Abstract
We introduce a new hybrid approach for spline-based elastic registration of multimodal medical images. The approach uses point landmarks as well as intensity information based on local analytic measures for mutual information. The intensity similarity metrics are computationally efficient and can be optimized independently for each voxel. We have successfully applied our approach to synthetic images, brain phantom images, as well as real multimodal medical images.
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References
Viola P, Wells WM. Alignment by maximization of mutual information. Proc ICCV. 1995; p. 16–23.
Rueckert D, Sonoda LI, Hayes C, et al. Nonrigid registration using free-form deformations: Application to breast MR images. IEEE Trans Med Imaging. 1999;18(8):712–721.
Hartkens T, Hill D, Castellano-Smith A, et al. Using points and surfaces to improve voxel-based non-rigid registration. Proc MICCAI. 2002; p. 565–572.
Teng CC, Shapiro LG, Kalet I. Head and neck lymph node region delineation using a hybrid image registration method. Proc IEEE ISBI. 2006; p. 462–465.
Wang X, Feng DD. Automatic hybrid registration for 2-D CT abdominal images. Proc ICIG. 2004; p. 208–211.
Fischer B, Modersitzki J. Intensity-based image registration with a guaranteed one-to-one point match. Methods Inf Med. 2004;43:327–30.
Wörz S, Winz ML, Rohr K. Geometric alignment of 2D gel electrophoresis images. Proc BVM. 2008; p. 97–101.
Wörz S, Rohr K. Physics-based elastic registration using non-radial basis functions and including landmark localization uncertainties. Computer Vis Image Underst. 2008; lll:263–274.
Karaçali B. Information theoretic deformable registration using local image information. Int J Computer Vis. 2007;72:219–237.
Kwan RKS, Evans AC, et al. MRI simulation-based evaluation of image-processing and classification methods. IEEE Trans Med Imaging. 1999;18(ll):1085–1097.
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© 2009 Springer-Verlag Berlin Heidelberg
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Biesdorf, A., Wörz, S., Kaiser, HJ., Rohr, K. (2009). Hybrid Spline-Based Multimodal Registration Using a Local Measure for Mutual Information. In: Meinzer, HP., Deserno, T.M., Handels, H., Tolxdorff, T. (eds) Bildverarbeitung für die Medizin 2009. Informatik aktuell. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-93860-6_26
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DOI: https://doi.org/10.1007/978-3-540-93860-6_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-93859-0
Online ISBN: 978-3-540-93860-6
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