MEAN SHIFT BASED ALGORITHM FOR MAMMOGRAPHIC BREAST MASS DETECTION

This paper presents a novel scheme for mass detection in mammography images. In this method, a mean shift-based algorithm is used to cluster pixels in the image. The extraction of the breast border is the first step. Image pixels are then clustered using a mean shift algorithm that employs intensity information to extract a set of high density points in the feature space. This is followed by further stages involving mode fusion. Due to its non-parametric nature, mean shift algorithm can work effectively with non-convex regions resulting in better candidates for a reliable segmentation. The proposed method has been validated on standard datasets and the results show that this method can detect masses in mammography images, making it useful for breast cancer detection systems.