Abstract
We present a novel approach for a combined homogenization and registration technique. Medical image data is often disturbed by inhomogeneities from staining, illumination or attenuation. State-of-the-art approaches tackle homogenization and registration separately. Our new method attacks both troublemakers simultaneously. It is modeled as a minimization problem of a functional consisting of a distance measure and regularizers for the displacement field and the grayscale correction term. The simultaneous homogenization and registration enables an automatic correction of gray values and improves the local contrast. The combined approach takes slightly more computing time for an optimization step as compared to the non-combined scheme and so is much faster than sequential methods. We tested the performance both on academic and real life data. It turned out, that the combined approach enhances image quality, especially the visibility of slightly differentiable structures.
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References
Brown, L.G.: A survey of image registration techniques. ACM Computing Surveys 24(4), 325–376 (1992)
Collignon, A., Vandermeulen, A., Suetens, P., Marchal, G.: 3D multi-modality medical image registration based on information theory. Computational Imaging and Vision 3, 263–274 (1995)
Droske, M., Rumpf, M.: A variational approach to non-rigid morphological registration. SIAM Appl. Math. 64(2), 668–687 (2004)
Fischer, B., Modersitzki, J.: Fast inversion of matrices arising in image processing. Num. Algo. 22, 1–11 (1999)
Hajnal, J., Hawkes, D., Hill, D.: Medical image registration. CRC Press, Boca Raton (2001)
MathWorks, Natick, Mass, Matlab user’s guide (1992)
Modersitzki, J.: Numerical methods for image registration. Oxford University Press, Oxford (2004)
Modersitzki, J., Schmitt, O.: Image registration of histological sections, Preprint A-02-06, Institute of Mathematics, University of Lübeck, Germany (2002)
Roche, A.: Recalage d’images médicales par inférence statistique, Ph.D. thesis, Université de Nice, Sophia-Antipolis, France (2001)
Schmitt, O., Modersitzki, J.: Registrierung einer hochaufgelösten histologischen Schnittserie eines Rattenhirns. In: Handels, H., Horsch, A., Lehmann, T.M., Meinzer, H.P.H. (eds.) Bildverarbeitung für die Medizin 2001, pp. 174–178. Springer, Heidelberg (2001)
Paul, A.: Viola, Alignment by maximization of mutual information, Ph.D. thesis, Massachusetts Institute of Technology, pp. 1–155 (1995)
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Modersitzki, J., Wirtz, S. (2006). Combining Homogenization and Registration. 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_31
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DOI: https://doi.org/10.1007/11784012_31
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-35648-6
Online ISBN: 978-3-540-35649-3
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