A two-stage method for lesion segmentation on digital mammograms

Abstract

In this paper, we present a two-stage method for the segmentation of breast mass lesions on digitized mammograms. A radial gradient index (RGI) based segmentation method is first used to estimate a initial contour close to the lesion boundary location in a computationally efficient manner. Then a region-based active contour algorithm, which minimizes an energy fucntion based on the homogeneities inside and outside of the envolving coutour, is applied to refine the contour closer to the lesion boundary. The minimization algorithm solves, by the level set method, the Euler-Lagrange equation that describes the contour evolution. By using a digitized screening film dababase with 96 biopy-proven, malignant lesions, we quantitatively compare this two-stage segmentation algorithm with a RGI-based method and a conventional region-growing algorithm by measuring the area similarity. At an overlap threshold of 0.30, the new method correctly segments 95% of the lesions while the prior methods delineate only 83% of the lesions. Our assessment demonstrates that the two-stage segmentation algorithm yields closer agreement with manually contoured lesion boundaries.