基于形态特征的医学图像检索与分类

Liuliu Fu, Yi-fei Zhang
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引用次数: 15

摘要

医学图像检索与分类是计算机辅助诊断的重要内容。特征提取是基于内容的图像检索与分类的重要技术之一。如何提取反映图像高级语义的底层特征是医学图像检索和分类的关键。针对这一问题,本文提出了一种利用边缘密度直方图提取医学图像形状特征的方法。然后利用欧氏距离和支持向量机(SVM)对医学图像进行检索和分类。实验结果表明,该算法已应用于医学图像检索,效果良好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Medical Image Retrieval and Classification Based on Morphological Shape Feature
Medical Image Retrieval and Classification is very important in Computer-Aided Diagnosis. Feature extraction is one of the most important techniques in content based image retrieval and classification. How to extract low-level features which reflect high-level semantics of an image is crucial for medical image retrieval and classification. In allusion to this issue, there proposed a method using edge density histogram to extract shape feature of medical images in this paper. Then Euclidean distance and Support Vector Machine (SVM) are used for medical image retrieval and classification. Results of experimentation showed that the proposed algorithm has been applied to medical image retrieval with promising effect.
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