Applications of fuzzy rule-based systems in medical image understanding

Rough Fuzzy Image Analysis: Foundations and Methodologies

Volumn , Issue , 2010, Pages 6-1-6-31

  Tarnawski, Wojciech ^a   Schaefer, Gerald ^b   Nakashima, Tomoharu ^c   Miroslaw, Lukasz ^a  

^a WROCLAW UNIVERSITY OF TECHNOLOGY   (Poland)

^b ASTON UNIVERSITY   (United Kingdom)

^c Osaka City University   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 85026793677     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1201/9781439803301     Document Type: Chapter

References (39)

1. Anbar, N., L. Milescu, A. Naumov, C. Brown, T. Button, C. Carly, and K. AlDu-laimi. 2001. Detection of cancerous breasts by dynamic area telethermometry. IEEE Engineering in Medicine and Biology Magazine 20(5).
2. Bezdek J.C., Pal, S.K. 1992. Fuzzy models for pattern recognition. New York: IEEE Press.
3. Chi, Z., and H. Yan. 1993. Map image segmentation based on thresholding and fuzzy rules,. Electronic Letters 29(21):1841-1843.
4. Chi, Z., and H. Yan. 1995a. Handwritten numeral recognition using self-organizing maps and fuzzy rules. Pattern Recognition 28(1):59-66.
5. Chi, Z., and H. Yan. 1995b. Image segmentation using fuzzy rules derived from k-means clusters. Journal of Electronic Imaging 4(2):199-206.
6. Dunn, J.C. 1973. A fuzzy relative of the isodata process and its use in detecting compact well-separated clusters. Cybernetics and Systems 3:95-104.
7. Grabisch, M. 1996. The representation of importance and interaction of features by fuzzy measures. Pattern Recognition Letters 17:567-575.
8. Grabisch, M., and F. Dispot. 1992. A comparison of some methods of fuzzy classi-fication on real data. In 2nd int. conference on fuzzy logic and neural networks, 659-662.
9. Grabisch, M., and J.-M. Nicolas. 1994. Classification by fuzzy integral: performance and tests. Fuzzy Sets and Systems 65(2/3):255-271.
10. Gustafson, E.E., and W.C. Kessel. 1979. Fuzzy clustering with a fuzzy covariance matrix. In Proceedings of the ieee confonfrence on decision and control, 761-766.
11. Hamou, J.E. 1979. Microendoscopy and contact endoscopy. Tech. Rep., International Patent PCT/FR80/0024; US Patent 4,385,810, Paris, Washington D.C.
12. Haralick, R.M. 1979. Statistical and structural approaches to texture. Proceedings of the IEEE 67(5):786-804.
13. Head, J.F., F. Wang, C.A. Lipari, and R.L. Elliott. 2000. The important role of infrared imaging in breast cancer. IEEE Engineering in Medicine and Biology Magazine 19: 52-57.
14. Hoeppner, F., F. Klawonn, and T. Runkler. 1999. Fuzzy cluster analysis, methods for classification, data analysis and image recognition. John Wiley & Sons Ltd.
15. Ishibuchi, H., and T. Nakashima. 1999a. Improving the performance of fuzzy classifier systems for pattern classification problems with continuous attributes. IEEE Trans. on Industrial Electronics 46(6):1057-1068.
16. Ishibuchi, H., and T. Nakashima. 1999b. Performance evaluation of fuzzy classifier systems for multi-dimensional pattern classification problems. IEEE Trans. Systems, Man and Cybernetics-Part B: Cybernetics 29:601-618.
17. Ishibuchi, H., K. Nozaki, and H. Tanaka. 1992. Distributed representation of fuzzy rules and its application to pattern classification. Fuzzy Sets and Systems 52(1): 21-32.
18. Klir, G.J., and B. Yuan. 1995. Fuzzy sets and fuzzy logic. Prentice-Hall.
19. Lee, C.C. 1990. Fuzzy logic in control systems: Fuzzy logic controller part I and part II. IEEE Trans. Systems, Man and Cybernetics 20:404-435.
