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Physics-Based Elastic Image Registration Using Splines and Including Landmark Localization Uncertainties

  • Stefan Wörz
  • Karl Rohr
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4191)

Abstract

We introduce an elastic registration approach which is based on a physical deformation model and uses Gaussian elastic body splines (GEBS). We formulate an extended energy functional related to the Navier equation under Gaussian forces which also includes landmark localization uncertainties. These uncertainties are characterized by weight matrices representing anisotropic errors. Since the approach is based on a physical deformation model, cross-effects in elastic deformations can be taken into account. Moreover, we have a free parameter to control the locality of the transformation for improved registration of local geometric image differences. We demonstrate the applicability of our scheme based on 3D CT images from the Truth Cube experiment, 2D MR images of the brain, as well as 2D gel electrophoresis images. It turns out that the new scheme achieves more accurate results compared to previous approaches.

Keywords

Target Image Geometric Error Localization Uncertainty Landmark Localization Deformable Image Registration 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Stefan Wörz
    • 1
  • Karl Rohr
    • 1
  1. 1.Dept. Bioinformatics and Functional Genomics, Biomedical Computer Vision GroupUniversity of Heidelberg, IPMB, and DKFZ HeidelbergHeidelbergGermany

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