Development of an integrated breast tissue density classification software system

The current work aims at the classification of breast tissue according to Breast Imaging Reporting and Data System (BIRADS), based on texture features from mammographic images. To this end an integrated software system was developed in visual C++ using the .NET 2.0 Framework. The system takes as inputs pictures in most of the popular bitmap formats as well as DICOM and provides as output a specific breast density category according to the BIRADS system. The functionality of the system is provided by three modules: (a) the pre-processing module, where a set of tools for image manipulation (rotation, crop, gray level adjustment) are available accompanied by the ability to perform anisotropic filtering to the input image, (b) the breast segmentation module where the breast region is separated from the image background and pectoral muscle using characteristics of monogenic signals and Gabor wavelets respectively and (c) the breast tissue density classification module where the breast tissue is categorized according to the BIRADS, using texture characteristics and probabilistic Latent Semantic Analysis (pLSA). Special emphasis has been given to the development of a functional and user-friendly interface.