Advertisement

Improvement of vessel segmentation by elastically compensated patient motion in digital subtraction angiography images

  • Thorsten M. Buzug
  • Cristian Lorenz
  • Jürgen Weese
Applications
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1296)

Abstract

Digital subtraction angiography is a standard diagnosis tool for the examination of vessels. For this method X-ray images (contrast images) are taken from the patient while a radio-opaque contrast agent is injected through a catheter. The first image of such a scene is usually taken before injection and is called mask image. In clinical routine the mask image is manually shifted to perform a rough motion compensation. Then the corrected mask is subtracted from the contrast image to erase all disturbing permanent structures like e.g. bones or organs. In the vessel diagnosis chain a vessel segmentation is often applied to the subtraction results. Real DSA-images only corrected via an interactive-shift routine still suffer from motion artifacts which may lead to false results from the segmentation step. Especially, for the abdomen where the patient motion is very complex it is illustrated how residual artifacts result in mis-segmentations. In the present paper we demonstrate that an affine transformation, and particularly, an elastic transformation yield an excellent patient motion compensation which is a sufficient basis for the segmentation algorithm. We describe a registration procedure based on the estimation of a motion vector field. Additionally, we outline a new vessel segmentation algorithm.

Keywords

Digital Subtraction Angiography Contrast Image Template Match Subtraction Image 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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    W. A. Chilcote, M. T. Modic, W. A. Pavlicek et. al., Digital subtraction angiography of the carotid arteries: A comparative study in 100 patients, Radiology 139 (1981) 287.PubMedGoogle Scholar
  2. 2.
    T. M. Buzug and J. Weese, Improving DSA images with an automatic algorithm based on template matching and an entropy measure, CAR'96, H. U. Lemke, M. W. Vannier, K. Inamura and A. G. Farman (Eds.), (Elsevier, Amsterdam, 1996) p. 145.Google Scholar
  3. 3.
    T. M. Buzug, J. Weese, C. Fassnacht and C. Lorenz, Image registration: Convex-weighted functions for histogram-based similarity measures, CVRMed/MRCAS'97, J. Troccaz, E. Grimson and R. Mösgen (Eds.), Lecture Notes in Computer Science 1205 (Springer, Berlin, 1997) p. 203.Google Scholar
  4. 4.
    F. L. Bookstein, Principal warps: Thin-plate splines and the decomposition of deformations, IEEE Trans. PAMI 11 (1989) 567.Google Scholar
  5. 5.
    T. M. Koller, G. Gerig, G. Székely and D. Dettwiller, Multiscale Detection of Curvilinear Structures in 2D and 3D Image Data, 5th International Conference on Computer Vision (Cambridge, 1995) p. 864.Google Scholar
  6. 6.
    T. Lindeberg, On scale selection for differential operators, 8th SCIA (1993) p. 857.Google Scholar
  7. 7.
    B. C. S. Tom, S. N. Efstratiadis, A. K. Katsaggelos, Motion estimation of skeletonized angiographic images using elastic registration, IEEE Trans. Med. Imaging 13 (1994) 450.CrossRefGoogle Scholar
  8. 8.
    W. K. Pratt, Correlation techniques of image registration, IEEE Trans. on AES, AES-10 (1974) 353.Google Scholar
  9. 9.
    J. M. Fitzpatrick, D. R. Pickens, H. Chang, Y. Ge and M. Özkan, Geometrical transformations of density images, SPIE 1137 (1989) 12.Google Scholar
  10. 10.
    A. Venot and V. Leclerc, Automated correction of patient motion and gray values prior to subtraction in digitized angiography, IEEE Trans. on Med. Im. 4 (1984) 179.Google Scholar
  11. 11.
    W. H. Press, B. P. Flannery, S. A. Teukolsky and W. T. Vetterling, Numerical Recipes in C (Cambridge University Press, Cambridge, 1990) p. 534.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

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

Personalised recommendations