摘要
提出了一种基于小波分解和Markov随机场的医学影像图像分割算法。该算法利用小波金字塔分解得到的多尺度分布较好的提取出图像的边缘轮廓信息,通过分层Markov建模,并借助最大后验概率准则克服了其边缘定位不准及非平稳性困难的缺点。实验结果表明,该算法有效地提高了图像分割的质量。
In this paper,a medical image segmentation algorithm based on wavelet transform and Markov random field was put forward.The algorithm of wavelet multiscale pyramid decomposition get distribution better extract image edge profile information,through the layered Markov modeling,and with the maximum a posteriori probability rule overcome its edge position non-accurate and non-stationary difficultly.The experimental results show that the algorithm can effectively improve the quality of image segmentation.
出处
《计算机应用》
CSCD
北大核心
2011年第A02期140-142,共3页
journal of Computer Applications
基金
国家自然科学基金资助项目(60603027)
天津市应用基础研究计划项目(05YFJMJC11700)
关键词
图像分割
小波金字塔分解
Markov场
期望最大化算法
image segmentation
wavelet pyramid decomposition
Markov field
Expectation-Maximization（EM） algorithm