20. Ng, E.Y.K., and N.M. Sudarshan. 2001. Numerical computation as a tool to aid thermographic interpretation. Journal of Medical Engineering and Technology 25(2): 53-60.
21. Nozaki, K., H. Ishibuchi, and H. Tanaka. 1996. Adaptive fuzzy rule-based classification systems. IEEE Trans. Fuzzy Systems 4(3):238-250.
22. Qi, H., W. E. Snyder, J. F. Head, and R. L. Elliott. 2000. Detecting breast cancer from infrared images by asymmetry analysis. In 22nd IEEE Int. Conference on Engineering in Medicine and Biology.
23. Schaefer, G., T. Nakashima, M. Zavisek, Y. Yokota, A. Drastich, and H. Ishibuchi. 2007. Thermography breast cancer diagnosis by fuzzy classification of statistical image features. In Ieee int. conference on fuzzy systems, 1096-1100.
24. Street, W.N., W.H. Wolberg, and O.L. Mangasarian. 1993. Nuclear feature extraction for breast tumor diagnosis. In Spie international symposium on electronic imaging: Science and technology, volume 1905, vol. 1905, 861-870.
25. Sugeno, M. 1985. An introductory survey of fuzzy control. Information Science 30(1/2):59-83.
26. Sugeno, M., and T. Yasukawa. February 1993. A fuzzy-logic-based approach to quali-tative modeling. IEEE Trans. Fuzzy Systems 1(1):7-31.
27. Tarnawski, W., and J. Cichosz. 2008. Fuzzy rule-based system for diagnosis of la-ryngeal pathology based on contact endoscopy images. In Information technologies in medicine, ed. J. Kacprzyk, E. Pietka, and J. Kawa, vol. 47 of Advances in Soft Computing, 217-224. Berlin: Springer Verlag.
28. Tarnawski, W., M. Fraczek, M. Jelen, T. Krecicki, and M. Zalesska-Krecicka. 2008a. The role of computer-assisted analysis in the evaluation of nuclear characteristics for the diagnosis of precancerous and cancerous lesions by contact laryngoscopy. Advances in Medical Sciences 53(2):221-227.
29. Tarnawski, W., M. Fraczek, T. Krecicki, and M. Jelen. 2008b. Fuzzy rule-based classi-fication system for computer-aided diagnosis in contact endoscopy imaging. In Pro-ceedings of the 5th international conference on soft computing as transdisciplinary science and technology. New York, U.S.A.
30. Tarnawski, W., and M. Kurzynski. 2007. An improved diffusion driven watershed algo-rithm for image segmentation of cells. Journal of Medical Informatics & Technologies 11:213-220.
31. Tsotos, J.K. 1987. Image understanding, encyclopedia of artificial intelligence. Stuart c. shapiro ed. New York: John Wiley & Sons.
32. Uematsu, S. 1985. Symmetry of skin temperature comparing one side of the body to the other. Thermology 1(1):4-7.
33. Wang, J., and J.M. Mendel. 1991. Generating fuzzy rules by learning from examples. In Proceedings of the ieee international symposium on intelligent control, 263-268. Arlington, Viriginia U.S.A.
34. Wang L., Mendel J.M. 1991. Generating fuzzy rules by learning from examples. In Proceedings of the ieee international symposium on intelligent control, 263-268. Arlington, Viriginia U.S.A.
35. Wardrop, P., S. Sim, and K. McLaren. 2000. Contact endoscopy of the larynx: A quantitative study. Journal of Laryngology and Otology 114(6):437-440.
36. Yager, R.R., and D. P. Filev. 1994. Essentials of fuzzy modeling and control. John Wiley & Sons Inc.
37. Zavisek, M., and A. Drastich. 2005. Thermogram classification in breast cancer detec-tion. In 3rd. european and biological conference. 1727-1783.
38. Zheru, Ch., Y. Hong, and Tuan P. 1996. Fuzzy algorithms: With applications to image processing and pattern recognition. World Scientific Publishing.
39. Zimmerman, H.J. 1991. Fuzzy set theory and its applications. Boston: Kluwer.