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CVPR
2008
IEEE

Adaptive parametrization of multivariate B-splines for image registration

14 years 5 months ago
Adaptive parametrization of multivariate B-splines for image registration
We present an adaptive parametrization scheme for dynamic mesh refinement in the application of parametric image registration. The scheme is based on a refinement measure ensuring that the control points give an efficient representation of the warp fields, in terms of minimizing the registration cost function. In the current work we introduce multivariate B-splines as a novel alternative to the widely used tensor B-splines enabling us to make efficient use of the derived measure. The multivariate B-splines of order n are Cn-1 smooth and are based on Delaunay configurations of arbitrary 2D or 3D control point sets. Efficient algorithms for finding the configurations are presented, and B-splines are through their flexibility shown to feature several advantages over the tensor B-splines. In spite of efforts to make the tensor product B-splines more flexible, the knots are still bound to reside on a regular grid. In contrast, by efficient nonconstrained placement of the knots, the multiva...
Michael Sass Hansen, Rasmus Larsen, Ben Glocker, N
Added 12 Oct 2009
Updated 28 Oct 2009
Type Conference
Year 2008
Where CVPR
Authors Michael Sass Hansen, Rasmus Larsen, Ben Glocker, Nassir Navab
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