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灰度共生矩阵和神经网络在医学图像处理中的应用
引用本文:孙进辉,于洋,李涢.灰度共生矩阵和神经网络在医学图像处理中的应用[J].实验技术与管理,2011,28(7):59-61.
作者姓名:孙进辉  于洋  李涢
作者单位:1. 中国人民武装警察部队学院训练部,河北廊坊,065000
2. 中国人民武装警察部队学院基础部,河北廊坊,065000
3. 首都医科大学附属北京口腔医院牙体牙髓科,北京,100050
摘    要:以龋齿诊断为例,探讨了灰度共生矩阵和神经网络在医学图像处理中的应用。通过对患者龋齿图像的特征分析,采用从灰度共生矩阵中提取的4个参数作为神经网络的输入特征向量,经过对该神经网络的多次训练,实现龋齿的识别。利用Matlab与VC++语言来设计龋齿诊断程序,并借助MIDEVA将其转化为脱离Matlab的工作环境的可执行程序,大大节省了系统资源。

关 键 词:龋齿识别  灰度共生矩阵  神经网络  MIDEVA

Application of gray level co-occurrence matrix and neural network in medical image processing
Sun Jinhui,Yu Yang,Li Yun.Application of gray level co-occurrence matrix and neural network in medical image processing[J].Experimental Technology and Management,2011,28(7):59-61.
Authors:Sun Jinhui  Yu Yang  Li Yun
Institution:Yun3(1.Training Department,the Chinese People’s Armed Police Forces Academy,Langfang 065000,China;2.Basic Department,the Chinese People’s Armed Police Forces Academy,Langfang 065000,China;3.Department of Operative Dentistry and Endodontics,Capital University of Medical Sciences,Beijing 100050,China)
Abstract:The application of gray level co-occurrence matrix and neural network in medical image processing by taking tooth decay diagnosis as an example was proposed and carefully experimented.With four coefficients extracted form gray level co-occurrence matrix of the tooth images as its input feature vector by analysis,the network was used to make differential diagnoses between decayed and normal teeth after it has been trained for many times.The diagnosis programs were projected with Matlab and VC++,and they were transformed into executable programs independent of Matlab,which save efficiently the limited system hardware resources.
Keywords:tooth decay diagnosis  gray level co-occurrence matrix  neural network  MIDEVA
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