Neighborhood matrix: A new idea in matching of two dimensional gel images

B. A. Savareh, Azadeh Bashiri, M. Mostafavi
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引用次数: 2

Abstract

Automated data analysis and pattern recognition techniques are the requirements of biological and proteomicsresearch studies. The analysis of proteins consists of some stages among which the analysis of two dimensionalelectrophoresis (2-DE) images is crucial. The aim of image capturing is to generate a Photostat that can be used infuture works such as image comparison. The researchers introduced a new method for matching two 2-DE gelimages. In this method, a neighborhood circular region is defined to obtain information about spots’ neighbors. Inthe present paper, the information obtained by this region is reordered into a matrix as a descriptor of the neighborsof each spot. The matrix is then used in matching the spots between two images. All conducted tests to evaluate themethod’s performance showed the power of the method in spot matching, even when the number of candidatematching spots in the second images increased. The proposed method provides a robust automatic comparison ideain gel images matching. Despite its low speed, its accuracy is excellent. The Novelty of the present study is the useof matrices as neighborhood descriptor. This idea is applicable in any other similar domain.
邻域矩阵:二维凝胶图像匹配的新思路
自动数据分析和模式识别技术是生物学和蛋白质组学研究的要求。蛋白质的分析包括几个阶段,其中二维电泳(2-DE)图像的分析是至关重要的。图像捕获的目的是生成一个可以在将来的工作中使用的Photostat,例如图像比较。研究人员介绍了一种新的方法来匹配两个2-DE gelimage。该方法通过定义一个邻域圆形区域来获取点的邻域信息。在本文中,该区域得到的信息被重新排序成一个矩阵,作为每个点的邻居的描述符。然后使用该矩阵来匹配两幅图像之间的点。所有评估该方法性能的测试都显示了该方法在点匹配方面的能力,即使在第二张图像中候选匹配点的数量增加时也是如此。该方法为凝胶图像匹配提供了一种鲁棒的自动比较方法。尽管它的速度很低,但它的准确性非常好。本研究的新颖之处在于使用矩阵作为邻域描述子。这个想法适用于任何其他类似的领域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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