title: The Zernike expansion--an example of a merit function for 2D/3D registration based on orthogonal functions.
abstract: Current merit functions for 2D/3D registration usually rely on comparing pixels or small regions of images using some sort of statistical measure. Problems connected to this paradigm the sometimes problematic behaviour of the method if noise or artefacts (for instance a guide wire) are present on the projective image. We present a merit function for 2D/3D registration which utilizes the decomposition of the X-ray and the DRR under comparison into orthogonal Zernike moments; the quality of the match is assessed by an iterative comparison of expansion coefficients. Results in a imaging study on a physical phantom show that--compared to standard cross--correlation the Zernike moment based merit function shows better robustness if histogram content in images under comparison is different, and that time expenses are comparable if the merit function is constructed out of a few significant moments only.
authors.affiliation: Center of Biomedical Engineering and Physics, Medical University Vienna, Austria.
authors.forename: Shuo
authors.initials: S
authors.lastname: Dong
authors.forename: Joachim
authors.initials: J
authors.lastname: Kettenbach
authors.forename: Isabella
authors.initials: I
authors.lastname: Hinterleitner
authors.forename: Helmar
authors.initials: H
authors.lastname: Bergmann
authors.forename: Wolfgang
authors.initials: W
authors.lastname: Birkfellner
mesh_terms: D000465:Algorithms; D021621:Imaging, Three-Dimensional / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D014057:Tomography, X-Ray Computed / Q000379:methods*