Point-based non-rigid surface registration with accuracy estimation

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Point-based non-rigid surface registration with accuracy estimation
This article presents a new method for non-rigid surface registration between a surface model and a surface of an internal organ in a given 3D medical image. The surface is represented with a set of feature points, of which locations are represented by a graphical model. For constructing the representation, a set of corresponding points is distributed on each of training surfaces based on an entropybased particle system. From these corresponding points, we estimate probability densities of the location of each feature point, the conditional probability distribution of the local image pattern around each feature point, and the probability distributions of relative positions between two neighboring feature points. When a new image is given, these densities are used for estimating the location of each feature point by means of a non-parametric belief propagation. The proposed method can estimate not only the locations of the feature points but also their conditional marginal distribution...
Hidekata Hontani, Wataru Watanabe
Added 06 Dec 2010
Updated 06 Dec 2010
Type Conference
Year 2010
Where CVPR
Authors Hidekata Hontani, Wataru Watanabe
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