Incorporating a segmentation routine for mammographic masses into a knowledge-based CADx approach

Computer aided diagnosis (CADx) systems have the potential to support the radiologist in the complex task of discriminating benign and malignant types of breast lesions based on their appearance in mammograms. Previously, we have proposed a knowledge-based CADx approach for mammographic mass lesions using casebased reasoning. The input of the systems reasoning process are features that are automatically extracted from regions of interest (ROIs) depicting mammographic masses.