Diagnosis of Breast Cancer in Digital Mammograms Using Independent Component Analysis and Neural Networks

  • Lúcio F. A. Campos
  • Aristófanes C. Silva
  • Allan Kardec Barros
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3773)


We propose a method for discrimination and classification of mammograms with benign, malignant and normal tissues using independent component analysis and neural networks. The method was tested for a mammogram set from MIAS database, and multilayer perceptron neural networks, probabilistic neural networks and radial basis function neural networks. The best performance was obtained with probabilistic neural networks, resulting in 97.3% success rate, with 100% of specificity and 96% of sensitivity.


Mammogram breast cancer independent component analysis neural networks computer aided diagnosis 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Lúcio F. A. Campos
    • 1
  • Aristófanes C. Silva
    • 1
  • Allan Kardec Barros
    • 1
  1. 1.Laboratory for Biologic Information ProcessingUniversity of Maranhão

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