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CVRMED
1997
Springer

Image registration: convex weighting functions for histogram-based similarity measures

9 years 6 months ago
Image registration: convex weighting functions for histogram-based similarity measures
Recently the entropy-similarity measure has been introduced for the registration of image pairs prior to subtraction in medical imaging e.g. digital subtraction angiography (DSA). The registration is based on motion-vector fields estimated with a template-matching techniques. The entropy is calculated via weighted grey-value histograms of the difference-image template and measures the degree of histogram dispersion in case of misregistration. In this paper, a generalization of the underlying concept is presented. We prove that any strictly convex function can be used as histogram-weighting function leading to a suitable similarity measure. The quality of the histogram-based measures is compared to other frequently used similarity measures. As a result the energy-similarity measure turns out to be the most suitable measure for template matching. The success of the registration will be demonstrated with a geometrically distorted pair of images taken of the abdomen.
Thorsten M. Buzug, Jürgen Weese, Carola Fassn
Added 07 Aug 2010
Updated 07 Aug 2010
Type Conference
Year 1997
Where CVRMED
Authors Thorsten M. Buzug, Jürgen Weese, Carola Fassnacht, Cristian Lorenz
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