In-Vivo IVUS Tissue Classification: A Comparison Between RF Signal Analysis and Reconstructed Images

  • Karla L. Caballero
  • Joel Barajas
  • Oriol Pujol
  • Neus Salvatella
  • Petia Radeva
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4225)


In this paper we present a novel framework for classification of the different kind of tissues in intravascular ultrasound (IVUS) data. We expose a normalized reconstruction of the IVUS images from radio frequency (RF) signals, and the use of these signals for classification. The reconstructed data is described in terms of texture based features and feeds an ECOC-Adaboost learning process. In the same manner, the RF signals are characterize using Autoregressive models, and classified with a similar learning process. A comparison is performed among these techniques and with DICOM based classification ones obtaining very promising results.


Local Binary Pattern Intravascular Ultrasound Gabor Filter Radio Frequency Signal DICOM Image 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Karla L. Caballero
    • 1
  • Joel Barajas
    • 1
  • Oriol Pujol
    • 1
    • 2
  • Neus Salvatella
    • 3
  • Petia Radeva
    • 1
  1. 1.Computer Vision CenterUAB BellaterraBarcelonaSpain
  2. 2.Dept. Matemàtica Aplicada i Anàlisi.University of BarcelonaBarcelonaSpain
  3. 3.Hospital Universitari German Trias i PujolBadalonaSpain

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