Abstract
Non-rigid mutual information (MI) registration algorithms with many degrees of freedom (DOF) are quite useful, but they come at high computational cost and have convergence issues. As a remedy adaptive non-rigid registration algorithms, where DOF is increased adaptively (i.e. the grid is refined adaptively), have been proposed. There are at least two ways to refine a grid adaptively: one based on changes in the global measure, the other based on a local measure. We compare these two and show that a local measure method can have better sensitivity to deformations than the global measure. The local measure employed is a novel method using local entropies and local MI.
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Park, H., Meyer, C.R. (2003). Grid Refinement in Adaptive Non-rigid Registration. In: Ellis, R.E., Peters, T.M. (eds) Medical Image Computing and Computer-Assisted Intervention - MICCAI 2003. MICCAI 2003. Lecture Notes in Computer Science, vol 2879. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39903-2_97
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DOI: https://doi.org/10.1007/978-3-540-39903-2_97
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