摘要
目的研究Rough集在乳腺癌辅助诊断中的应用。方法采用基于Rough集的属性约简算法,利用决策树算法对乳腺癌图像数据进行分类,辅助医疗诊断。结果实现了基于Rough集的属性约简算法,对乳腺癌数据进行处理,获得了分类的实验结果。结论该模型系统达到了较高的分类准确率,证明Rough集在辅助医疗诊断中有着广泛的应用前景。
Aim To study the application of Rough set algorithm for diagnosis breast cancer.Methods Apply the attribute reduction strategies of rough set to the data mining of the mammography classification,proposes a medical images classifier based on decision tree algorithm.Results Attribute reduction strategies of rough set for medical image data mining are realized,the experiment results are given.Conclusion The experimental results show that the system performs well in accuracy,verifying the great potential of rough set in assistant medical treatment.
出处
《西北大学学报（自然科学版）》
CAS
CSCD
北大核心
2007年第4期573-576,共4页
Journal of Northwest University（Natural Science Edition）
基金
国家自然科学基金资助项目(60372072)
关键词
ROUGH集
属性约简
分类
医学图像
Rough set
attribute reduction
classification
medical images
