Mammogram Mass Segmentation Using Fractal Oriented Gamma Transformation

Digital mammogram has become the reliable and most effective screening method for the early detection of breast cancer. A novel Fractal Hurst-based Gamma Transformation (FHGT) is presented in this paper for the segmentation of masses from mammograms. This method is a composition of two mechanisms namely detection of masses from digital mammograms and the segmentation of those detected masses. The artifacts removal and spatial enhancement are performed for pre-processing of the mammograms, which subsequently help in mass detection. The process of segmentation is performed using morphological operations. The proposed FHGT is proved to produce promising results in terms of segmentation that confirms its merit.