Novel image processing techniques for early detection of breast cancer, mat lab and lab view implementation

Early detection of breast cancer is carried out by using mammographic images. Due to low contrast nature of these images, it is difficult to detect signs such as microcalcifications and masses. This paper describes novel algorithms for early detection of breast cancer using image enhancement techniques to identify masses and microcalcifications. We implemented algorithm for 1) Image enhancement using wavelets and adaptive histogram equalization technique 2) Segmentation of masses is done using region growing technique 3) Extraction of border of the mass using canny edge detection and morphological operations. Bilateral asymmetry was detected using fluctuating asymmetry [9]. The paper presents case studies of four patients, though fourteen patient breast images are processed having different mammographic features.