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Please use this identifier to cite or link to this item: http://hdl.handle.net/1974/2603

Title: A System For Computer-Assisted Surgery With Intraoperative CT Imaging
Authors: Oentoro, Anton

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Keywords: Computer-Assisted Surgery
Intraoperative Imaging
Issue Date: 2009
Series/Report no.: Canadian theses
Abstract: Image-guided interventions using intraoperative three-dimensional (3D) imaging can be less cumbersome than systems dependent on preoperative images, especially by needing neither image-to-patient registration nor a lengthy process of segmenting and generating a 3D model. In this dissertation, a method for computer-assisted surgery using direct navigation on intraoperative images is presented. In this system the registration step of a navigated procedure was divided into two stages: preoperative calibration of images to a ceiling-mounted optical tracking system, and intraoperative tracking during acquisition of the 3D image. The preoperative stage used a custom-made multi-modal calibrator that could be optically tracked and also contained fiducial spheres for radiological detection; a robust registration algorithm was used to compensate for the high false-detection rate that arose from the optical light-emitting diodes. Intraoperatively, a tracking device was at- tached to bone models that were also instrumented with radio-opaque spheres; a calibrated pointer was used to contact the latter spheres as a validation. The fiducial registration error of the calibration stage was approximately 0.1 mm with the Innova 3D X-ray fluoroscope and 0.7 mm with the mobile-gantry CT scanner. The target registration error in the valida- tion stage was approximately 1.2 mm with the Innova 3D X-ray fluoroscope and 1.8 mm with the mobile-gantry CT scanner. These findings suggest that direct registration can be a highly accurate means of performing image-guided interventions in a fast, simple manner.
Description: Thesis (Master, Computing) -- Queen's University, 2009-08-17 11:14:03.275
URI: http://hdl.handle.net/1974/2603
Appears in Collections:Queen's Graduate Theses and Dissertations
School of Computing Graduate Theses

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