Abstract
Computational anatomy via the deformable modeling or elastic matching paradigm is gaining increased prominence in medical imaging research. Our work in atlas-based localization of neuroanatomy has progressed toward statistical approaches that subsume the original elastic matching while retaining its practical flavor. In view of the complex geometries involved and the sparsity of image features in the localization problem, elastic matching is reformulated using variational principles to facilitate its numerical solution by the finite element method. The variational formulation in addition exposes the means by which Gibbs modeling and, thus, Bayesian analysis can be applied to the problem. In this paper, we review these developments and demonstrate the methods on MRI data, including the computation of interval estimates.
This work was supported by the U.S.P.H.S. under grant 1-RO1-NS-33662-01A1.
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References
R. Bajcsy and C. Broit. Matching of deformed images. In 6th Int. Conf. Pattern Recog., pages 351–353, 1982.
R. Bajcsy and S. Kovačič. Multiresolution elastic matching. Comput. Vision, Graphics, Image Process., 46:1–21, 1989.
K.-J. Bathe. Finite Element Procedures in Engineering Analysis. Prentice-Hall, Englewood Cliffs, 1982.
J. Besag. Towards Bayesian image analysis. J. Appl. Stat., 16:395–407, 1989.
L. Brown. A survey of image registration techniques. ACM Comput. Surveys, 24:325–376, 1992.
G. E. Christensen, M. I. Miller, M. W. Vannier, and U. Grenander. Individualizing neuroanatomical atlases using a massively parallel computer. IEEE Computer, 29(1):32–38, 1996.
G. E. Christensen, R. D. Rabbitt, M. I. Miller, S. C. Joshi, U. Grenander, T. A. Coogan, and D. C. Van Essen. Topological properties of smooth anatomic maps. In Y. Bizais, C. Barillot, and R. Di Paola, editors, Information Processing in Medical Imaging, pages 101–112. Kluwer Academic, Dordrecht, 1995.
R. Dann, J. Hoford, S. Kovačič, M. Reivich, and R. Bajcsy. Evaluation of elastic matching system for anatomic (CT, MR) and functional (PET) cerebral images. J. Comput. Assist. Tomogr., 13:603–611, 1989.
J. C. Gee. Probabilistic matching of deformed images. Ph.D. Thesis, Department of Computer and Information Science, University of Pennsylvania, Philadelphia, 1996.
J. C. Gee, M. Reivich, L. Bilaniuk, D. Hackney, R. Zimmerman, S. Kovačič, and R. Bajcsy. Evaluation of multiresolution elastic matching using MRI data. In M. H. Loew, editor, Medical Imaging V: Image Processing, pages 226–234, Bellingham, 1991. SPIE.
U. Grenander. General Pattern Theory. Oxford University Press, New York, 1993.
L. E. Malvern. Introduction to the Mechanics of a Continuous Medium. Prentice-Hall, Englewood Cliffs, 1969.
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Gee, J.C., Haynor, D.R., Le Briquer, L., Bajcsy, R.K. (1997). Advances in elastic matching theory and its implementation. In: Troccaz, J., Grimson, E., Mösges, R. (eds) CVRMed-MRCAS'97. CVRMed MRCAS 1997 1997. Lecture Notes in Computer Science, vol 1205. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0029225
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DOI: https://doi.org/10.1007/BFb0029225
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