Abstract
Breast cancer is one of the most common cancers worldwide. Breast cancer rates are high in low- and middle income countries, where breast tumors are diagnosed late. Early detection of masses or abnormalities that indicate breast cancer is a very important step for treating breast cancer in its first stages. The early detection of breast cancer tumors depends on both the ability of radiologists to read mammogram images and the quality of these images. The target of this research is to present an algorithm, which assists the radiologists identifying breast tumors at their early stages. This paper studies an algorithm for the automatic removal of artifacts and noise that are present in mammogram images using morphological operations, and then it enhances contrast of mammogram images using the Band Limited Histogram Equalization (BLHE) method for easier detection of lesions or tumors. After preprocessing of mammogram images, this algorithm segments the images using Otsu's N thresholding method to detect the region of interest in mammogram images.