Advertisement

Computer-Aided Diagnosis of Laryngopathies in the LabVIEW Environment: Exemplary Implementation

  • Dominika Gurdak
  • Krzysztof Pancerz
  • Jaroslaw Szkola
  • Jan Warchol
Part of the Studies in Computational Intelligence book series (SCI, volume 473)

Abstract

In the paper, we present a computer tool supporting a non-invasive diagnosis of selected larynx diseases. The tool is created on the basis of the LabVIEW environment. LabVIEW enables us to create, in an easy way, a user-friendly graphical interface facilitating both entering input data and visualizing results in order to make the platform ready to use directly in the medical community. Computer-aided diagnosis of laryngopathies, in the presented tool, is based on a family of coefficients reflecting spectrum disturbances around basic tones and their multiples for patients’ voice signals.

Keywords

computer-aided diagnosis laryngopathy LabVIEW decision support system 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
  2. 2.
    Multi-Dimensional Voice Program, MDVP (2011), http://www.kayelemetrics.com
  3. 3.
    Bazan, J.G., Nguyen, H.S., Nguyen, S.H., Synak, P., Wroblewski, J.: Rough set algorithms in classification problem. In: Polkowski, L., Tsumoto, S., Lin, T.Y. (eds.) Rough Set Methods and Applications, pp. 49–88. Physica-Verlag, Heidelberg (2000)CrossRefGoogle Scholar
  4. 4.
    Bazan, J., Szczuka, M.S.: The Rough Set Exploration System. In: Peters, J.F., Skowron, A. (eds.) Transactions on Rough Sets III. LNCS, vol. 3400, pp. 37–56. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  5. 5.
    Breiman, L., Friedman, J., Olshen, R., Stone, C.: Classification and Regression Trees. Chapman & Hall, Boca Raton (1993)Google Scholar
  6. 6.
    Gelzinis, A., Verikas, A., Bacauskiene, M.: Automated speech analysis applied to laryngeal disease categorization. Computer Methods and Programs in Biomedicine 91(1), 36–47 (2008)CrossRefGoogle Scholar
  7. 7.
    Greenes, R.: Clinical Decision Support: The Road Ahead. Elsevier (2007)Google Scholar
  8. 8.
    Grzymala-Busse, J.: A new version of the rule induction system LERS. Fundamenta Informaticae 31, 27–39 (1997)MATHGoogle Scholar
  9. 9.
    Hippe, Z.: Machine learning – a promising strategy for business information processing? In: Abramowicz, W. (ed.) Business Information Systems, pp. 603–622. Academy of Economics Editorial Office, Poznan (1997)Google Scholar
  10. 10.
    Pancerz, K., Paja, W., Szkola, J., Warchol, J., Olchowik, G.: A rule-based classification of laryngopathies based on spectrum disturbance analysis - an exemplary study. In: Van Huffel, S., et al. (eds.) Proc. of the BIOSIGNALS 2012, Vilamoura, Algarve, Portugal, pp. 458–461 (2012)Google Scholar
  11. 11.
    Pancerz, K., Szkola, J., Warchol, J., Olchowik, G.: Spectrum disturbance analysis for computer-aided diagnosis of laryngopathies: An exemplary study. In: Proc. of the International Workshop on Biomedical Informatics and Biometric Technologies (BT 2011), Slovak Republic, Zilina (2011)Google Scholar
  12. 12.
    Pawlak, Z.: Rough Sets. Theoretical Aspects of Reasoning about. Data. Kluwer Academic Publishers, Dordrecht (1991)MATHCrossRefGoogle Scholar
  13. 13.
    Quinlan, J.: C4.5. Programs for machine learning. Morgan Kaufmann Publishers (1993)Google Scholar
  14. 14.
    Semmlow, J.: Biosignal and Medical Image Processing. CRC Press (2009)Google Scholar
  15. 15.
    Szkola, J., Pancerz, K., Warchol, J.: Computer diagnosis of laryngopathies based on temporal pattern recognition in speech signal. Bio-Algorithms and Med-Systems 6(12), 75–80 (2010)Google Scholar
  16. 16.
    Szkola, J., Pancerz, K., Warchol, J.: Recurrent neural networks in computer-based clinical decision support for laryngopathies: An experimental study. Computational Intelligence and Neuroscience Article ID 289398 (2011)Google Scholar
  17. 17.
    Verikas, A., Gelzinis, A., Bacauskiene, M., Uloza, V.: Towards a computer-aided diagnosis system for vocal cord diseases. Artificial Intelligence in Medicine 36(1), 71–84 (2006)CrossRefGoogle Scholar
  18. 18.
    Warchol, J.: Speech examination with correct and pathological phonation using the SVAN 912AE analyser (in Polish). Ph.D. thesis, Medical University of Lublin (2006)Google Scholar
  19. 19.
    Witten, I.H., Frank, E.: Data Mining: Practical Machine Learning Tools and Techniques. Morgan Kaufmann (2005)Google Scholar
  20. 20.
    Wroblewski, J.: Genetic algorithms in decomposition and classification problem. In: Polkowski, L., Skowron, A. (eds.) Rough Sets in Knowledge Discovery 2, vol. 2, pp. 471–487. Physica-Verlag, Heidelberg (1998)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Dominika Gurdak
    • 1
  • Krzysztof Pancerz
    • 1
  • Jaroslaw Szkola
    • 1
  • Jan Warchol
    • 2
  1. 1.Institute of Biomedical InformaticsUniversity of Information Technology and ManagementRzeszówPoland
  2. 2.Department of BiophysicsMedical University of LublinLublinPoland

Personalised recommendations