基于偏移向量场和期望最大化算法的微阵列图像处理

G. Weng, Jian Su
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引用次数: 4

摘要

DNA微阵列提供了一种简单的工具,可以同时识别和量化成千上万个基因的基因表达。图像处理是微阵列实验的重要步骤。提出了一种基于偏移向量场的去除基因噪声的新方法,并利用期望最大化算法对基因进行分割。仿真结果表明,该方法对微阵列图像的滤波和分割具有较好的效果。实验结果在计算上具有吸引力,具有良好的性能,可以在有效抑制噪声的同时保留斑点数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Microarray Images Processing Using the Offset Vector Field and Expectation Maximization Algorithm
DNA microarrays provide a simple tool to identify and quantify the gene expression for tens of thousands of genes simultaneously. Image processing is an important step in microarrays experiments. This paper presents a novel technique for removing gene's noises based on the offset vector field and segmenting genes using the expectation maximization algorithm. Simulations show that the new technique for microarray images filtering and segmentation has better performance than most of the common ways. The results of experiments are computationally attractive, have excellent performance and can preserve spots' data while efficiently suppress noises.
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