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Proceedings Paper

Stochastic rank correlation for slice-to-volume registration of fluoroCT/CT imaging
Author(s): Wolfgang Birkfellner; Michael Figl; Helmar Bergmann
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Paper Abstract

Slice-to-Volume registration is a special case of 2D/3D registration where a single slice obtained using a stationary scanner geometry is registered to a pre-interventional diagnostic volume scan. Examples include interventional magnetic resonance imaging (IMRI) or fluoroscopic computed tomography (CT). In a recent study in FluoroCT/ CT registration, we have shown that conventional cross correlation (CC), together with repeated use of conventional local optimization algorithms, provides an optimum measure for slice-to-volume registration for monoenergetic CT imaging data. If the required linear relationship between corresponding pixel pairs is offended (e. g. by using X-rays of different energy or by varying detector characteristics), CC becomes an unreliable measure of image similarity. A more general merit function like normalized mutual information (NMI) serves better in such a case but is stricken with local minima caused by sparse population of joint histograms. We present a novel merit function for 2D/3D registration named stochastic rank correlation (SRC), which is well-suited for intramodal dual-energy imaging. A first evaluation of SRC is given on a set of simulated and clinical FluoroCT/CT scan image data sets.

Paper Details

Date Published: 22 March 2007
PDF: 5 pages
Proc. SPIE 6509, Medical Imaging 2007: Visualization and Image-Guided Procedures, 650937 (22 March 2007); doi: 10.1117/12.711394
Show Author Affiliations
Wolfgang Birkfellner, Medical Univ. Vienna (Austria)
Michael Figl, Imperial College London (United Kingdom)
Helmar Bergmann, Medical Univ. Vienna (Austria)


Published in SPIE Proceedings Vol. 6509:
Medical Imaging 2007: Visualization and Image-Guided Procedures
Kevin R. Cleary; Michael I. Miga, Editor(s)

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