Journal of information and communication convergence engineering

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
권호 표지

Discrimination of Cancer Cell by Fuzzy Logic in Medical Images

  • Published : 2006.03.01
Download PDF
⟨ Previous Next ⟩

Abstract

A new method of digital image analysis technique for medical images of cancer cell is presented. This paper deals with the cancer cell discrimination. The object images were the Thyroid Gland cell images that were diagnosed as normal and abnormal. This paper proposes a new discrimination method based on fuzzy logic algorithm. The focus of this paper is an automatic discrimination of cells into normal and abnormal of medical images by dominant feature parameters method with fuzzy algorithm. As a consequence of using fuzzy logic algorithm, the nucleus were successfully diagnosed as normal and abnormal. As for the experimental result, average recognition rate of 64.66% was obtained by applying single parameter of 16 feature parameters at a time. The discrimination rate of 93.08% was obtained by proposed method.

Keywords

References

  1. Sing-Tze Bow, Pattern Recognition and Image Preprocessing, Marcel Dekker, New York, 1992
  2. A. Khotanzad and R. Kashyap, 'Feature Selection for Texture Recognition Based on Image Systhesis,' IEEE Trans. on Systems, Man, and Cybernetics, Vol. SMC-17, pp. 1087-1095, Nov., 1987
  3. W. Galvraith, et, al., 'Studies on Papanicolaou Staining,' Analytical and Quantitative Cytology, Vol. 1, No. 3, pp. 160-169, 1979
  4. G. W. Gill, K. A. Miller, 'In Compendium on Cytopreparatory Techniques,' Edited by C.M. Keebler, Tutorials of Cytology, Vol. 9, No. 25, 1974
  5. Cheol-Hun Na and Hyeon-Jae Kim, 'Effective Discrimination of Cancer cells in Medical Images,' Proc. of IEEE 1993 NSS and MIC, Vol. 2, pp. 1371-1375, San Francisco, CA, U. S. A., Nov. 1993
  6. W. K. Pratt, Digital Image Processing, 2nd ed., John Wiley & Sons, New York, 1991
  7. J. S. Weska, 'A Survey of Threshold Selection Techniques,' Computer Graphics and Image Processing, Vol. 7, No.2, pp. 259-265, April 1978 https://doi.org/10.1016/0146-664X(78)90116-8
  8. Cheol-Hun Na and Sang-Jin Ryoo, 'Cancer Cell Recognition by Dominant Feature Parameters Method,' GSPx 2003, Dallas, TX, U.S.A., 2003
  9. A. K. Nath and T. T. Lee, 'On the Design of a Classifier with Linguistic Variables as Inputs,' Fuzzy Sets Syst., vol. 11, pp. 265-285, 1983 https://doi.org/10.1016/S0165-0114(83)80086-4
  10. Cheol-Hun Na et, al., 'Discrimination of Cancer Cells by Distribution Function of Power Spectral Density of Fourier Transform,' GSPx 2004, Santa Clara, CA, U.S.A., 2004
  11. Cheol-Hun Na et, al., 'Cancer Cell Recognition by Fuzzy Logic in Medical Images,' GSPx 2005, Santa Clara. CA. U.S.A., 2005