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Multi-modal Image Registration Using the Generalized Survival Exponential Entropy

  • Shu Liao
  • Albert C. S. Chung
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4191)

Abstract

This paper introduces a new similarity measure for multi-modal image registration task. The measure is based on the generalized survival exponential entropy (GSEE) and mutual information (GSEE-MI). Since GSEE is estimated from the cumulative distribution function instead of the density function, it is observed that the interpolation artifact is reduced. The method has been tested on four real MR-CT data sets. The experimental results show that the GSEE-MI-based method is more robust than the conventional MI-based method. The accuracy is comparable for both methods.

Keywords

Mutual Information Image Registration Registration Error Image Registration Method Translational Probe 
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

  • Shu Liao
    • 1
  • Albert C. S. Chung
    • 1
  1. 1.Lo Kwee-Seong Medical Image Analysis Laboratory, Department of Computer Science and EngineeringThe Hong Kong University of Science and TechnologyHong Kong

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