Lucio Flávio A. Campos,  Emanuel C. M. Lemos,  Luis C. O. Silva,  Daniel D.Costa,  Allan Kardec Barros. 

We propose a method for segmentation and classification of breast cancer in digital mammograms using Independent Component Analysis (ICA), Texture Features and Multilayer Perceptron (MLP) Neural Networks. The method was tested for a mammogram set from MIAS database, resulting in 90.15% success rate, with 92% of specificity and 88.3% of sensitivity.

http://www.lbd.dcc.ufmg.br/colecoes/wim/2011/009.pdf

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