Résumé:
The segmentation of mammograms plays a major role in isolating areas, which can
be subject to tumors. The identification of these zones is done in three stages: contrast
enhancement, overdense regions detection and finally texture and shape analysis of the
regions of interest for a classification of masses. We use region growing algorithm for the
masses detection. Classification of these structures is accomplished through Support Vector
Machines, which separate them into two groups, Benign Tumors and Malignant Tumors, using
shape and texture descriptors to aid clinical diagnosis.