Abstract
We consider the problem of non-rigid, point-to-point registration of two 3D surfaces. To avoid restrictions on the topology, we represent the surfaces as a level-set of their signed distance function. Correspondence is established by finding a displacement field that minimizes the sum of squared difference between the function values as well as their mean curvature. We use a variational formulation of the problem, which leads to a non-linear elliptic partial differential equation for the displacement field. The main contribution of this paper is the application of an adaptive finite element discretization for solving this non-linear PDE. Our code uses the software library DUNE, which in combination with pre- and post-processing through ITK leads to a powerful tool for solving this type of problem. This is confirmed by our experiments on various synthetic and medical examples. We show in this work that our numerical scheme yields accurate results using only a moderate number of elements even for complex problems.
Keywords
- Discontinuous Galerkin Method
- Signed Distance Function
- Human Skull
- Registration Problem
- Adaptive Finite Element
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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References
ALUGrid – Adaptive, Load Balanced, and Unstructured Grid Library, http://www.mathematik.uni-freiburg.de/IAM/Research/alugrid/
DUNE – Distributed and Unified Numerics Environment, http://dune-project.org/
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Dedner, A., Lüthi, M., Albrecht, T., Vetter, T. (2007). Curvature Guided Level Set Registration Using Adaptive Finite Elements. In: Hamprecht, F.A., Schnörr, C., Jähne, B. (eds) Pattern Recognition. DAGM 2007. Lecture Notes in Computer Science, vol 4713. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74936-3_53
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DOI: https://doi.org/10.1007/978-3-540-74936-3_53
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