A Comparative Analysis on Filtering Techniques Used in Preprocessing of Mammogram Image

Abstract

Breast cancer is one of the vital causes of an increase in the rate of mortality of women in developing countries. Detection of micro-calcifications in the breast tissue by the radiologists is a significant step in the process of identification of cancer in the breast. Preprocessing in mammogram has played a vital role in identifying such micro-calcifications, masses and architectural distortion in the breast. It is important in the process of breast cancer analysis as it helps in reducing the number of false positive. The digital mammogram has emerged as the popular screening approach for early detection of masses and other abnormalities in the breast. In this manuscript, we introduced four standard filtering methods, which improve the efficiency of the model used for early detection of breast cancer. To compare the performance of the studies filter methods the mean square error and peak signal to noise ratio are widely used performance measure being considered in our work.