Mass detection in mammograms using ga based PCA and Haralick features selection

2011 19th Iranian Conference on Electrical Engineering, ICEE 2011

Volumn , Issue , 2011, Pages

  Amroabadi, Sayedmasoud Hashemi ^a   Ahmadzadeh, Mohammad Reza ^b   Hekmatnia, Ali ^c  

^a UNIVERSITY OF TORONTO   (Canada)

^b ISFAHAN UNIVERSITY OF TECHNOLOGY   (Iran)

^c ISFAHAN UNIVERSITY OF MEDICAL SCIENCES   (Iran)

Author keywords

co occurrence matrices; component analysis; Digital mammography; Genetic algorithm

Indexed keywords

CO-OCCURRENCE-MATRIX; COMPONENT ANALYSIS; DIGITAL MAMMOGRAPHY; FEATURE EXTRACTION TECHNIQUES; HARALICK FEATURES; HYBRID METHOD; MASS DETECTION; PRINCIPLE COMPONENT ANALYSIS;

ELECTRICAL ENGINEERING; GENETIC ALGORITHMS; MAMMOGRAPHY; PRINCIPAL COMPONENT ANALYSIS; X RAY SCREENS;

FEATURE EXTRACTION;

EID: 80051920910     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (20)

1. S. K. Moore, "Better Breast cancer detection," Medical Imaging, IEEE SPECTRUM, May 2001.
2. S. L. Ng, and W.F. Bischof, "Automated detection and classification of breast tumors," Computers and Biomedical Research, vol. 25, pp. 218-237, 1992.
3. H. Qi, and W. Snyder, "Lesion detection and characterization in Digital mammography by Bezier histograms," SPIE Medical Imaging, San Diego, February, 1999.
4. F. Fauci, S. Bagnasco, R. Bellotti, D. Cascio, S.C Cheran, F. De Carlo, G. De Nunzio, M.E. Fantacci, G. Forni, A. Lauria, E.L. Torres, R. Magro, G.L. Masala, P. Oliva, M. Quarta, G. Raso, A. Retico, and S. Tangaro, "Mammogram segmentation by contour searching and massive lesion classification with neural network," Nuclear Science Symposium Conference Record, 2004 IEEE, vol.5, pp.2695-2699, 2004. (Pubitemid 41147826)
5. A. O. Malagelada, Automatic mass segmentation in mammographic images. PhD thesis, Universitat de Girona, 2004.
6. D. Raba, A. Oliver, J. Marti, M. Peracaula, and J. Espunya, "Breast segmentation with pectoral muscle suppression on digital mammograms," Proc. Marques, J.S., Pérez de la Blanca, N., Pina, P. (eds.) IbPRIA 2005. LNCS, vol. 3523, pp. 471-478, 2005. (Pubitemid 41343221)
7. M. Roffilli, "Advanced machine learning techniques for digital mammography," Technical Report, Department of Computer Science University of Bologna, UBLCS-2006, vol. 12, 2006.
8. L. Semler,L. Dettori, and J. Furst, "Wavelet-based texture classification of tissues in computed tomography," Proc. IEEE International Symp. on Computer-Based Medical Systems, 2005.
9. F. Moayedi, Z. Azimifar, and R. Boostani, and S. Katebi, "Contourlet-Based Mammography Mass Classification," Lecture Notes in Computer Science, Springer Berlin / Heidelberg, vol. 4633, pp. 923-934, 2007.
10. R. Mousa, Q. Munib, and A. Mousa, "Breast cancer diagnosis system based on wavelet analysis and fuzzy-neural network," IEEE Trans. Image Processing, vol. 28, no. 4, pp. 713-723, 2005. (Pubitemid 40583849)
11. L. Semler, and L. Dettori, "Curvelet-based texture classification of tissues in computed tomography," Proc. IEEE International Conf. on Image Processing, pp. 2165-2168, 2006.
12. M. N. Do, and M. Vetterli, "The contourlet transform: An efficient directional multiresolution image representation," IEEE Trans. Image Processing, vol. 14, no. 12, pp. 2091-2106, 2005. (Pubitemid 41781516)
13. H. Bu, S. Zheng, and J. Xia, "Genetic algorithm based Semi-feature selection method," Proc. Int. Joint Conf. on Bioinformatics, Sys. Biology and Intelligent Computing 2009, pp. 521-524, 2009.
14. E. A. Fischer, J. Y. Lo, and M. K. Markey, "Bayesian networks of BI-RADS descriptors for breast lesion classification," Proc. IEEE EMBS, San Francisco 4, pp. 3031-3034, 2004. (Pubitemid 40035678)
15. K. Bovis, S. Singh, J. Fieldsend, and C. Pinder, "Identification of masses in digital mammograms with MLP and RBF nets," IEEE Trans. Image Processing, vol. 1, pp. 342-347, 2002.
16. T. Mu, and A. K. Nandi, "Detection of breast cancer using v-SVM and RBF networks with self organization selection of centers," Proc. Third IEEE International Seminar on Medical Applications of Signal Processing, pp. 47-52, 2005.
17. O. J. Freixenet, A. Bosch, D. Raba, and R. Zwiggelaar, "Automatic classification of breast tissue," Proc. Marques, J.S., Pérez de la Blanca, N., Pina, P. (eds.) IbPRIA 2005. LNCS, vol. 3523, pp. 431-438, 2005. (Pubitemid 41343216)
18. K. I. Kim, K. Jung, and H. J. Kim, "Face recognition using kernel principal component analysis." IEEE Signal Processing Lett. Vol. 9, No.2, pp. 40-42, 2002. (Pubitemid 34490978)
19. H. Liu, J. Li, L. Wong, A comparative study on feature selection and classification methods using gene expression profiles and proteomic pattern, Genomic Informatics, 13, 51-60, 2002
20. D. S. Haykin, Neural Networks: A Comprehensive Foundation. New York: McMillan, 1994.