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中文摘要：
脑部CT图像拥有良好的纹理特性且图像间纹理角点的位置近似相同．基于此原因，文中提出基于K最近邻纹理角点（KAP）有向图模型的医学图像分类算法．首先提出面向纹理的角点提取方法；然后针对提取的角点，结合医学图像的固有特点，提出KAP有向图模型用于描述医学图像；最后基于KAP有向图模型提出医学图像分类算法．实验表明，文中算法在时间复杂度和准确度方面都取得较好结果．
英文摘要：
Brain CT images have good texture features and similar texture angular point positions between them. Thus, a classification algorithm based on K nearest neighbor texture angular points （KAP） directed graph model is put forward to classify medical images. Firstly, the T-Harris method is proposed to extract texture angular points. Then, the KAP directed graph model is presented by using texture and combining the inherent characteristics of medical images. Finally, a medical image angular points classification algorithmbased on the KAP directed graph model is proposed. Experimental results show good results of the presented algorithm in time complexity and accuracy.
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