Watershed segmentation of detected masses in digital mammograms

A method for segmentation of detected masses in digital mammograms is introduced. The method is based on gray scale mathematical morphology. In a preprocessing step, image enhancement based on a local histogram technique is applied, followed by a morphological smoothing operation. The watershed transform is then applied to the gradient of the smoothed image resulting in segmented regions. A good segmentation is important in order to be able to extract useful feature measures from the segmented regions. These feature measures can be input to a classifier which classifies each region as either a mass or a false detection. Initial experiments have been performed using mammograms from the MIAS database. Results of the experimental study indicate that our scheme can provide useful contour extraction for mass structures.