Improved computer-aided diagnosis for breast lesions detection in DCE-MRI based on image registration and integration of morphologic and dynamic characteristics

Motion-based artifacts lead in breast MRI to diagnostic misinterpretation and therefore represents an important prerequisite to automatic lesion detection and diagnosis. In the present paper, we evaluate the performance of a computer-aided diagnosis (CAD) system consisting of motion correction, lesion segmentation, feature extraction and classification. Many novel feature extraction techniques are proposed and tested in conjunction with motion correction and classification. Our simulation results have shown that motion compensation combined with Minkowsi functionals and Bayesian classifier can improve the lesion detection and classification.