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A multi-scale approach to mass segmentation using graph cuts

This paper presents a novel scheme for mass segmentation in digitized mammograms, which is based on Graph Cuts algorithm and multi-scale analysis. The multi-scale method can segment mammographic images with a stepwise process from global to local segmentation by iterating Graph Cuts. To improve the segmentation efficiency and robustness, the watershed transform is used for pre-segmentation of the image to produce a region adjacency graph for the following optimization steps. Besides, this paper proposes a strategy of increasing smoothness energy term step by step in the Markov Random Field (MRF) image segmentation module, so as to improve the efficiency effectively in the mass segmentation. The new segmentation strategy effectively improves segmentation performance with less influences of image noise level. The experimental results demonstrate that the proposed method achieves a better performance in accuracy and robustness than conventional ones.