Automatic segmentation of liver CT images based on Mean Shift method
Zhizhen Wang · Zhongguo yixue yingxiang jishu · 2010
Objective To assess the method based on Mean Shift for automatic segmentation of liver regions in CT images. Methods Firstly,the Mean Shift smoothing method achieved with a single iteration was applied to remove the noise in the original image for robustness enhancement of the algorithm. Then the initial seed point was selected automatically based on Mean Shift iterations and finally the region growing approach was utilized to implement automatic liver segmentation of the image. Results Experiment results showed that the presented algorithm was an accurate,fast and effective method for automatic segmentation of liver regions in CT images. Conclusion The new algorithm presented in this paper can efficiently implement automatic segmentation of liver regions from CT images.