Research On Liver CT Images Segmentation Algorithm Based On Level Set Method

With the wide application of new medical imaging methods such as CT,medical image processing and analysis has become one of the most rapidly developing and most notable achievements in medical technology.How to analyze the acquired image data is the key problem,so the segmentation technology becomes the key technology in the following image processing and analysis.In this thesis,the medical image segmentation method is reviewed,and the research object is based on the segmentation algorithm of the liver CT image based on the level set method.Aiming at the problems of the edge blur of CT image,the contrast between the organs and the gray level of liver parenchyma,the segmentation method of CT images of the liver is presented.The main work of this thesis is as follows:(1)In liver CT imaging noise and liver parenchyma gray uneven problems.For the first time,the mean shift method for smoothing the liver CT images,due to the traditional liver image smoothing method in smooth and drastically reduces the image quality and treatment of hepatic parenchyma of gray uneven problem is not very good,the increased after segmentation difficulty.Smooth along the gradient direction by mean shift method,preserves the edge information of images of the liver,while smoothing the image quality changes little,through experiments show that the method of liver image has good smoothing effect.(2)The problem of the contrast between the contrast and the edge of the organs in the liver CT images is presented,and the method of the interactive liver segmentation based on the GVFGAC model is proposed.Using region growing coarse segmentation,excluding liver image in other organs,and then through morphological transform and edge detection,repair area growth empty and over segmentation problem generated in the process,to obtain the gradient map with GVFGAC model fine segmentation and model GVFGAC through into the GVF model,the vector field,increase the ability to enter into depression,can complete the segmentation of liver in more detail.Experiments show that this method is better than some existing methods for liver image segmentation.(3)In order to eliminate the effect of human liver CT image segmentation,segmentation method is proposed for automatic liver CT images based on DRLSE model,through the clustering and classification of K-means,and then the image further by morphological transformation and find the biggest connected area to complete the coarse segmentation,and then through the C-V model and DRLSE model combined with level set method the completion of the liver CT image segmentation,the segmentation method automatically without human guidance,complex algorithm,the large amount of computation,the DRLSE model does not need to initialize the level set can greatly reduce the computation time,based on the energy in the C-V model,can quickly and accurately complete the segmentation of liver region.Experiments show that the proposed method is better than some existing automatic liver image segmentation method.