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Please use this identifier to cite or link to this item:
http://hdl.handle.net/1974/2603
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| 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 Theses & Dissertations
Computing Graduate Theses
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