting that of the reference. TRE measurements showed registration in a CT head phantom with error ~0.95 mm, equivalent to that of the reference. Conclusions: The library of custom tool designs perform equivalently to common, commercially available reference markers and present a multitude of distinct, simultaneously trackable rigid-body marker designs. The library is available as open source CAD files suitable to 3D printing by researchers in image-guided surgery and other applications.

Paper Details

Date Published: 14 March 2018
PDF
Proc. SPIE 10576, Medical Imaging 2018: Image-Guided Procedures, Robotic Interventions, and Modeling, 105761J (14 March 2018); doi: 10.1117/12.2293823
Show Author Affiliations
Alisa J. V. Brown, Johns Hopkins Univ. (United States)
Ali Uneri, Johns Hopkins Univ. (United States)
Tharindu De Silva, Johns Hopkins Univ. (United States)
Jeffrey H. Siewerdsen, Johns Hopkins Univ. (United States)


Published in SPIE Proceedings Vol. 10576:
Medical Imaging 2018: Image-Guided Procedures, Robotic Interventions, and Modeling
Baowei Fei; Robert J. Webster, Editor(s)

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