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Atherosclerotic plaque tissue characterization in 2D ultrasound longitudinal carotid scans for automated classification: a paradigm for stroke risk assessment

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Abstract

In the case of carotid atherosclerosis, to avoid unnecessary surgeries in asymptomatic patients, it is necessary to develop a technique to effectively differentiate symptomatic and asymptomatic plaques. In this paper, we have presented a data mining framework that characterizes the textural differences in these two classes using several grayscale features based on a novel combination of trace transform and fuzzy texture. The features extracted from the delineated plaque regions in B-mode ultrasound images were used to train several classifiers in order to prepare them for classification of new test plaques. Our CAD system was evaluated using two different databases consisting of 146 (44 symptomatic to 102 asymptomatic) and 346 (196 symptomatic and 150 asymptomatic) images. Both these databases differ in the way the ground truth was determined. We obtained classification accuracies of 93.1 and 85.3 %, respectively. The techniques are low cost, easily implementable, objective, and non-invasive. For more objective analysis, we have also developed novel integrated indices using a combination of significant features.

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Authors and Affiliations

  1. Department of Electronics and Computer Engineering, Ngee Ann Polytechnic, Clementi, Singapore

    U. Rajendra Acharya & Muthu Rama Krishnan Mookiah

  2. Department of Biomedical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur, Malaysia

    U. Rajendra Acharya

  3. Global Biomedical Technologies Inc., CA, USA

    S. Vinitha Sree & Jasjit S. Suri

  4. Department of Electrical and Computer Engineering, Instituto Superior Tecnico, Lisbon, Portugal

    David Afonso & Joao Sanches

  5. CorVasc MDs, Indianapolis, IN, USA

    Shoaib Shafique

  6. Vascular Screening and Diagnostic Centre, London, Imperial college, London, UK

    Andrew Nicolaides

  7. Department of Biological Sciences, University of Cyprus, Nicosia, Cyprus

    Andrew Nicolaides

  8. Cardiovascular Institute and the Lisbon University Medical School, Hospital de SantaMaria, 1600-190, Lisbon, Portugal

    L. M. Pedro & J. Fernandes e Fernandes

  9. Department of Biomedical Engineering, Idaho State University, Pocatello, ID, USA

    Jasjit S. Suri

  10. Diagnostic and Monitoring Division, AtheroPoint(TM) LLC Roseville, CA, USA

    Jasjit S. Suri

Authors
  1. U. Rajendra Acharya
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  2. Muthu Rama Krishnan Mookiah
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  3. S. Vinitha Sree
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  4. David Afonso
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  5. Joao Sanches
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  6. Shoaib Shafique
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  7. Andrew Nicolaides
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  8. L. M. Pedro
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  9. J. Fernandes e Fernandes
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  10. Jasjit S. Suri
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Corresponding author

Correspondence to S. Vinitha Sree.

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Acharya, U.R., Mookiah, M.R.K., Vinitha Sree, S. et al. Atherosclerotic plaque tissue characterization in 2D ultrasound longitudinal carotid scans for automated classification: a paradigm for stroke risk assessment. Med Biol Eng Comput 51, 513–523 (2013). https://doi.org/10.1007/s11517-012-1019-0

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  • DOI: https://doi.org/10.1007/s11517-012-1019-0

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