Classification of Breast Lesions in Combination with Metamorphic Segmentation and Saliency Feature Block

Abstract

Breast cancer is leading disease of females and every year death rate is increased gradually due to the breast cancer. Early diagnosis and treatment of breast cancer is an effective way to reduce the death rate of women. The development of the CAD systems improved the mortality rate by reducing false assumptions. This proposed work presents a computer-aided diagnosis (CAD) system for early detection of tumor in digitized mammograms. A novel classification method for breast lesions is proposed using transformative segmentation and saliency feature block. Experimental results show that proposed methods outperformed the existing method and provide timely diagnosis which greatly reduces the mortality rate in medical informatics.