一种改进的拉普拉斯水平集医学图像分割算法  

Improved Medical Image Segmentation Algorithm Based on Laplacian Level Set

作　　者：王欣[1,2] 薛龙[1] 张明明[1] 

机构地区：[1]吉林大学计算机科学与技术学院,长春130012 [2]吉林大学符号计算与知识工程教育部重点实验室,长春130012

出　　处：《计算机科学》2012年第8期278-280,303,共4页Computer Science

基　　金：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

摘　　要：作为图像识别与图像理解的关键步骤,图像分割一直受到人们的重视,很多相应的算法被提出,但它也面临着很多挑战。医学图像分割的难点是对模糊边缘的连续有效分割,为准确的目标提取提供保障。提出一种新的医学图像分割算法,算法在拉普拉斯水平集图像分割算法基础上,融入图像的区域信息,重新定义了驱动水平集表面演化的速度函数。算法除了利用图像的边缘梯度信息外,还充分融合了图像的区域信息,从而在保持图像边缘局部特征的同时,充分利用了区域全局优化的特点,可实现医学图像的有效分割。与经典水平集分割方法相比,改进后的方法能够更好地保持边界的连续性,得到比较完整的分割结果,为图像分析提供可靠的科学数据。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.

关 键 词：医学图像分割 拉普拉斯算子 水平集 速度函数 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]