%0 Journal Article
%T CT Image Segmentation Based on Mixture Gauss Markov Random Field Models<br>基于混合高斯模型MRF场的CT图像分割*
%A JIN Yan-fang
%A ZHANG Ding-hua
%A ZHAO Xin-bo
%A CHEN Zhi-qiang
%A ZHANG Dong-ping
%A <br>金炎芳
%A 张定华
%A 赵歆波
%A 陈志强
%A 张东平
%J 计算机应用研究
%D 2007
%I 
%X A method of CT image segmentation based on Gaussian mixture Markov field model was presented.According to the characteristics of the CT images,a Gaussian mixture model to approach image statistic model was established.The mixture Gaussian Markov random field for image processing was presented which the Gaussian mixture model was used to be the priori Markov random field probability model.Experimental results show that this method can get better result of segmentation than the signal gauss model.
%K ICT image
%K Gauss mixture model
%K Markov random field
%K image segmentation<br>工业CT图像
%K 混合高斯模型
%K 马尔科夫模型
%K 图像分割
%K 混合高斯
%K 高斯模型
%K 图像分割
%K Models
%K Markov
%K Random
%K Field
%K Gauss
%K Mixture
%K Based
%K 分割效果
%K 改善
%K 实验
%K 分割模型
%K 先验模型
%K 马尔可夫随机场
%K 统计模型
%K 图像灰度
%K 逼近
%K 工业
%K 分割方法
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=EF4AD2E7BFCF0B30A7E0EBC9A4C6992C&yid=A732AF04DDA03BB3&vid=B91E8C6D6FE990DB&iid=B31275AF3241DB2D&sid=5BC9492E1D772407&eid=6425DAE0271BB751&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=7