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Inverse-Consistent Symmetric Free Form Deformation

  • Conference paper

Part of the Lecture Notes in Computer Science book series (LNIP,volume 7359)

Abstract

Bias in image registration has to be accounted for when performing morphometric studies. The presence of bias can lead to unrealistic power estimates and can have an adverse effect in group separation studies. Most image registration algorithms are formulated in an asymmetric fashion and the solution is biased towards the transformation direction. The popular free-form deformation algorithm has been shown to be a robust and accurate method for medical image registration. However, it suffers from the lack of symmetry which could potentially bias the result. This work presents a symmetric and inverse-consistent variant of the free form deformation.

We first assess the proposed framework in the context of segmentation-propagation. We also applied it to longitudinal images to assess regional volume change. In both evaluations, the symmetric algorithm outperformed a non-symmetric formulation of the free-form deformation.

Keywords

  • Image Registration
  • Normalise Mutual Information
  • Forward Transformation
  • Segmentation Propagation
  • Image Registration Algorithm

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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Modat, M., Cardoso, M.J., Daga, P., Cash, D., Fox, N.C., Ourselin, S. (2012). Inverse-Consistent Symmetric Free Form Deformation. In: Dawant, B.M., Christensen, G.E., Fitzpatrick, J.M., Rueckert, D. (eds) Biomedical Image Registration. WBIR 2012. Lecture Notes in Computer Science, vol 7359. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31340-0_9

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  • DOI: https://doi.org/10.1007/978-3-642-31340-0_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31339-4

  • Online ISBN: 978-3-642-31340-0

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