基于优化水平集的细胞图像分割算法  

Improved level-set segmentation algorithm on image sequences of stem cells

作　　者：张瑞华[1] 吴谨[2] 

机构地区：[1]武汉科技大学信息科学与工程学院,湖北武汉430081 [2]中国人民解放军空军雷达学院实验中心,湖北武汉430019

出　　处：《电子技术应用》2013年第9期142-144,共3页Application of Electronic Technique

基　　金：国家自然科学基金资助项目(60974012)

摘　　要：介绍了一种基于优化水平集的细胞图像分割算法。优化水平集在水平集算法基础上添加了局部熵和灰度变换,以达到突出边缘和去噪的目的。为修正经典OTSU阈值法忽略目标与背景的类内平均距离,创新性地对阈值选择函数进行改进。实验结果表明,相比于传统算法,该算法在正确分割率和运行时间上更优,在复杂的细胞图像分割中具备有效性和可行性。A separating algorithm for neuron stem cell images based on level-set segmentation algorithm combined with improved OTSU criterion is presented. Firstly, prove level-set, edge stopping function is constructed based on local entropy and grayscale transformation which can do a good work for overcoming the drawbacks. Secondly, analyze the shortcoming of the OTSU and propose a new threshold function according to the suggestion that make the variance within clusters as a factor of computing the best threshold. Experiments demonstrate that this algorithm has proved high-speed and has a good effect of cell segmention compared to traditional methods.

关 键 词：图像处理 图像分割 细胞粘连 水平集 局部熵 OTSU阈值 

分 类 号：TP391[自动化与计算机技术—计算机应用技术] TP37[自动化与计算机技术—计算机科学与技术]