AUTOMATED CLASSIFICATION OF BREAST CARCINOMA CELL BASED ON IMAGE PROCESSING AND SUPPORT VECTOR MACHINE

Abstract

As breast cancer is a substantial threat to the lives of women, it has become a major health issue in the world over the past 50 years, and its incidence has increased in the recent years. Early diagnosis and suitable treatment is relatively important. In the process of breast screening, tissue biopsy is an important operation in determining the presence of breast cancer. It not only provides an accurate diagnosis of the disease but also determines the prognosis for breast cancer. The main goal of this study is to develop a breast cancer diagnosis system based on histopathology and a sequence of image-processing technologies to analyze H&E stained images of breast tissues. The proposed system can automatically detect the mitosis of nuclei and analyze the size and the shape of nuclei to evaluate the duct structure of the breast tissue. Moreover, it provides physicians quantitative prognosis and classification of tissue malignancy, which will improve the diagnostic accuracy and efficiency of the cancer.