@CONFERENCE\{IMM2008-06178,
    author       = "M. Hansen and B. Glocker and N. Navab and R. Larsen",
    title        = "Adaptive Parametrization of Multivariate {B-}splines for Image Registration",
    year         = "2008",
    pages        = "3254-3261",
    booktitle    = "{IEEE} Conference on Computer Vision and Pattern Recognition",
    volume       = "",
    series       = "",
    editor       = "",
    publisher    = "",
    organization = "",
    address      = "",
    url          = "http://www2.compute.dtu.dk/pubdb/pubs/6178-full.html",
    abstract     = "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 non- constrained placement of the knots, the multivariate {B-} splines are shown to give a good representation of inho- mogeneous objects in natural settings. The wide applicability of the method is illustrated through its application on medical data and for optical flow estimation.",
    isbn_issn    = "DOI: 10.1109/CVPR.2008.4587760"
}