Local Intensity Mapping for Hierarchical Non-rigid Registration of Multi-modal Images Using the Cross-Correlation Coefficient

  • Adrian Andronache
  • Philippe Cattin
  • Gábor Székely
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4057)


The hierarchical subdivision strategy which decomposes the non-rigid matching problem into numerous local rigid transformations is a very common approach in image registration. For multi-modal images mutual information is the usual choice for the measure of patch similarity. As already recognized in the literature, the statistical consistency of mutual information is drastically reduced when it is estimated for regions covering only a limited number of image samples. This often affects the reliability of the final registration result.

In this paper we present a new intensity mapping algorithm which can locally transform images of different modalities into an intermediate pseudo-modality. Integrated into the hierarchical framework, this intensity mapping uses the local joint intensity histograms of the coarsely registered sub-images and allows the use of the more robust cross-correlation coefficient for the matching of smaller patches.


Mutual Information Image Registration Intensity Mapping Subdivision Strategy Multimodal Image 
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

  • Adrian Andronache
    • 1
  • Philippe Cattin
    • 1
  • Gábor Székely
    • 1
  1. 1.ETH Zurich – Computer Vision LaboratoryZurich

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