| 基于贝叶斯网络高斯混合模型医学图像检索的研究 |
| |
| 引用本文： | 周显国.基于贝叶斯网络高斯混合模型医学图像检索的研究[J].中国数字医学,2014(11):60-61. |
| |
| 作者姓名： | 周显国 |
| |
| 作者单位： | 吉林省人民医院,吉林省长春市朝阳区工农大路1183号130021 |
| |
| 基金项目： | 吉林省科委资助项目（编号20070323）Fund project Funded by Science and Technology Commission of Jilin Province |
| |
| 摘 要： | 结合医学影像诊断的实际情况，提出一种基于贝叶斯网络高斯混合模型的医学图像检索方法。算法首先引入条件高斯模型，将连续变量模糊离散化，再利用贝叶斯网络对医学图像进行语义建模，并最终完成基于内容的图像检索。实验采用医学图像库中的CT和MRI影像样本进行仿真，仿真结果显示，这种方法是有效的，可以满足医生的一般需要。
|
| 关 键 词： | 医学图像 贝叶斯网络 高斯混合模型 连续变量模糊离散化 语义建模 |
Research on Medical Image Bayesian Network Retrieval Based on Gauss Mixture Model |
| |
| ZHOU Xian-guo.Research on Medical Image Bayesian Network Retrieval Based on Gauss Mixture Model[J].China Digital Medicine,2014(11):60-61. |
| |
| Authors: | ZHOU Xian-guo |
| |
| Institution: | ZHOU Xian-guo (Jilin People＇s Hospital, Changchun 130021, Jilin Province, P.R.C.) |
| |
| Abstract: | Combined with the actual situation of medical image diagnosis, this paper presents a medical image retrieval method of Bayesian network based on Gauss mixture model. The algorithm introduces the Gauss model, the continuous variable fuzzy discretization. then using the Bayesian network for medical image semantic modeling, and finally complete the content based image retrieval. Experiments using CT and MRI image samples of medical image databases in the simulation, the simulation results show, this method is effective and meet the general need a doctor. |
| |
| Keywords: | medical image bayesian network Gauss mixture model continuous variable fuzzy discretization semantic modeling |
| 本文献已被 维普 等数据库收录！ |
