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《Computer Science》 2012-08
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Improved Medical Image Segmentation Algorithm Based on Laplacian Level Set

WANG Xin1,2 XUE Long1 ZHANG Ming-ming1(College of Computer Science and Technology,Jilin University,Changchun 130012,China)1(Key Laboratory of Symbolic Computation and Knowledge Engineer of Ministry of Education,Jilin University,Changchun 130012,China)2  
Being a key procedure of image recognition and image understanding,image segmentation,on one hand,is regarded as being of important potential value,hence a lot of algorithms have been proposed,on the other hand,it has encountered a lot of challenges.Among all these challenges,one of them is how to acquire continuous segmentation result from blurring region.A new medical image segmentation algorithm based on the Lapalacian level set was proposed,and this algorithm combines regional information into speed function to drive the evolution of level set surface.The algorithm utilizes not only the information of image edges and gradient information,but also image region information.The algorithm takes advantage of regional global optimization features meanwhile maintaining the local features of edges.The new proposed algorithm implements effective segmentation of medical images.Compared with the classical level set segmentation methods,the improved algorithm has good performance in maintaining the continuity of the edges,so that the segmentation result is relatively complete.This algorithm can provide reliable scientific data for image analysis.
【Fund】: 国家自然科学基金项目(60905022);; 吉林省科技发展计划项目(201105016);; 吉林大学符号计算与知识工程教育部重点实验室开放基金项目资助
【CateGory Index】: TP391.41
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