Medical Image Recognition Based on Fractal Features

  • Edward Kacki
  • Marcin Janaszewski
Conference paper
Part of the Advances in Soft Computing book series (AINSC, volume 19)


The article presents a new method of feature extraction from an image represented as a digital bit-mapped display in grey scale. The method is based on an idea of fractal model of nature and processes carried out in it. The results of three recognition experiments of different kinds of medical images were included. Fractal and traditional features were evaluated, by the Fisher coefficient, in each experiment. Extracted features were recognised by the use of: sigmoidal neural network, neuro-fuzzy system, k-nearest neighbour method and the nearest mode algorithm. The authors presented the discussion of obtained results, tips concerning fractal features extracting, the comparison of effectiveness and the properties of recognition the method used.


Feature Extraction Fractal Feature Recognition Quality Fractal Method Grain Texture 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [1]
    Fisher Y.: Fractal Image Compression, SIGGRAPH’92 Course Notes, 1992.Google Scholar
  2. [2]
    Hayes D. F.: Atlas of breast cancer, London Mosby-Wolfe, 1995.Google Scholar
  3. [3]
    Internet 2001,
  4. [4]
    Internet 2001,
  5. [5]
    Internet 2001,
  6. [6]
    Kcki E., Janaszewski M.: Neural network in extremal temperature determination at cyclic heating, Procedings of the fourth conference Neural network and Their Aplications in Zakopane, pp.673–679, Poland 1999.Google Scholar
  7. [7]
    Masters T.: Neural networks in practice, Warsaw, WNT, 1996. (In Polish)Google Scholar
  8. [8]
    Materka A., Strzelecki., M., Lerski R., Schad L.: Feature evaluation of texture test objects for magnetic resonance imaging, Procedings of the fifth conference Computers in Medicine in Lodz, pp 101–107, Poland 1999.Google Scholar
  9. [9]
    Rubens R. D., Fogelman I.: Bone metastases. Diagnosis and treatment. London: Springer-Verlab, 1991.CrossRefGoogle Scholar
  10. [10]
    Rutkowska D., Piliski M., Rutkowski L.: Neural networks, genetic algorithms and fuzzy systems, Warsaw, PWN, 1997. (In Polish)Google Scholar
  11. [11]
    Tadeusiewicz R., Flasiski M.: Pattern recognition, Warsaw, PWN, 1991. (In Polish)Google Scholar
  12. [12]
    Trojani M.: A colour atlas of breast histopatology, J. B. Lippincott Company, Philadelphia, 1991.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Edward Kacki
    • 1
  • Marcin Janaszewski
    • 2
  1. 1.Technical University of LodzLodzPoland
  2. 2.The College of Computer ScienceLodzPoland

Personalised recommendations