Détection automatique des opacités dans les mammographies par la méthode de minimisation de la somme de l'inertie

Abstract

In this paper a new algorithm for detection of suspicious mass area from mammographic images is presented. It uses histogram modification enhancement technique and a segmentation method based on minimization of inertia sum. The histogram modification filter is designed so as to be able to enhance disease patterns of suspected masses by cleaning up unrelated background clutters. Segmentation is then performed on the enhanced-image to localize the suspected mass areas using minimisation of inertia sum of images intensity classes. The proposed algorithm was tested on a database of 32 mammogramms provided by Gynaeco-obstetric and pediatric hospital of Yaoundé on which masses had previously been localised by experienced radiologists. Results show that the algorithm is able to identify masses in all cases presented with a sensibility of 94% approximately. In addition, we found out that sizes and edges of masses detected are similar to those marked by radiologists. Furthermore in some cases, we could detect some hidden masses that the radiologists were not able to mark out.