An Automatic-Pre-processing Method For Mammographic Images

Screening mammography represents the technique adopted to detect breast cancer at an early stage. However the presence of artifacts and pectoral muscle can disturb the detection of breast cancer and reduce the rate of accuracy in the computer aided analysis (CAD). For this reason, the preprocessing of mammogram images is very important in the process of breast cancer analysis because it reduces the number of false positive. It also allows radiologists to help in the comparison between mammograms. The aim of this paper is to propose a method of pre-processing on medio-lateral oblique-view (MLO) mammograms that is composed of two stages: the first step helps to extract the breast region from the rest of the image (background.), while the second aims at the suppression of the pectoral muscle. To extract the breast region, we used a method based on automatic thresholding (Otsu's) and Connected Component Labelling algorithm. Identifying the pectoral muscle has been done using the Hough transform and active contour. We evaluated our pre-processing method on a set of 80 images obtained from the DDSM database and we found that breast region extraction gave an excellent success rate that reached 100%. The success rate in the removal of the pectoral muscle was 92.5% with the use of Hough transform and active contour.