Semantic Modelling of Coronary Vessel Structures in Computer Aided Detection of Pathological Changes

  • Mirosław Trzupek
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6908)


In the paper, the author discusses the results of his research on the opportunities for using selected artificial intelligence methods to semantically analyse medical images. In particular, he will present attempts at using linguistic methods of structural image analysis to develop systems for the cognitive analysis and understanding of selected medical images, and this will be illustrated by the recognition of pathological changes in coronary arteries of the heart. The problem undertaken is important because the identification and location of significant stenoses in coronary vessels is a widespread practical task. The obtained results confirm the importance of the proposed methods in the diagnosis of coronary heart disease.


Intelligent medical image processing and understanding spatial modelling of coronary vessels computer-aided diagnosis 


  1. 1.
    Yusuf, S., Reddy, S., Ounpuu, S., Anand, S.: Global burden of cardiovascular diseases, Part I. General considerations, the epidemiologic transition, risk factors, and impact of urbanization. Circulation 104, 2746–2753 (2001)CrossRefGoogle Scholar
  2. 2.
    Lewandowski, P., Tomczyk, A., Szczepaniak, P.S.: Visualization of 3-D Objects in Medicine - Selected Technical Aspects for Physicians. Journal of Medical Informatics and Technologies 11, 59–67 (2007)Google Scholar
  3. 3.
    Sonka, M., Fitzpatrick, J.M.: Handbook of Medical Imaging. Medical Image Processing and Analysis, vol. 2. SPIE, Belligham (2004)Google Scholar
  4. 4.
    Katritsis, D.G., Pantos, I., Efstathopoulos, E.P., et al.: Three-dimensional analysis of the left anterior descending coronary artery: comparison with conventional coronary angiograms. Coronary Artery Disease 19(4), 265–270 (2008)CrossRefGoogle Scholar
  5. 5.
    Wang, Y., Liatsis, P.: A Fully Automated Framework for Segmentation and Stenosis Quantification of Coronary Arteries in 3D CTA Imaging. In: Dese, Second International Conference on Developments in eSystems Engineering, pp. 136–140 (2009)Google Scholar
  6. 6.
    Oncel, D., Oncel, G., Tastan, A., Tamci, B.: Detection of significant coronary artery stenosis with 64-section MDCT angiography. European Journal of Radiology 62(3), 394–405 (2007)CrossRefGoogle Scholar
  7. 7.
    SOMATOM Sensation Cardiac 64 Brochure.: Get the Entire Picture. Siemens medical (2004)Google Scholar
  8. 8.
    Tadeusiewicz, R., Korohoda, P.: Computer Analysis and Image Processing. Foundation of Progress in Telecommunication, Kraków (1997) (in Polish)Google Scholar
  9. 9.
    Pavlidis, T.: Algorithms for graphics and image processing. Computer Science Press, Rockville (1982)Google Scholar
  10. 10.
    Tadeusiewicz, R., Flasiński, M.: Pattern Recognition. PWN, Warsaw (1991) (in Polish)Google Scholar
  11. 11.
    Skomorowski, M.: A Syntactic-Statistical Approach to Recognition of Distorted Patterns. Jagiellonian University, Krakow (2000)Google Scholar
  12. 12.
    Tadeusiewicz, R., Ogiela, M.R.: Medical Image Understanding Technology. Springer, Heidelberg (2004)zbMATHGoogle Scholar
  13. 13.
    Faergeman, O.: Coronary Artery Disease. Elsevier, Amsterdam (2003)Google Scholar
  14. 14.
    Ogiela, M.R., Tadeusiewicz, R., Trzupek, M.: Picture grammars in classification and semantic interpretation of 3D coronary vessels visualisations. Opto.-Electronics Review 17(3), 200–210 (2009)CrossRefGoogle Scholar
  15. 15.
    Trzupek, M., Ogiela, M.R., Tadeusiewicz, R.: Image content analysis for cardiac 3D visualizations. In: Velásquez, J.D., Ríos, S.A., Howlett, R.J., Jain, L.C. (eds.) KES 2009. LNCS, vol. 5711, pp. 192–199. Springer, Heidelberg (2009)CrossRefGoogle Scholar

Copyright information

© IFIP International Federation for Information Processing 2011

Authors and Affiliations

  • Mirosław Trzupek
    • 1
  1. 1.Institute of AutomaticsAGH University of Science and TechnologyKrakówPoland

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