Approach to automated screening of mammograms
Dragana P. Brzakovic, Predrag Brzakovic, Milorad Neskovic · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1993
This paper describes an adaptive image segmentation method that detects cancerous changes in mammograms. A mammogram containing abnormal signs changes is segmented into 'suspicious regions' and normal tissue. The method employs hierarchical region growing that uses pyramidal multiresolution image representation. The relationships between pixels at different resolution levels are established using a fuzzy membership function, thus enabling detection of very small and/or low contrast details in highly textured background. The paper discusses two versions of the method, the first is aimed at detection of microcalcifications, and the second at detection of benign and malign nodules. Both versions are fully automated and differ in selection of parameters of the fuzzy membership function. The algorithm was evaluated using synthetically generated objects superimposed on normal mammograms, and real mammograms. Based on this evaluation, the method has potential to be used as an aid to medical experts in establishing the correct diagnosis.