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CLASSIFICATION OF BREAST MASSES USING ANFIS-BASED FUZZY ALGORITHMS: A COMPARATIVE STUDY

Year 2013, Volume: 13 Issue: 1, 1605 - 1611, 02.09.2013

Abstract

This study aims to produce a diagnosis system for breast masses related to breast cancer. The dataset consisting of 60 digital mammograms is acquired from Istanbul University Faculty of Medicine Hospital. 78 masses in the mammograms are extracted manually for this study by the experts. It is a fuzzy based comperative study of malignant-benign classification for breast masses which has the accuracy of 74.36% with k-means and 93.75% with ANFIS based fuzzy c-means and subtractive clustering.

References

  • In-Sung J., Devinder T. and Wang G.N. Neural Network Based Algorithms for diagnosis and classification of breast canser tumor. Department of Industrial and Information Engineerin, Ajou University, South Korea, 2011.
  • Gorgel P. , “Cancer Region diagnosis of 2-dimensional mammographic data using image processing techniques”, İstanbul University, The Institute of Sciences, Computer Engineering Department, PhD thesis, 2011.
  • DUNN, J.C., 1974, A Fuzyy Relative of ISODATA Process and Its Use in Detecting Compact, Well Separated Clusters, Journ., Cybern., 3, 95-104.
  • BEZDEK, J.C., 1981, “Pattern Recognition with Fuzzy Objective Function Algorithms”, Plenum Press, New York. Hongxing, L. et al. 2001. Fuzzy Neural Intelligent System, Mathematical Foundation and the Application in Engineering. CRC Press LLC.
  • SUGENO, M., 1977, "Fuzzy measures and fuzzy integrals: a survey," (M.M. GUPTA, G. N. SARIDIS, and B.R. GAINES, editors) Fuzzy Automata and Decision Processes, pp. 89-102, North-Holland, NY.
  • JANG, J.-S. R. and C.-T. SUN, 1997, “Neuro-Fuzzy and Soft Computing: A Computational Approach to Learning and Machine Intelligence”, Prentice Hall.
  • Geisser, Seymour (1993). Predictive Inference. New York, NY: Chapman and Hall. ISBN 0412034719.
Year 2013, Volume: 13 Issue: 1, 1605 - 1611, 02.09.2013

Abstract

References

  • In-Sung J., Devinder T. and Wang G.N. Neural Network Based Algorithms for diagnosis and classification of breast canser tumor. Department of Industrial and Information Engineerin, Ajou University, South Korea, 2011.
  • Gorgel P. , “Cancer Region diagnosis of 2-dimensional mammographic data using image processing techniques”, İstanbul University, The Institute of Sciences, Computer Engineering Department, PhD thesis, 2011.
  • DUNN, J.C., 1974, A Fuzyy Relative of ISODATA Process and Its Use in Detecting Compact, Well Separated Clusters, Journ., Cybern., 3, 95-104.
  • BEZDEK, J.C., 1981, “Pattern Recognition with Fuzzy Objective Function Algorithms”, Plenum Press, New York. Hongxing, L. et al. 2001. Fuzzy Neural Intelligent System, Mathematical Foundation and the Application in Engineering. CRC Press LLC.
  • SUGENO, M., 1977, "Fuzzy measures and fuzzy integrals: a survey," (M.M. GUPTA, G. N. SARIDIS, and B.R. GAINES, editors) Fuzzy Automata and Decision Processes, pp. 89-102, North-Holland, NY.
  • JANG, J.-S. R. and C.-T. SUN, 1997, “Neuro-Fuzzy and Soft Computing: A Computational Approach to Learning and Machine Intelligence”, Prentice Hall.
  • Geisser, Seymour (1993). Predictive Inference. New York, NY: Chapman and Hall. ISBN 0412034719.
There are 7 citations in total.

Details

Primary Language English
Journal Section Articles
Authors

Pelin Görgel

Ahmet Sertbas

Ainura Turusbekova This is me

Publication Date September 2, 2013
Published in Issue Year 2013 Volume: 13 Issue: 1

Cite

APA Görgel, P., Sertbas, A., & Turusbekova, A. (2013). CLASSIFICATION OF BREAST MASSES USING ANFIS-BASED FUZZY ALGORITHMS: A COMPARATIVE STUDY. IU-Journal of Electrical & Electronics Engineering, 13(1), 1605-1611.
AMA Görgel P, Sertbas A, Turusbekova A. CLASSIFICATION OF BREAST MASSES USING ANFIS-BASED FUZZY ALGORITHMS: A COMPARATIVE STUDY. IU-Journal of Electrical & Electronics Engineering. September 2013;13(1):1605-1611.
Chicago Görgel, Pelin, Ahmet Sertbas, and Ainura Turusbekova. “CLASSIFICATION OF BREAST MASSES USING ANFIS-BASED FUZZY ALGORITHMS: A COMPARATIVE STUDY”. IU-Journal of Electrical & Electronics Engineering 13, no. 1 (September 2013): 1605-11.
EndNote Görgel P, Sertbas A, Turusbekova A (September 1, 2013) CLASSIFICATION OF BREAST MASSES USING ANFIS-BASED FUZZY ALGORITHMS: A COMPARATIVE STUDY. IU-Journal of Electrical & Electronics Engineering 13 1 1605–1611.
IEEE P. Görgel, A. Sertbas, and A. Turusbekova, “CLASSIFICATION OF BREAST MASSES USING ANFIS-BASED FUZZY ALGORITHMS: A COMPARATIVE STUDY”, IU-Journal of Electrical & Electronics Engineering, vol. 13, no. 1, pp. 1605–1611, 2013.
ISNAD Görgel, Pelin et al. “CLASSIFICATION OF BREAST MASSES USING ANFIS-BASED FUZZY ALGORITHMS: A COMPARATIVE STUDY”. IU-Journal of Electrical & Electronics Engineering 13/1 (September 2013), 1605-1611.
JAMA Görgel P, Sertbas A, Turusbekova A. CLASSIFICATION OF BREAST MASSES USING ANFIS-BASED FUZZY ALGORITHMS: A COMPARATIVE STUDY. IU-Journal of Electrical & Electronics Engineering. 2013;13:1605–1611.
MLA Görgel, Pelin et al. “CLASSIFICATION OF BREAST MASSES USING ANFIS-BASED FUZZY ALGORITHMS: A COMPARATIVE STUDY”. IU-Journal of Electrical & Electronics Engineering, vol. 13, no. 1, 2013, pp. 1605-11.
Vancouver Görgel P, Sertbas A, Turusbekova A. CLASSIFICATION OF BREAST MASSES USING ANFIS-BASED FUZZY ALGORITHMS: A COMPARATIVE STUDY. IU-Journal of Electrical & Electronics Engineering. 2013;13(1):1605-11.