Abstract
One of the main factors that affect the accuracy of intensity-based registration of two-dimensional (2D) X-ray fluoroscopy to three-dimensional (3D) CT data is the similarity measure, which is a criterion function that is used in the registration procedure for measuring the quality of image match. This paper presents a unifying framework for rationally deriving point similarity measures based on Markov random field (MRF) modeling of difference images which are obtained by comparing the reference fluoroscopic images with their associated digitally reconstructed radiographs (DRR’s). The optimal solution is defined as the maximum a posterior (MAP) estimate of the MRF. Three novel point similarity measures derived from this framework are presented. They are evaluated using a phantom and a human cadaveric specimen. Combining any one of the newly proposed similarity measures with a previously introduced spline-based registration scheme, we develop a fast and accurate registration algorithm. We report their capture ranges, converging speeds, and registration accuracies.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Penney, G.P., Weese, J., Little, J.A., Desmedt, P., Hill, D.L.G., Hawkes, D.J.: A comparison of similarity measures for use in 2D-3D medical image registration. IEEE T Med. Imaging 17(4), 586–595 (1998)
Lemieux, L., Jagoe, R., Fish, D.R., Kitchen, N.D., Thomas, D.G.T.: A patient-to-computed-tomography image registration method based on digitally reconstructed radiographs. Med. Phys. 21(11), 1749–1760 (1994)
Buzug, T.M., Weese, J., Fassnacht, C., Lorenz, C.: Image registration: convex weighting functions for histogram-based similarity measures. In: Troccaz, J., Mösges, R., Grimson, W.E.L. (eds.) CVRMed-MRCAS 1997, CVRMed 1997, and MRCAS 1997. LNCS, vol. 1205, pp. 203–212. Springer, Heidelberg (1997)
Weese, J., Buzug, T.M., Lorenz, C., Fassnacht, C.: An approach to 2D/3D registration of a vertebra in 2D X-ray fluoroscopies with 3D CT images. In: Troccaz, J., Mösges, R., Grimson, W.E.L. (eds.) CVRMed-MRCAS 1997, CVRMed 1997, and MRCAS 1997. LNCS, vol. 1205, pp. 119–128. Springer, Heidelberg (1997)
Maes, F., Collignon, A., Vandermeulen, D., Marchal, G., Suetens, P.: Multi-modality image registration by maximization of mutual information. IEEE T Med. Imaging 16(2), 187–198 (1997)
Brown, L.M.G., Boult, T.E.: Registration of planar film radiographs with computed tomography. In: IEEE Proceedings of MMBIA, pp. 42–51 (1996)
Jonić, S., Thévenaz, P., Zheng, G., Nolte, L.-P., Unser, M.: An Optimized Spline-based registration of a 3D CT to a set of C-arm images. International Journal of Biomedical Imaging (in press, 2006)
Jonić, S., Thévenaz, P., Unser, M.: Multiresolution-based registration of a volume to a set of its projection. In: Proceedings of the SPIE International Symposium on Medical Imaging: Image Processing (MI 2003), San Diego CA, USA, Part II, vol. 5032, pp. 1049–1052 (2003)
Li, S.Z.: Markov random field modeling in computer vision. Springer, Heidelberg (1995)
Zheng, G., Zhang, X., Nolte, L.-P.: Assessing spline-based multi-resolution 2D-3D image registration for practical use in surgical guidance. In: Yang, G.-Z., Jiang, T. (eds.) MIAR 2004. LNCS, vol. 3150, pp. 294–301. Springer, Heidelberg (2004)
Zöllei, L., Grimson, E., Norbash, A., Wells, W.: 2D-3D rigid registration of X-ray fluoroscopy and CT images using mutual information and sparsely sampled histogram estimators. In: Proceedings of CVPR 2001, vol. 2, pp. 679–703 (2001)
Russakoff, D.B., Rohlfind, T., Maurer Jr., C.R.: Fast intensity-based 2D-3D image registration of clinical data using lighting fields. In: Proceedings of ICCV 2003, pp. 416–422 (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Zheng, G., Zhang, X., Jonić, S., Thévenaz, P., Unser, M., Nolte, LP. (2006). Point Similarity Measures Based on MRF Modeling of Difference Images for Spline-Based 2D-3D Rigid Registration of X-Ray Fluoroscopy to CT Images. In: Pluim, J.P.W., Likar, B., Gerritsen, F.A. (eds) Biomedical Image Registration. WBIR 2006. Lecture Notes in Computer Science, vol 4057. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11784012_23
Download citation
DOI: https://doi.org/10.1007/11784012_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-35648-6
Online ISBN: 978-3-540-35649-3
eBook Packages: Computer ScienceComputer Science (R0)Springer Nature Proceedings Computer Science
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.