HMPFIM-B: Hybrid Markov Penalized FCM in Mammograms for Breast Cancer

Abstract

Mammography is an imaging tool which uses low dose low energy x-ray for early detection of tumours in breast. Currently there are number of image based software applications to assist radiologists for better screening. Segmentation is the best way for reliable diagnosis by reducing false rate. So here, we propose novel segmentation algorithm using fuzzy logic. This new approach uses penalized fuzzy c means clustering in mammographic image to give significant improved performance while screening mammogram. The real-time implementation of this paper can be implemented using hardware and software interface with the mammography systems.