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Fuzzy Inference Mechanism Based Automatic Elastic Registration of Two-dimensional Gel Electrophoresis Images

机译:基于模糊推理机制的二维凝胶电泳图像自动弹性配准

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摘要

A key technique for protein analysis is the geometric alignment of two-dimensional polyacrylamide gel electrophoresis (2-D PAGE), i.e., 2-D PAGE image registration. In this study, the adaptability in elastic image registration was emphasized. According to the characteristics of 2-D gel image registration, a fuzzy-inference-rule based flexible model (FIM-FM) is proposed to model the complex transformation between 2-D gel image pairs. By introducing the concept of motion estimation, the parameter learning rules of the proposed model are derived for registration. The experiments show that the proposed algorithm is highly effective for registration of 2-D gel images and is competitive to the existing state-of-the-art algorithms.
机译:蛋白质分析的关键技术是二维聚丙烯酰胺凝胶电泳(2-D PAGE)的几何排列,即2-D PAGE图像配准。在这项研究中,强调了弹性图像配准的适应性。根据二维凝胶图像配准的特点,提出了一种基于模糊推理规则的柔性模型(FIM-FM),对二维凝胶图像对之间的复杂转换进行建模。通过引入运动估计的概念,导出了所提出模型的参数学习规则以进行注册。实验表明,所提出的算法对于二维凝胶图像的配准非常有效,并且与现有的最新算法相比具有竞争力。

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