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Independent Component Analysis Applied to the Detection of Early Breast Cancer Signs (2007) PDF
Título:Independent Component Analysis Applied to the Detection of Early Breast Cancer Signs (2007)
Autores: Ramón Gallardo Caballero, Carlos J. García Orellana, Horacio González Velasco, Miguel Macías Macías

Revista: 

Lectures Notes in Computer Science

Vol./Pag.: 

4505, 988-995
Ed./Año: Springer (Alemania), 2007
DOI:
10.1007/978-3-540-73007-1_119
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.