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首页> 外文期刊>Biomedical and Health Informatics, IEEE Journal of >A Fully Automatic Method for Gridding Bright Field Images of Bead-Based Microarrays
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A Fully Automatic Method for Gridding Bright Field Images of Bead-Based Microarrays

机译:基于珠子微阵列的亮场图像网格化的全自动方法

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摘要

In this paper, a fully automatic method for gridding bright field images of bead-based microarrays is proposed. There have been numerous techniques developed for gridding fluorescence images of traditional spotted microarrays but to our best knowledge, no algorithm has yet been developed for gridding bright field images of bead-based microarrays. The proposed gridding method is designed for automatic quality control during fabrication and assembly of bead-based microarrays. The method begins by estimating the grid parameters using an evolutionary algorithm. This is followed by a grid-fitting step that rigidly aligns an ideal grid with the image. Finally, a grid refinement step deforms the ideal grid to better fit the image. The grid fitting and refinement are performed locally and the final grid is a nonlinear (piecewise affine) grid. To deal with extreme corruptions in the image, the initial grid parameter estimation and grid-fitting steps employ robust search techniques. The proposed method does not have any free parameters that need tuning. The method is capable of identifying the grid structure even in the presence of extreme amounts of artifacts and distortions. Evaluation results on a variety of images are presented.
机译:本文提出了一种基于网格的微阵列亮场图像栅格化的全自动方法。已经开发了许多用于对传统斑点微阵列的荧光图像进行网格化的技术,但据我们所知,尚未开发出用于对基于微珠的微阵列的明场图像进行网格化的算法。提出的网格化方法设计用于基于珠子的微阵列的制造和组装过程中的自动质量控制。该方法开始于使用进化算法估计网格参数。接下来是网格拟合步骤,该步骤将理想的网格与图像严格对齐。最后,网格细化步骤使理想的网格变形以更好地拟合图像。网格拟合和优化是在本地执行的,最终的网格是非线性(逐段仿射)网格。为了处理图像中的极端损坏,初始网格参数估计和网格拟合步骤采用了健壮的搜索技术。所提出的方法没有任何需要调整的自由参数。该方法甚至在存在大量伪像和失真的情况下也能够识别网格结构。呈现了各种图像的评估结果。

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