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3D Graph Description of the Intracerebral Vasculature from Segmented MRA and Tests of Accuracy by Comparison with X-ray Angiograms

  • Elizabeth Bullitt
  • Stephen Aylward
  • Alan Liu
  • Jeffrey Stone
  • Suresh K. Mukherji
  • Chris Coffey
  • Guido Gerig
  • Stephen M. Pizer
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1613)

Abstract

This paper describes largely automated methods of creating connected, 3D vascular trees from individual vessels segmented from magnetic resonance angiograms. Vessel segmentation is initiated by user-supplied seed points, with automatic calculation of vessel skeletons as image intensity ridges and automatic estimation of vessel widths via medialness calculations. The tree-creation process employs a variant of the minimum spanning tree algorithm and evaluates image intensities at each proposed connection point. We evaluate the accuracy of nodal connections by registering a 3D vascular tree with 4 digital subtraction angiograms (DSAs) obtained from the same patient, and by asking two neuroradiologists to evaluate each nodal connection on each DSA view. No connection was judged incorrect. The approach permits new, clinically useful visualizations of the intracerebral vasculature.

Keywords

Digital Subtraction Angiography Segmented Vessel Parent Vessel Vessel Segmentation Skeleton Curve 
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 1999

Authors and Affiliations

  • Elizabeth Bullitt
    • 1
  • Stephen Aylward
    • 1
  • Alan Liu
    • 1
  • Jeffrey Stone
    • 1
  • Suresh K. Mukherji
    • 1
  • Chris Coffey
    • 1
  • Guido Gerig
    • 1
  • Stephen M. Pizer
    • 1
  1. 1.Medical Image Display and Analysis GroupUniversity of North CarolinaChapel HillUSA

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