基于Mumford-Shah模型的高精度MR图像轮廓提取算法  

A High-Accuracy Contour Extraction Algorithm for MR Images Based on Mumford-Shah Model

作　　者：原达[1,2] 张彩明[1] 李晋江[1] 刘晓华[2] 

机构地区：[1]山东大学计算机科学与技术学院,济南250100 [2]山东工商学院计算机科学与技术学院,山东烟台264005

出　　处：《计算机学报》2009年第2期268-274,共7页Chinese Journal of Computers

基　　金：国家自然科学基金(60773053,60673153,60673003)资助~~

摘　　要：提出了基于曲线演化的MR边界轮廓精确提取方法.针对MR图像边缘模糊和高噪声问题,改进Mum-ford-Shah曲线演化模型,将模糊聚类引入到轮廓演化能量模型中,降低对非规则细节和噪声的敏感性;利用水平集和半隐式的加性-乘性算子分裂数值方案进行轮廓线演化的迭代计算,提高精度和计算效率.实验表明这种方法可以对边界模糊和高噪声的轮廓进行有效提取.This paper proposes a high-accuracy contour extraction algorithm based on curve evolution model. Face to the blurred edges and high noise in MR image, Mumford-shah model is improved here and fuzzy clustering is used to establish active contour model to lower sensitivity to irregular details and noises. The derivation of the level set and the semi-implicit implementation based on the additive-multiplicative operator splitting is performed in order to improve the computing efficiency and accuracy. Experimental results are given to demonstrate the feasibility of the proposed method in extracting contour from the blurred edge and high-noise images.

关 键 词：曲线演化 轮廓提取 水平集 算子分裂 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]