This paper introduces a new method for shape registration by matching vector distance functions. The vector distance function representation is more flexible than the conventional...
We present a novel variational and statistical approach for shape registration. Shapes of interest are implicitly embedded in a higher dimensional space of distance transforms. In...
Xiaolei Huang, Nikos Paragios, Dimitris N. Metaxas
Abstract. The goal of this paper is to present a novel recipe for deformable image registration under varying illumination, as a natural extension of the demons algorithm. This gen...
Conventional deformable registration methods are mostly driven by the interface between different brain structures. In recent years, Diffusion Tensor Magnetic Resonance Imaging (D...
Alexandre Guimond, Charles R. G. Guttmann, Simon K...
We introduce a novel probabilistic approach for nonparametric nonrigid image registration using generalized elastic nets, a model previously used for topographic maps. The idea of...