Improved GAC model for medical image sequence
引入新的停止函数的GAC模型医学图像序列分割

Traditional geodesics active contour model has a shortage in soft image and edge fog image segmentation. This paper constructed a new edge stop function by combining regional characteristics with relevance between sequence image, and brought the regional characteristics and priori information into the edge stop function. Then it applicated this new function in GAC model to improve medical sequence image segmentation quality, and achieved a much ideal result. Experiments show that after introducting of a priori information and improving its forms of expression, it greatly improved anti-noise performance and segmentation efficiency of the model.