Computer-Aided Diagnosis (CADx) schemes have been proposed to serve as a supplementary image analysis tool in mammography. Experienced radiologists tend be more assertive such assisting their interpretation rather than solely relying on ability detect suspicious signals. This study focuses simplified version of previously developed mammography CADx scheme, which was initially designed for digit...

The classification of breast masses from mammograms into benign or malignant has been commonly addressed with machine learning classifiers that use as input a large set of hand-crafted features, usually based on general geometrical and texture information. In this paper, we propose a novel deep learning method that automatically learns features based directly on the optmisation of breast mass c...

In this paper we present a computer aided diagnosis (CAD) system for mass detection and classification in digitized mammograms, which performs mass detection on regions of interest (ROI) followed by the benign-malignant classification on detected masses. In order to detect mass effectively, a sequence of preprocessing steps are proposed to enhance the contrast of the image, remove the noise eff...