Segmentation of digitized mammograms using self-organizing maps in a breast cancer computer aided diagnosis system

Abstract

The objective of this work is to develop a digitized mammogram feature extraction approach using Kohonen's self-organizing maps (SOM). Once developed, the SOM network can be used as the first processing stage in a breast cancer computer aided diagnosis system. Its role is to offer segmented data as input to a second stage dedicated to the diagnosis task, which is implemented via a multilayer perceptron trained by the backpropagation algorithm.