Abstract
We propose a method for unifying registration and segmentation of multi-modal images assuming that the hidden scene model is a Gibbs probability distribution.
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References
A. P. Dempster, N. M. Laird, and D. B. Durbin. Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society, 39:185–197, 1977.
Stuart Geman and Donald Geman. Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images. IEEE Transactions on Pattern Analysis and Machine Intelligence, 6(6):721–741, 1984.
Alexis Roche, Gregoire Malandain, and Nicholas Ayache. Unifying maximum likelihood approaches in medical image registration. Technical Report 3741, INRIA, 1999.
Alexis Roche, Gregoire Malandain, Xavier Pennec, and Nicholas Ayache. Multimodal image registration by maximization of the corralation ratio. Technical Report 3378, INRIA, 1998.
M. I. Schlesinger and V. Hlaváč. Ten Lectures in Statistical and Structural Pattern Recognition. Kluwer Academic Publishers, Dordrecht, 2002.
Michail I. Schlesinger. Connection between unsuprevised and supervised learning in pattern recognition. Kibernetika, 2:81–88, 1968. In Russian.
Milan Sonka and J. Michael Fitzpatrick, editors. Handbook of Medical Imaging, volume 2. SPIE Press, 2000.
C. Studholme, D. L. G. Hill, and D. J. Hawkes. An overlap invariant entropy measure of 3D medical image alignment. Pattern Recognition, 32:71–86, 1999.
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© 2002 Springer-Verlag Berlin Heidelberg
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Flach, B., Kask, E., Schlesinger, D., Skulish, A. (2002). Unifying Registration and Segmentation for Multi-sensor Images. In: Van Gool, L. (eds) Pattern Recognition. DAGM 2002. Lecture Notes in Computer Science, vol 2449. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45783-6_24
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DOI: https://doi.org/10.1007/3-540-45783-6_24
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