This 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 ahieves 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 χ² 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. 4.4mm in z, and xyz axial rotation within 0.5°. The standard deviation given 1800 random starting locations was 9.3mm in x, 12.7mm 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 IVchange 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.