| 基于KAP有向图模型的医学图像分类算法* |
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| 引用本文： | 吴枰,潘海为,高琳琳,韩启龙,谢晓芹,冯晓宁.基于KAP有向图模型的医学图像分类算法*[J].模式识别与人工智能,2016,29(5):427-438. |
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| 作者姓名： | 吴枰 潘海为 高琳琳 韩启龙 谢晓芹 冯晓宁 |
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| 作者单位： | 哈尔滨工程大学 计算机科学与技术学院 哈尔滨 150001 |
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| 基金项目： | 国家自然科学基金项目(No.61370084,61272184,61202090)、黑龙江省自然科学基金项目(No.F2016005)、中央高校基础科研业务费项目 |
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| 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。
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| 关 键 词： | 医学图像 纹理 角点 图模型 分类 |
| 收稿时间： | 2015-05-15 |
Medical Image Classification Algorithm Based on KAP Directed Graph Model |
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| WU Ping,PAN Haiwei,GAO Linlin,HAN Qilong,XIE Xiaoqin,FENG Xiaoning.Medical Image Classification Algorithm Based on KAP Directed Graph Model[J].Pattern Recognition and Artificial Intelligence,2016,29(5):427-438. |
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| Authors: | WU Ping PAN Haiwei GAO Linlin HAN Qilong XIE Xiaoqin FENG Xiaoning |
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| Affiliation: | College of Computer Science and Technology, Harbin Engineering University, Harbin 150001 |
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| Abstract: | 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 angular points and combining the inherent characteristics of medical images. Finally, a medical image classification algorithm based 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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| Keywords: | Medical Image Texture Angular Point Graph Model Classification |
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