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Segmentation of ultrasonic breast tumor images is a challenging topic in the clinical practice. A novel coarse-to-fine active contour (CFAC) model is proposed to extract boundaries of breast tumors based on a level-set framework. To apply the CFAC model, a Gaussian pyramid is firstly constructed to represent images at different resolution levels. Then, on the top pyramid level a region-based segmentation algorithm incorporating with the certain edge information is used to get a coarse boundary. Finally, the coarse boundary is gradually refined on other higher-level images according to the more detailed gradient information. Experiments are performed on both synthetic and real ultrasonic breast tumor images. The qualitative and quantitative results verified the efficiency of the CFAC model for the image segmentation task.