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Topology Preservation and Anatomical Feasibility in Random Walker Image Registration

  • Shawn Andrews
  • Lisa Tang
  • Ghassan Hamarneh
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8673)

Abstract

The random walker image registration (RWIR) method is a powerful tool for aligning medical images that also provides useful uncertainty information. However, it is difficult to ensure topology preservation in RWIR, which is an important property in medical image registration as it is often necessary for the anatomical feasibility of an alignment. In this paper, we introduce a technique for determining spatially adaptive regularization weights for RWIR that ensure an anatomically feasible transformation. This technique only increases the run time of the RWIR algorithm by about 10%, and avoids over-smoothing by only increasing regularization in specific image regions. Our results show that our technique ensures topology preservation and improves registration accuracy.

Keywords

Image Registration Target Registration Error Uncertainty Information Deformable Image Registration Deformable 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 International Publishing Switzerland 2014

Authors and Affiliations

  • Shawn Andrews
    • 1
  • Lisa Tang
    • 1
  • Ghassan Hamarneh
    • 1
  1. 1.Medical Image Analysis LabSimon Fraser UniversityCanada

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