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A microarray image gridding method based on image projection difference sequences analysis and local extrema searching

机译:基于图像投影差异序列分析和局部极值搜索的微阵列图像网格化方法

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Microarray image gridding is one important step of microarray image analysis to determine 2D image coordinates of all array spots in the hybridized gene chip image. Accuracy of microarray image gridding will affect the reliability of gene-chip data extraction and even the final analysis results of gene-chip assays. However, in recent years, many new microarray image gridding methods presented have higher accuracy but have more computation complexity than those precedented ones. To promote gridding accuracy and decrease computation complexity simultaneously, we presented a novel and simple microarray image gridding method based on image projection sequences analysis and local extrema searching. Firstly we transformed 2D microarray image into vertical and horizontal 1D projection sequences, secondly utilized signal processing methods of low pass filtering and zero mean to filtered projection sequences, thirdly computed the first-order difference and second-order difference for the smoothed signals, and finally realized microarray image gridding according to the local extrema of difference sequences and span information of spots array on the microarray image. The subsequent gridding experiments showed that this method had met the requirements of computing accuracy and efficiency of microarray image gridding.
机译:微阵列图像网格化是微阵列图像分析中确定杂交基因芯片图像中所有阵列点的2D图像坐标的重要步骤。微阵列图像网格化的准确性将影响基因芯片数据提取的可靠性,甚至会影响基因芯片分析的最终分析结果。然而,近年来,提出的许多新的微阵列图像网格化方法比先前的方法具有更高的准确性,但是具有更高的计算复杂度。为了提高网格划分的准确性并降低计算复杂度,我们提出了一种基于图像投影序列分析和局部极值搜索的新颖,简单的微阵列图像网格划分方法。首先我们将二维微阵列图像转换为垂直和水平一维投影序列,其次利用低通滤波和零均值的信号处理方法对滤波后的投影序列进行处理,然后再对平滑后的信号计算一阶差分和二阶差分,最后根据差异序列的局部极值和微阵列图像上点阵列的跨度信息实现微阵列图像网格化。后续的网格实验表明,该方法满足了计算精度和微阵列图像网格化效率的要求。

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