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Please use this identifier to cite or link to this item: http://hdl.handle.net/11375/24552
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dc.contributor.advisorElbestawi, M.A.-
dc.contributor.authorde Villiers, Etienne-
dc.date.accessioned2019-06-17T19:55:08Z-
dc.date.available2019-06-17T19:55:08Z-
dc.date.issued2000-02-
dc.identifier.urihttp://hdl.handle.net/11375/24552-
dc.description.abstractThis thesis outlines the development of an automatic image registration algorithm for matching 3D CT data to 2D fluoroscope X-ray images. The registration is required in order to calculate a transformation for measurements in the 2D image into the 3D representation. The algorithm achieves the registration by generating digitally reconstructed radiographs from the CT data set. The radiographs are 2D projection images, and therefore may be compared with the 2D Fluoroscope images. The X-ray and fluoroscope images were compared using the photometric-based registration algorithm, pseudocorrelation, with X^2 as the distance metric. An automated search algorithm was implemented using the Downhill Simplex of Nelder and Meade. The algorithm was successful in locating the position and orientation of the CT data set for calculating a digitally reconstructed radiograph to match the fluoroscope image. The CT data set was located with a maximum mean position error of 2.4 mm in xy, 4.4 mm in z, and xyz axial rotation within 0.5°. The standard deviation given 1800 random starting locations was 9.3 mm in x, 12.7 mm in y, 16.9 mm in z, xz axial rotation 2.5°, and y axial rotation of 1.9°. The search algorithm was successful in handling gross misalignment, however there were difficulties in convergence once within the vicinity of the global minimum. It is suggested to implement a hybrid search technique, switching to a conjugate gradient search algorithm once in the vicinity of the global minimum. An additional refinement would be a possible change of the distant metric, or the registration algorithm, once within the vicinity of the global minimum. Additional investigation needs to be directed towards testing the algorithm with live fluoroscope and CT data. This is required in order to assess registration performance when comparing different imaging modalities.en_US
dc.language.isoenen_US
dc.subjectautomatic intermodal image registrationen_US
dc.subjectautomatic image registration algorithmen_US
dc.subjectrobotic surgical toolsen_US
dc.subjectalignment of robotic surgical toolsen_US
dc.subjectrobot-assisted surgeryen_US
dc.subjectrobotic surgeryen_US
dc.subjectcomputer-assisted surgeryen_US
dc.subjectmechanical engineeringen_US
dc.subjectintermodal image registrationen_US
dc.subjectimage registrationen_US
dc.titleAutomatic Intermodal Image Registration for Alignment of Robotic Surgical Toolsen_US
dc.typeThesisen_US
dc.contributor.departmentMechanical Engineeringen_US
dc.description.degreetypeThesisen_US
dc.description.degreeMaster of Engineering (ME)en_US
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