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Medical Image Retrieval Based on Semantic of Neighborhood Color Moment Histogram

机译:基于邻域颜色矩直方图语义的医学图像检索

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Content-based medical image retrieval is getting more and more importance in aspect of clinical assistant diagnose. This paper in allusion to gastroscopic images, make use of latent semantic indexing technology to implement image retrieval which based on its semantic information. First extract image's histogram of neighborhood color moments of low-level features, and then use normalizing, term weighting and singular value decomposition to realize low-level features mapping into high-level semantic features. In this way, the retrieval results will be more in accordance with the doctor's comprehension of the image's semantic content. The experimental results according to the prototype system show that the approach proposed in the paper could improve the retrieval performance steadily.
机译:在临床助手诊断方面,基于内容的医学图像检索越来越重要。本文针对胃镜图像,利用潜在语义索引技术,基于其语义信息进行图像检索。首先提取低级特征邻域颜色矩的图像直方图,然后使用归一化,项权重和奇异值分解来实现低级特征映射为高级语义特征。这样,检索结果将更符合医生对图像语义内容的理解。根据原型系统进行的实验结果表明,本文提出的方法可以稳定地提高检索性能。

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