Abstract
We propose a methodology for nonlinear alignment of three-dimensional objects on the basis of geometric features such as surfaces. Studies that require the collation of volumetric images from different individuals call for the use of nonlinear transformations. Elastic transformations [1] have been developed to contribute in the problem of registration of images from two different individuals. In this paper we examine their performance quality and accuracy. We align objects by using easily obtained features, such as external brain surfaces. The effectiveness of the method is evaluated by examining the accuracy with which inner structures are brought into registration. We compare the results of linear transformations ([2] — [3]) and Elastic transformations in the registration of two 3D images acquired from two different rat brains.
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References
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© 1998 Springer-Verlag London Limited
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Gabrani, M., Tretiak, O.J. (1998). Cross individual model-based alignment of volumetric images. In: Marshall, S., Harvey, N.R., Shah, D. (eds) Noblesse Workshop on Non-Linear Model Based Image Analysis. Springer, London. https://doi.org/10.1007/978-1-4471-1597-7_1
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DOI: https://doi.org/10.1007/978-1-4471-1597-7_1
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