Stochastic Rank Correlation - A novel merit function for dual energy 2D/3D registration in image-modulated radiation therapy

Abstract

Image-modulated radiation therapy is a field of considerable interest for both the clinical and the research community. By using on-board imaging equipment, patient pose and tumor position can be monitored during the course of therapy. 2D/3D registration is a key technology to achieve this goal. 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.