基于灰度分层和几何分块的蛋白质点匹配算法  

New Spot Matching Algorithm for Protein 2-DE Images Based on Geometric Blocking and Gray Hierarchical

作　　者：唐浩[1] 熊邦书[1] 欧巧凤[1] 李俊[1] 

机构地区：[1]南昌航空大学无损检测技术教育部重点实验室,南昌330063

出　　处：《生物医学工程学杂志》2014年第3期487-492,498,共7页Journal of Biomedical Engineering

基　　金：国家自然科学基金资助项目(61163047);江西省自然科学基金资助项目(20114BAB201036);江西省工业支撑计划项目资助(2010GB00405)

摘　　要：针对二维电泳凝胶图像匹配过程中,由于图像局部非线性形变导致的伪匹配和漏匹配问题,本文提出了一种结合灰度分层和几何分块的自动匹配算法。首先,依据灰度和几何位置对蛋白质点进行分组,采用形状上下文特征,结合归一化互相关法对蛋白质点进行粗匹配;然后,以粗匹配结果作为标记特征点,采用几何相似性准则,对未匹配点进行精确匹配;最后,采用局部仿射变换模型,验证匹配的正确性,去除伪匹配和漏匹配。通过对不同来源的凝胶图像进行匹配实验,结果表明本算法能有效解决蛋白质点匹配中的伪匹配和漏匹配问题,可获得更为精确的匹配结果。To reduce the mismatching and non-matching in the protein two-dimension electrophoresis （2-DE） images, we proposed an auto-malching algorithm based on gray hierarchical and geometric blocking in this study. Firstly, protein spots in the gel images were divided into groups by gray level and geometric position, and then a method based on shape context and normalized correlation was used for coarse matching in protein spots. Secondly, matched pairs in coarse matching were set as feature points, and the precise matching in the rest of not matched protein spots was accomplished by the method of geometric correlation and similarity criterion. Finally, local affine transformation was used in the verification of matching results to remove non-matching and mis-matching points. The algorithm was applied to different 2-DE gel images. The results showed that the new matching algorithm could reduce the non- matching and mis-matching spots, and increase the matching accuracy.

关 键 词：二维电泳凝胶图像 蛋白质点匹配 灰度分层 几何分块 形状上下文 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]