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Proceedings Paper

Incorporation of a laser range scanner into an image-guided surgical system
Author(s): David Marshall Cash; Tuhin K. Sinha; William C. Chapman; Hiromi Terawaki; Michael I. Miga; Robert L. Galloway
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Paper Abstract

Laser range scanners provide rapid and accurate non-contact methods for acquiring 3D surface data, offering many advntages over other techniques currently available during surgery. The range scanner was incorporated into our image-guided surgery system to augment registration and deformation compensation. A rigid body, embedded with IR diodes, was attached to the scanner for tracking in physical space with an optical localization system. The relationship between the scanner's coordinate system and the tracked rigid body was determined using a calibration phantom. Tracking of the scanner using the calibration phantom resulted in an error of 1.4±0.8 mm. Once tracked, data acquired intraoperatively from the range scanner data is registered with preoperative tomographic volumes using the Iterative Closest Point algorithm. Sensitivity studies were performed to ensure that this algorithm effectively reached a global minimum. In cases where tissue deformation is significant, rigid registrations can lead to inaccuracy during surgical navigation. Methods of non-rigid compensation may be necessary, and an initial study using a linearly elastic finite element model is presented. Differences between intraoperative and preoperative surfaces after rigid registration are used to formulate boundary conditions, and the resulting displacement field deforms the preoperative image volume. To test this protocol, a phantom was built, consisting of fiducial points and a silicone liver model. Range scan and CT data were captured both before and after deforming the organ. The pre-deformed images, after registration and modeling, were compared to post-deformation, although there is a noticeable improvement by implementing the finite element model. To improve accuracy, more elaborate surface registration and deformation compensation strategies will be investigated. To improve accuracy, more elaborate surface registration and deformation compensation strategies will be investigated. The ragne scanner is an innovative, uncumbersome, and relatively inexpensive method of collecting intraoperative data. It has been integrated into our image-guided surgical system and software with virtually no overhead.

Paper Details

Date Published: 30 May 2003
PDF: 12 pages
Proc. SPIE 5029, Medical Imaging 2003: Visualization, Image-Guided Procedures, and Display, (30 May 2003); doi: 10.1117/12.480376
Show Author Affiliations
David Marshall Cash, Vanderbilt Univ. (United States)
Tuhin K. Sinha, Vanderbilt Univ. (United States)
William C. Chapman, Washington Univ. School of Medicine (United States)
Hiromi Terawaki, Duke Univ. (United States)
Michael I. Miga, Vanderbilt Univ. (United States)
Robert L. Galloway, Vanderbilt Univ. (United States)

Published in SPIE Proceedings Vol. 5029:
Medical Imaging 2003: Visualization, Image-Guided Procedures, and Display
Robert L. Galloway, Editor(s)

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