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Intravascular Ultrasound Tissue Characterization with Sub-class Error-Correcting Output Codes

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Abstract

Intravascular ultrasound (IVUS) represents a powerful imaging technique to explore coronary vessels and to study their morphology and histologic properties. In this paper, we characterize different tissues based on radial frequency, texture-based, and combined features. To deal with the classification of multiple tissues, we require the use of robust multi-class learning techniques. In this sense, error-correcting output codes (ECOC) show to robustly combine binary classifiers to solve multi-class problems. In this context, we propose a strategy to model multi-class classification tasks using sub-classes information in the ECOC framework. The new strategy splits the classes into different sub-sets according to the applied base classifier. Complex IVUS data sets containing overlapping data are learnt by splitting the original set of classes into sub-classes, and embedding the binary problems in a problem-dependent ECOC design. The method automatically characterizes different tissues, showing performance improvements over the state-of-the-art ECOC techniques for different base classifiers. Furthermore, the combination of RF and texture-based features also shows improvements over the state-of-the-art approaches.

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Notes

  1. The codeword is a sequence of bits of a code representing each class, where each bit identifies the membership of the class for a given binary classifier.

  2. The parameters of the base classifiers are explained in the experimental results section.

  3. Due to the high similitude among slope-based and RF features results, the combination of texture-based and slope-based features has been omitted.

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Acknowledgements

This work has been supported in part by TIN2006-15308-C02 and FIS ref. PI061290.

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Authors and Affiliations

  1. Centre de Visió per Computador, Campus UAB, 08193, Bellaterra Barcelona, Spain

    Sergio Escalera, Oriol Pujol & Petia Radeva

  2. Department Matemàtica Aplicada i Anàlisi, UB, Gran Via 585, 08007, Barcelona, Spain

    Sergio Escalera, Oriol Pujol & Petia Radeva

  3. Hospital Universityari Germans Trias i Pujol, Badalona, Spain

    Josepa Mauri

Authors
  1. Sergio Escalera
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  2. Oriol Pujol
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  3. Josepa Mauri
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  4. Petia Radeva
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Correspondence to Sergio Escalera.

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Escalera, S., Pujol, O., Mauri, J. et al. Intravascular Ultrasound Tissue Characterization with Sub-class Error-Correcting Output Codes. J Sign Process Syst Sign Image Video Technol 55, 35–47 (2009). https://doi.org/10.1007/s11265-008-0180-z

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  • DOI: https://doi.org/10.1007/s11265-008-0180-z

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