Contributions to medical images analysis for breast cancer recognition ; Contributions à l'analyse d'images médicales pour la reconnaissance du cancer du sein

Computer-aided diagnosis of breast cancer is raising increasingly a genuine enthusiasm because of the ever-increasing quantity of mammographic images from breast cancer screening campaigns. The focus is on breast masses due to the high risk of cancer associated with them. Indeed, the variability of shape encountered and the difficulty to discern the masses especially when they are embedded in a high density require a new approach especially suited for the most complex cases namely the masses which belong to classes BI-RADS IV and V, i.e. spiculated breast mass and architectural distortion. In this work, a fully automatic computer-aided diagnosis system is designed for the segmentation and classification of breast mass especially for malignant masses of classes BI-RADS IV and BI-RADS V. Initially, we developed a pre-processing method combined with the reduction of the dictionary size in order to remove effectively and quickly the digitization noise of the mammographic images that make up the database used to design our computer-aided diagnosis system in comparison with the existing approaches. After the image pre-processing, we have proposed an unsupervised segmentation method based on a Markov random field which has the advantage of being faster, more efficient and more robust than the state-of-art segmentation methods. Furthermore, the proposed method overcomes the variability of the breast masses whatever the image density. In purpose to describe correctly the spiculated malignant lesions, we proposed an approach which avoid the computation and extraction of local features, and to rely on general-purpose classification procedures whose performance and computational efficiency can greatly vary depending on design and image characteristics. The proposed method is based on several assumptions on the structure of spicules as they appear in mammograms which have been reported in the literature. In order to make use of the above assumptions, the proposed method proceeds the following steps: first the mammogram is ...