Segmentation And Characterization Of Masses In The Digital Mammograms

Breast tumor segmentation is needed for monitoring and quantifying breast cancer. However, automated tumor segmentation in mammograms poses many challenges with regard to characteristics of an image. A comparison of two different semi-automated methods, viz., modified gradient magnitude region growing technique (MGMRGT) and watershed method is undertaken here for evaluating their relative performance in the segmentation of breast tumor. A set of 6 mammogram images is used to validate the effectiveness of the segmentation methods. The MGMRGT segmentation shows better results than those due to watershed approach. The present application is intended to assist the radiologist in performing an in-depth examination of the breast at considerably reduced time.