Mass modeling and segmentation in mammogram

A novel method of mass segmentation in mammogram is proposed in this paper. First, a mathematical model is presented based on the clinical features of the mass and a multi-filtering method is used to detect the mass' location. Then, according to the result of clustered pixels, which is got by mean shift algorithm, rough handling masses could be obtained. Finally, the active contour without edge model is applied to refine the rough-wrought masses. Experiments implemented on the public MIAS database indicate that the proposed method can achieve better true positive rate than the morphological component analysis method with low false positive rate. In addition, the proposed segmentation method could emerge complete boundary, which could meet the clinical examination and diagnosis demand.EI05495-499+5223