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基于模糊决策的肝纤维化CT图像分类方法研究
Study on classification with CT images of hepatic fibrosis based on fuzzy decision
【摘要】 提出一种基于K近邻法的模糊决策的肝纤维化CT图像分类方法。对提取的图像频域特征向量用模糊加权K近邻法进行分类 ,其中引入隶属度函数对由于各种噪声和扫描参数的变化引起的特征值的不确定性进行描述。本研究结果表明模糊技术的应用提高了分类器的识别率和鲁棒性。
【Abstract】 The paper presents a classifier of K-nearest-neighbor based on fuzzy decision.The classifier uses a memˉbership function to describe the uncertainty of features extracted from the spectrums of images aroused by various noises and the changes of scanning parameters.In the classifier the values of fuzzy function are used as weights.The results demonstrated that the technology of fuzzy improves rates of detection and the robust of classifier with CT images of hepatic fibrosis.
【关键词】 模糊技术;
K近邻法;
特征提取;
隶属度函数;
【Key words】 technology of fuzzy; K-nearest-neighbor; feature extraction; membership function;
【Key words】 technology of fuzzy; K-nearest-neighbor; feature extraction; membership function;
- 【文献出处】 医疗设备信息 ,Information of Medical Equipment , 编辑部邮箱 ,2004年11期
- 【分类号】R816.5
- 【被引频次】3
- 【下载频次】81