基于权重自动设置的医学图像检索算法

Qidong Zhang, Liqun Gao
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引用次数: 2

摘要

基于内容的多特征集成图像检索可以克服单一特征的问题,但如何将这些特征和特征表示方法结合起来是图像检索的关键。本文提出了一种基于粒子群优化的图像特征检索权值自动设置算法,该算法可以引导粒子的运动方向,并快速接近理想解集。结合医学图像,的特点,采用轮廓let变换进行纹理特征提取。泽尼克矩提取形状特征。实验结果表明,该方法具有较好的查全率和查准率。它可以得到医学图像检索的最佳特征组合。
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 Algorithm Using Setting Up Weight Automatically
Integrating multiple features content-based image retrieval can overcome the problems of single feature, but how to combine these features and feature representation methods is important in image retrieval. In this paper an image feature retrieval setting up weight automatically based on particle swarm optimization algorithm is proposed, which could guide the movement direction for particles, and close to ideal solution set quickly. Considering the characteristics of medical image ,, the contour let transform is used for texture feature extraction. Zernike moments extracts shape feature. The experimental results show that the recall and precision of this proposed approach is better. It can get the best feature combination for medical image retrieval.
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