Abstract
Breast cancer is one of the leading causes to women mortality in the world. Cluster of Microcalcifications (MCC) in mammograms can be an important early sign of breast cancer, the detection is important to prevent and treat the disease. In this paper, we present a novel method for the detection of MCC in mammograms which consists of image enhancement by histogram adaptive equalization technique, MCC edge detection by Coordinate Logic Filters (CLF), generation, clustering and labelling of suboptimal features vectors by means of Self Organizing Map (SOM) Neural Network. Like comparison we applied an unsupervised clustering K-means in the stage of labelling of our method. In the labelling stage, we obtain better results with the proposed SOM Neural Network compared with the k-means algorithm. Then, we show that the proposed method can locate MCCs in an efficient way.
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References
Wei, L., Yang, Y., Nishikawa, R.M.: Microcalcification classification assisted by content-based image retrieval for breast cancer diagnosis. Pattern Recognition 42(6), 1126 (2009)
Papadopoulos, A., Fotiadis, D.I., Costaridou, L.: Improvement of microcalcification cluster detection in mammography utilizing image enhancement techniques. Computers in Biology and Medicine 38(10), 1045 (2008)
Rezai-rad, G., Jamarani, S.: Detecting microcalcification clusters in digital mammograms using combination of wavelet and neural network. In: CGIV 2005: Proceedings of the International Conference on Computer Graphics, Imaging and Visualization, pp. 197–201 (2005)
Sung-Nien, Y., Kuan-Yuei, L., Yu-Kun, H.: Detection of microcalcifications in digital mammograms using wavelet filter and markov random field model. Computerized Medical Imaging and Graphics, 30(3), 163–173 (2006)
Vega-Corona, A., Álvarez, A., Andina, D.: Feature vectors generation for detection of microcalcifications in digitized mammography using neural networks. In: Mira, J., Álvarez, J.R. (eds.) IWANN 2003. LNCS, vol. 2687, p. 583. Springer, Heidelberg (2003)
Bhattacharya, M., Das, A.: Fuzzy logic based segmentation of microcalcification in breast using digital mammograms considering multiresolution. In: Machine Vision and Image Processing Conference, 2007, pp. 98–105 (2007)
Veni, G., Regentova, E.E., Zhang, L.: Detection of clustered microcalcifications with susan edge detector, adaptive contrast thresholding and spatial filters. In: Campilho, A., Kamel, M.S. (eds.) ICIAR 2008. LNCS, vol. 5112, pp. 837–843. Springer, Heidelberg (2008)
University of Essex. Mammographic image analysis society (2008), http://peipa.essex.ac.uk/ipa/pix/mias/
Laine, A.F., Schuler, Fan, S.J., Huda, W.: Mammographic feature enhancement by multiscale analysis. IEEE Transactions on Medical Imaging 13(4), 725–740 (1994)
Cheng, H.D., Cai, X., Chen, X., Hu, L., Lou, X.: Computer-aided detection and classification of microcalcifications in mammograms: a survey. Pattern Recognition 36(12), 2967–2991 (2003)
Mertzios, B.G., Tsirikolias, K.: Applications of coordinate logic filters in image analysis and pattern recognition. In: Proceedings of the 2nd International Symposium on Image and Signal Processing and Analysis, ISPA 2001, pp. 125–130 (2001)
Danahy, E.E., Panetta, K.A., Agaian, S.S.: Coordinate logic transforms and their use in the detection of edges within binary and grayscale images. In: IEEE International Conference on Image Processing, ICIP 2007, pp. 3:III – 53–III – 56 (2007)
Vega-Corona, A., Sánchez-García, M., González-Romo, M., Quintanilla-Domínguez, J., Barrón-Adame, J.M.: Contextual and non-contextual features extraction and selection method for microcalcifications detection. In: Proceedings of the World Automation Congress, July 2006, vol. 5 (2006)
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Quintanilla-Domínguez, J., Cortina-Januchs, M.G., Barrón-Adame, J.M., Vega-Corona, A., Buendía-Buendía, F.S., Andina, D. (2009). Detection of Microcalcifications Using Coordinate Logic Filters and Artificial Neural Networks. In: Mira, J., Ferrández, J.M., Álvarez, J.R., de la Paz, F., Toledo, F.J. (eds) Bioinspired Applications in Artificial and Natural Computation. IWINAC 2009. Lecture Notes in Computer Science, vol 5602. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02267-8_20
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DOI: https://doi.org/10.1007/978-3-642-02267-8_20
Publisher Name: Springer, Berlin, Heidelberg
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