Histogram-based image registration for digital subtraction angiography

  • Thorsten M. Buzug
  • Jürgen Weese
  • Cristian Lorenz
  • Wolfgang Beil
Poster Session D: Biomedical Applications, Detection, Control & Surveillance, Inspection, Optical Character Recognition
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1311)

Abstract

A generalized framework for histogram-based similarity measures is presented and applied to the image-enhancement task in digital subtraction angiography (DSA). The class of differentiable, strictly convex weighting functions is identified as suitable weightings of histograms for measuring the degree of clustering that goes along with registration. With respect to computation time, the energy similarity-measure is the function of choice for the registration of mask and contrast image prior to subtraction. The registration success for the automated procedure is compared with a manually shift-corrected image pair of the head.

Keywords

Similarity Measure Digital Subtraction Angio Contrast Image Template Match Contrast Variation 
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 1997

Authors and Affiliations

  • Thorsten M. Buzug
    • 1
  • Jürgen Weese
    • 1
  • Cristian Lorenz
    • 1
  • Wolfgang Beil
    • 1
  1. 1.Philips Research HamburgHamburgGermany

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