Automatic IVUS Segmentation of Atherosclerotic Plaque with Stop & Go Snake

  • Ellen Brunenberg
  • Oriol Pujol
  • Bart ter Haar Romeny
  • Petia Radeva
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4191)


Since the upturn of intravascular ultrasound (IVUS) as an imaging technique for the coronary artery system, much research has been done to simplify the complicated analysis of the resulting images. In this study, an attempt to develop an automatic tissue characterization algorithm for IVUS images was done. The first step was the extraction of texture features. The resulting feature space was used for classification, constructing a likelihood map to represent different coronary plaques. The information in this map was organized using a recently developed [1] geodesic snake formulation, the so-called Stop & Go snake. The novelty of our study lies in this last step, as it was the first time to apply the Stop & Go snake to segment IVUS images.


Local Binary Pattern Deformable Model IVUS Image Geodesic Active Contour Soft Plaque 
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 2006

Authors and Affiliations

  • Ellen Brunenberg
    • 1
  • Oriol Pujol
    • 2
  • Bart ter Haar Romeny
    • 1
  • Petia Radeva
    • 2
  1. 1.Department of Biomedical EngineeringEindhoven University of TechnologyEindhovenThe Netherlands
  2. 2.Computer Vision CenterUniversitat Autònoma de Barcelona, Edifici OBellaterra (Cerdanyola), BarcelonaSpain

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