Adaboost to Classify Plaque Appearance in IVUS Images

  • Oriol Pujol
  • Petia Radeva
  • Jordi Vitrià
  • Josepa Mauri
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3287)

Abstract

Intravascular Ultrasound images represent a unique tool to analyze the morphological vessel structures and make decisions about plaque presence. Texture analysis is a robust way to detect and characterize different kind of vessel plaques. In this article, we make exhaustive comparison between different feature spaces to optimally describe plaque appearance and show that applying advanced classification techniques based on multiple classifiers (adaboost) significantly improves the final results. The validation tests on different kind of plaques are very encouraging.

Keywords

Linear Discriminant Analysis Recognition Rate Local Binary Pattern Vulnerable Plaque IVUS Image 
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 2004

Authors and Affiliations

  • Oriol Pujol
    • 1
  • Petia Radeva
    • 1
  • Jordi Vitrià
    • 1
  • Josepa Mauri
    • 1
  1. 1.Computer Vision Centre and Dept. InformàticaUniversitat Autònoma de BarcelonaBellaterra (Barcelona)Spain

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