Liver image segmentation algorithm based on the Snake modeland optimized by watershed transformation
分水岭优化的Snake模型肝脏图像分割

Directional Snake is a classical algorithm in the active contour models, and is widely used in the field of image segmentation and video research in the past few years. Aimed at sensitivity to the initial contour and lack of curvature constraints in the formulation of the function, an automatic contour segmentation algorithm based on an improved watershed transformation and active contour model is presented. First, a modified watershed algorithm based on the marker function and the mandatory minimum technology is proposed in this paper to deal with the over-segmentation. Then,the improved watershed algorithm is adopted for pre-segmentation, and the extracted object contour is taken as the initial contour for the Snake model. Finally, an external force,which is related to the curve shape,is added in the Snake model for making up the lack of curvature constraints in the formulation of the energy function for precise segmentation computation. The improved Snake model can achieve good results in the liver image recognition and segmentation when applied to the MR images of the abdomen.