Independent component analysis applied to detection of early breast cancer signs

Authors:
Ramón Gallardo-Caballero;Carlos J. García-Orellana;Horacio M. González-Velasco;Miguel Macías-Macías
Affiliations:
CAPI Research Group, Universidad de Extremadura, Cáceres, Spain;CAPI Research Group, Universidad de Extremadura, Cáceres, Spain;CAPI Research Group, Universidad de Extremadura, Cáceres, Spain;CAPI Research Group, Universidad de Extremadura, Cáceres, Spain
Venue:
IWANN'07 Proceedings of the 9th international work conference on Artificial neural networks
Year:
2007

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Abstract

This work evaluates the efficiency of Independent Component Analysis in conjunction with neural network classifiers to detect microcalcification clusters in digitized mammograms, the most important non invasive sign of breast cancer. The widespread Digital Database for Screening Mammography was used as the source for digitized mammograms. The results seem to suggest that this technique is suitable to deal with the noisy mammogram environment.