Medical Image Segmentation Research Based On Improved Level Set Method

Image segmentation,which is the key part of our image processing,is the substratum technology in image processing technology,is the foundation of all the image technology of artificial intelligence,is the precondition of higher level image understanding technology,thus,the image segmentation technology has always been the hot spot of the image processing and robot vision research and difficulty.Through the decades of development,image segmentation has been widely used in real life and work.,such as industrial robots?traffic lights?remote sensing image positioning?medical imaging technology etc.There are so many types image should be dealt by image segmentation,on this account,the processing method come to be complex and diverse.Research up to date,has not yet developed method with strong adaptability and commonality,and there is no perfect criteria can judge segmentation method.Therefore,the domestic and foreign scholars have been keen to mage segmentation research and improvement,conquer image segmentation research on the road constantly.On the basis of reference to many documents,this article has investigated medical image segmentation research based on improved level set method,and proposes several improvement methods:Image segmentation algorithm based on clustering and improved double level set,Image segmentation algorithm based on biased field and improved level set etc.And related intelligent image processing system is bewrote and designed.The main research contents and innovation points are as follows:1.This paper expounds the background and significance of medical image segmentation technology research,states the mathematical description of the medical image segmentation techniques,introduces the present situation of medical image segmentation technology research,also,the development of the medical image segmentation technology and difficulty is discussed.This paper describes basic model and common model of the level set method in mathematical way.2.In order to be able to split multiphase image,which appears in medical image with noise and multiple objective phenomenon frequently,this paper proposes the improved double level set model based on clustering algorithm,by suppression fuzzy clustering algorithm(SRFCM)"suppress competition" thought to improve the convergence speed of the algorithm,and then adopt the way of increasing energy penalty term to improve double level set medical image segmentation model(DCV),solve the multiple objective segmentation at last.3.In order to solve medical image gray level uneven,and the existence of the offset field problem,this paper proposes Image segmentation algorithm based on biased field and improved level set method,by coupling model of regional area and adding regional information,combining the global segmentation method and the Split-Bregman method.The 2N regions in the images are segmented by using N curves,according to variational multiphase level set method,add the energy penalty term in the function level set to avoid initialization,which reduces the segmentation algorithm of computing and time complexity.4.Practice,write and design Intelligent Segmentation Image Processing System V1.0,Medical Image Segmentation Processing System V1.0.using guided process for our user,open source design scheme,the programmer can compile in the environment of MATLAB Editor software algorithm function callback to improve segmentation algorithm and the user interface(GUI).