Mammograms enhancement based on multifractal measures for microcalcifications detection

Abstract

Breast cancer is the most common cancer in women and represents as a leading cause of death in the world (https://gco.iarc.fr/today/home). Microcalcifications (MCs) are the essential signs of precancerous cells. Their small size makes them difficult to detect and locate, hence the need of developing computer-aided detection systems for early detection of breast cancer. In this paper, an approach of MCs detection is proposed. Our system includes three phases. In the first, we start by a pre-processing step to remove various noises, followed by a step of intensity enhancement based on the haze removal algorithm. The third step is based on multifractal measures to construct the α-image which enhance MCs contrast. The proposed method was tested on three databases with a set of 371 images and evaluated in terms of PSNR and sensitivity. The obtained results are very significant and better compared to other approaches proposed in the literature.