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dc.contributor.authorKoslowski, Brianen
dc.date2010-05-28 11:17:31.934
dc.date.accessioned2010-05-28T18:30:45Z
dc.date.available2010-05-28T18:30:45Z
dc.date.issued2010-05-28T18:30:45Z
dc.identifier.urihttp://hdl.handle.net/1974/5689
dc.descriptionThesis (Master, Computing) -- Queen's University, 2010-05-28 11:17:31.934en
dc.description.abstractComputer assisted surgery uses a collection of different techniques including but not limited to: CT-guided, fluoroscopy-guided, and ultrasound-guided imaging which allows medical staff to view bony anatomy of a patient in relation to surgical tools on a computer screen. By providing this visual data to surgeons less invasive surgeries can be performed on a patient's fractured scaphoid. The data required for a surgeon to perform a minimally invasive surgery while looking only at a computer screen, and not directly at a patient's anatomy, will be provided by CT and ultrasound data. We will discuss how ultrasound and CT data can be used together to allow a minimally invasive surgery of the scaphoid to be performed. In this thesis we will explore two techniques of registering segmented ultrasound images to CT data; an Iterative Closest Point (ICP) approach, and an Unscented Kalman Filter-based Registration (UKF). We use two different ultrasound segmentation methods; a semi-automatic segmentation, and a Bayesian segmentation technique. The segmented ultrasound data is then registered to a CT volume. The success or failure of the registrations is measured by the error calculated in mapping the corresponding land- marks to one another and calculating the target registration error. The results show that the Unscented Kalman Filter-based registration using the Bayesian segmentation of ultrasound images has the least registration error, and has the most robustness to error in initial alignment of the two data sets.en
dc.language.isoengen
dc.relation.ispartofseriesCanadian thesesen
dc.rightsThis publication is made available by the authority of the copyright owner solely for the purpose of private study and research and may not be copied or reproduced except as permitted by the copyright laws without written authority from the copyright owner.en
dc.subjectFeature-Based Registrationen
dc.subjectUltrasounden
dc.subjectCTen
dc.subjectScaphoiden
dc.titleFeature Based Registration of Ultrasound and CT Data of a Scaphoiden
dc.typethesisen
dc.description.degreeM.Sc.en
dc.contributor.supervisorAbolmaesumi, Purangen
dc.contributor.departmentComputingen
dc.degree.grantorQueen's University at Kingstonen


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