An Efficient Preprocessing Technique for Multimodality Breast Cancer Images

On average, one in every eight women is diagnosed with breast cancer during their lifetime, and accounts for 14% of cancers women. Since early diagnosis could improve treatment outcomes longer survival times patients, it absolutely necessary to develop techniques classify lesions within mammograms ultrasound images. The main goal determine the class tumor present image, which pivotal diagnosing patients. In this paper, we propose an Sobel-Canny-Gabor(SCG) model, a hybrid model that implements three different edge detection filters; Sobel filter, Gabor Canny filter. This used enhance appearance mammogram images, then fed into classification model. Through classification, there be potential improvement results overall classification. Post-classification, evaluated using metric Peak Signal-to-Noise Ratio (PSNR), measures quality between original image compressed image.On image.