Automatic detection of breast masses using two-view mammography

Abstract

Computer-Aided Detection (CADe) and Computer- Aided Diagnosis (CADx) systems have been developed to increase the possible abnormalities diagnostic performance of radiologists in the initial stage. However, several computerized systems analyze the MedioLateral Oblique (MLO) view and CranioCaudal (CC) views independently or using only one of the views. A group of tools for computer-aided detection of lesions caused by breast masses in the two above projections are presented in this paper. A preprocessing stage was applied to enhance the breast information. Moreover, a method for automatic segmentation of lesions combining genetic algorithm and wavelet transform for multilevel threshold was proposed. Through preliminary tests, the method seems to meaningfully improve the diagnosis in the early breast cancer detection with multi-views. It was found a difference about 11% between the boundary regions identified by the proposed approach and that obtained by compared the chain-code available in the base DDSM (Digital Database for Screening Mammography). © 2009 Springer-Verlag.