R. A. Aliev, B. G. Guirimov and R. R. Aliev,A neuro-fuzzy object classifier with modified
distance measure estimator, Iranian Journal of Fuzzy Systems, 1(1) (2004), 5-15.
 K. Bovis, S. Singh, J. Fieldsend and C. Pinder,Identification of masses in digital mammograms
with MLP and RBF nets, IEEE Trans. on Image Processing, 1 (2005), 342-347.
 E. J. Candes and D. L. Donoho,Curvelets: a surprisingly effective non adaptive representation
for objects with edges, Saint-Malo Proceedings, Nashville, TN: Vanderbilt Univ, 2000.
 O. Cordon and M. J. del Jesus and F. Herrera,Genetic learning of fuzzy rule based classification
systems cooperating with fuzzy reasoning methods, Technical Report, DECSAI-970130,1997.
 M. N. Do and M. Vetterli,The contourlet transform: an efficient directional multi-resolution
image representation, IEEE Trans. on Image Processing, 14(12) (2005), 2091-2106.
 I. El-Naqa, Y. Yang, M. Wernick, N. Galatsanos and R. Nishikawa,A support vector machine
approach for detection of microcalcifications, IEEE Trans. on Medical Imaging, 21(12)(2002), 1552-1563.
 E. A. Fischer, J. Y. Lo and M. K. Markey,Bayesian networks of BI-RADS descriptors for
breast lesion classification, IEEE EMBS, San Francisco, 4 (2004), 3031-3034.
 O. J. Freixenet, A. Bosch, D. Raba and R. Zwiggelaar,Automatic classification of breast
tissue, Lecture Notes in Computer Science, Pattern Recognition and Image Analysis, (2000),431-438.
 W. H. Land, J. L. Wong Daniel, W. McKee, T. Masters and F. R Anderson,Breast cancer
computer aided diagnosis (CAD) using a recently developed SVM/GRNN oracle hybrid, IEEE
International Conference on Systems, Man and Cybernetics, 2003.
 C. T. Lin, C. M. Yeh, S. F. Liang, J. F. Chung and N. Kumar, Support-vector-based fuzzy
neural network for pattern classification, IEEE Trans. on Fuzzy Systems, 14(1) (2006), 31-41.
 A. O. Malagelada, Automatic mass segmentation in mammographic images, PhD Thesis,
Universitat de Girona, Spain, 2004.
 E. G. Mansoori, M. J. Zolghadri and S. D. Katebi,Using distribution of data to enhance
prformance of fuzzy classification systems, Iranian Journal of Fuzzy Systems, 4(1) (2007),21-36.
 E. G. Mansoori, M. J. Zolghadri, S. D. Katebi, H. Mohabatkar, R. Boostani and M. H.Sadreddini,
Generating fuzzy for protein classification, Iranian Journal of Fuzzy Systems,5(2)(2008), 21-33.
 F. Moayedi, Z. Azimifar, R. Boostani and S. Katebi,Contourlet based mammography mass
classification, Lecture Notes in Computer Science, Image Analysis and Recognition, 4633(2007), 923-934.
 F. Moayedi, R. Boostani, Z. Azimifar and S. Katebi,A support vector based fuzzy neural network
approach for mass classification in mammography, International Conference on Digital
Signal Processing, Britain, 2007.
 R. Mousa, Q. Munib and A. Mousa,Breast cancer diagnosis system based on wavelet analysis
and fuzzy-neural netwrok, IEEE Trans. on Image Processing, 28(4) (2005), 713-723.
 D. Y. Po and N. Do, Directional multiscale modeling of images using the contourlet transform,
IEEE Trans. on Image Processing, (2006), 1-11.
 D. Raba, A. Oliver, J. Marti, M. Peracaula and J. Espunya, Breast segmentation with pectoral
muscle suppression on digital mammograms, Springer-Verlag: Medical Imaging: Pattern
Recognition and Image Analysis, 3523 (2005), 471-478.
 M. Roffilli, Advanced machine learning techniques for digital mammography, Technical Report,
Department of Computer Science University of Bologna, Italy, 2006.
 M. S. B. Sehgal, I. Gondal and L. Dooley, Support vector machine and generalized regression
neural network based classification fusion models for cancer diagnosis, proceedings in Fourth
IEEE International Conference on Hybrid Intelligent System, Computer Society, 2004.
 L. Semler and L. Dettori, A comparison of wavelet-based and ridgelet-based texture classification
of tissues in computed tomography, International Conference on Computer Vision
Theory and Applications, 2006.
 L. Semler, L. Dettori and J. Furst, Wavelet-based texture classification of tissues in computed
tomography, IEEE International Symposium on Computer-Based Medical Systems, 2005.
 J. L. Starck, E. J. Candes and D. L. Donoho, The curvelet transform for image denoising,
IEEE Trans. on Image Processing, 11(6) (2002), 670-684.
 C. Varelaa, P. G. Tahocesb, A. J. Mndezc, M. Soutoa and J. J. Vidala, Computerized detection
of breast masses in digitized mammograms, Computers in Biology and Medicine, 37(2)(2007), 214-226.
 W. Xiaodan and W. Chongming, Using membership function to improve multi-class SVM
classification, ICSP Proceeding, China, 2004.
 Z. Yu and C. Bajaj, A fast and adaptive for image contrast enhancement, IEEE International
Conference on Image Processing, 2004.
 M. Zhu and A. M. Martinez, Subclass discriminant analysis, IEEE Trans. on Pattern Analysis
and Machine Intelligence, 28(8) (2006), 1247-1286.