Novel network architecture and learning algorithm for the classification of mass abnormalities in digitized mammograms

The proposed approach produced very promising results. It has outperformed existing classification approaches in terms of classification accuracy, generalization and memorization abilities, number of iterations, and guaranteed training on a benchmark database.