Combining Homogenization and Registration

  • Jan Modersitzki
  • Stefan Wirtz
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4057)


We present a novel approach for a combined homogenization and registration technique. Medical image data is often disturbed by inhomogeneities from staining, illumination or attenuation. State-of-the-art approaches tackle homogenization and registration separately. Our new method attacks both troublemakers simultaneously. It is modeled as a minimization problem of a functional consisting of a distance measure and regularizers for the displacement field and the grayscale correction term. The simultaneous homogenization and registration enables an automatic correction of gray values and improves the local contrast. The combined approach takes slightly more computing time for an optimization step as compared to the non-combined scheme and so is much faster than sequential methods. We tested the performance both on academic and real life data. It turned out, that the combined approach enhances image quality, especially the visibility of slightly differentiable structures.


Image Registration Combine Approach Local Contrast Registration Technique Real Life Data 
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

  • Jan Modersitzki
    • 1
  • Stefan Wirtz
    • 1
  1. 1.Institute of MathematicsUniversity of LübeckGermany

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