基于共现、行程长度和粗糙度特征的组织图像检索系统

Loay E. George, Esraa Z. Mohammed
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引用次数: 4

摘要

本文的研究旨在提高基于纹理特征的医学图像检索系统的检索性能。总的来说,该工作包括两个阶段:(1)登记阶段,包括基于共现矩阵和行程长度矩阵特征的特征提取,并结合开发的粗糙度测量方法;(2)检索阶段,使用人工神经网络和相似度测量。所进行的测试对来自四种组织(即血细胞、乳腺组织、胃肠道组织、肝脏组织)的600张医学图像进行了测试,并获得了非常高的精确度和召回率(100,98)。
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Tissues image retrieval system based on co-occuerrence, run length and roughness features
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).
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