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Tissues image retrieval system based on co-occuerrence, run length and roughness features

机译:组织图像检索系统基于共校正,运行长度和粗糙度特征

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The research presented in this paper was aimed to improve the retrieval performance of an images retrieval system in medical applications based on texture features. In general, the work consists of two phases: (1) enrollment phase, which consist of feature extraction based on Co-occurrence matrix and run length matrix features combined with developed method to measure the roughness, (2) retrieving phase, which use the artificial neural network and similarity measurement. The conducted tests were carried on 600 medical images from four types of tissues (i.e., blood cells, breast tissues, GI tissues, liver tissues) and give very high precision and recall rates (100,98).
机译:本文提出的研究旨在提高基于纹理特征的医学应用中的图像检索系统的检索性能。 一般而言,工作包括两个阶段:(1)注册阶段,由基于共发生矩阵和运行长度矩阵特征组成的特征提取和运行长度矩阵特征与开发方法一起测量粗糙度,(2)检索阶段,使用该方法 人工神经网络和相似度测量。 通过四种组织(即血细胞,乳腺组织,GI组织,肝组织)进行600种医学图像进行进行的测试,并提供非常高的精度和召回率(100,98)。

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