Fast Explicit Diffusion for Registration with Direction-Dependent Regularization

  • Alexander Schmidt-Richberg
  • Jan Ehrhardt
  • René Werner
  • Heinz Handels
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7359)

Abstract

The accurate estimation of respiratory lung motion by non-linear registration is currently an important topic of research and required for many applications in pulmonary image analysis, e.g. for radiotherapy treatment planning.

A special challenge for lung registration is the sliding motion between visceral an parietal pleurae during breathing, which causes discontinuities in the motion field. It has been shown that accounting for this physiological aspect by modeling the sliding motion using a direction-dependent regularization approach can significantly improve registration results. While the potential of such physiology-based regularization methods has been demonstrated in several publications, so far only simple explicit solution schemes were applied due to the computational complexity.

In this paper, a numerical solution of the direction-dependent regularization based on Fast Explicit Diffusion (FED) is presented. The approach is tested for motion estimation on 23 thoracic CT images and a significant improvement over the classic explicit solution is shown.

Keywords

Motion Estimation Object Boundary Explicit Scheme Template Image Target Registration Error 
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 2012

Authors and Affiliations

  • Alexander Schmidt-Richberg
    • 1
  • Jan Ehrhardt
    • 1
  • René Werner
    • 1
  • Heinz Handels
    • 1
  1. 1.Institute of Medical InformaticsUniversity of LübeckLübeckGermany

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