Combination of nonlinear filters and ANN for detection of microcalcifications in digitized mammography

Authors:
J. Quintanilla-Domínguez;M. G. Cortina-Januchs;Aleksandar Jevtic;D. Andina;J. M. Barrón-Adame;A. Vega-Corona
Affiliations:
Technical University of Madrid, Madrid, Spain;Technical University of Madrid, Madrid, Spain;Technical University of Madrid, Madrid, Spain;Technical University of Madrid, Madrid, Spain;University of Guanajuato, Laboratorio de Inteligencia Computacional, Guanajuato, Mexico;University of Guanajuato, Laboratorio de Inteligencia Computacional, Guanajuato, Mexico
Venue:
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Year:
2009

Citing 5
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Abstract

Breast cancer is one of the leading causes to women mortality in the world. Cluster of Microcalcifications (MCCs) 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 MCCs in mammograms which consists of image enhancement by histogram adaptive equalization technique, MCCs edge detection by Coordinate Logic Filters (CLF), generation, clustering and labelling of suboptimal features vectors by Self Organizing Map (SOM) Neural Network. The experiment results show that the proposed method can locate MCCs in an efficient way.