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Using an entropy similarity measure to enhance the quality of DSA images with an algorithm based on template matching

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Visualization in Biomedical Computing (VBC 1996)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1131))

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Abstract

The reduction of motion artifacts arising in DSA requires registration of mask- and contrast image prior to subtraction. An algorithm has been developed consisting of a) partitioning an interactively chosen region-of-interest (ROI) and exclusion of low-contrast partitions, b) assignment of homologous landmarks or control points, c) estimation of parameters of an affine transformation and application of the transformation on the mask image (inside the ROI), and d) subtraction of contrast- and corrected mask image. For assigning homologous landmarks, we use the entropy as similarity measure and compare the results to other frequently used measures.

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Authors and Affiliations

  1. Philips Research, Technical Systems Hamburg, Röntgenstraße 24-26, 22335, Hamburg, Germany

    Thorsten M. Buzug, Jürgen Weese, Carola Fassnacht & Cristian Lorenz

Authors
  1. Thorsten M. Buzug
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  2. Jürgen Weese
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  3. Carola Fassnacht
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  4. Cristian Lorenz
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Editor information

Karl Heinz Höhne Ron Kikinis

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© 1996 Springer-Verlag Berlin Heidelberg

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Buzug, T.M., Weese, J., Fassnacht, C., Lorenz, C. (1996). Using an entropy similarity measure to enhance the quality of DSA images with an algorithm based on template matching. In: Höhne, K.H., Kikinis, R. (eds) Visualization in Biomedical Computing. VBC 1996. Lecture Notes in Computer Science, vol 1131. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0046959

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  • DOI: https://doi.org/10.1007/BFb0046959

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-61649-8

  • Online ISBN: 978-3-540-70739-4

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