  Characterization of breast lesions is an essential prerequisite to detect
breast cancer in an early stage. Automatic segmentation makes this
categorization method robust by freeing it from subjectivity and human error.
Both spectral and morphometric features are successfully used for
differentiating between benign and malignant breast lesions. In this thesis, we
used empirical mode decomposition method for semi-automatic segmentation.
Sonographic features like ehcogenicity, heterogeneity, FNPA, margin definition,
Hurst coefficient, compactness, roundness, aspect ratio, convexity, solidity,
form factor were calculated to be used as our characterization parameters. All
of these parameters did not give desired comparative results. But some of them
namely echogenicity, heterogeneity, margin definition, aspect ratio and
convexity gave good results and were used for characterization.
