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An improved automatic gridding method for cDNA microarray images

机译:改进的cDNA微阵列图像自动网格化方法

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Gridding, which has a large impact on the identification of differentially expressed genes, is the first and key step for microarray image analysis. Most gridding methods are semi-automatic or require parameter preset. In this paper, an improved method was proposed for rapid and accurate gridding compared to the mathematical morphology based method. First, the image quality was enhanced by using the logarithm transformation. Then, an optimal threshold was gained based on Otsu method. Experiments on microarray images drawn from SMD and GEO prove that our method is fully automatic and need no parameter, with high accuracy in the presence of lots of noise.
机译:网格化对差异表达基因的识别有很大影响,是微阵列图像分析的第一步也是关键步骤。大多数网格化方法是半自动的或需要参数预设的。与基于数学形态学的方法相比,本文提出了一种改进的方法,用于快速,准确的网格化。首先,通过使用对数变换来提高图像质量。然后,基于大津法获得了最佳阈值。从SMD和GEO提取的微阵列图像的实验证明,我们的方法是全自动的,不需要任何参数,在存在大量噪声的情况下具有很高的精度。

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