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Spot Edge Detection in Microarray Images Using Bi-Dimensional Empirical Mode Decomposition

机译:使用双维经验模式分解在微阵列图像中的专出边缘检测

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A Deoxyribonucleic Acid (DNA) microarray is a collection of microscopic DNA spots attached to a solid surface, such as glass, plastic or silicon chip forming an array. The analysis of DNA microarray images allows the identification of gene expressions to draw biological conclusions for applications ranging from genetic profiling to diagnosis of cancer. The DNA microarray image analysis includes three tasks: gridding, segmentation and intensity extraction. During the processing of microarray images, the irregularities of spot position and shape could generate significant errors. This paper presents an edge detection method using Bi-dimensional Empirical Mode Decomposition. Application of edge detection technology on separating spots form the background decreases the probability of errors and gives more accurate information about the states of spots. The proposed method identifies the spots with low density, thus increasing the performance of microarray images.
机译:脱氧核糖核酸(DNA)微阵列是连接到固体表面的微观DNA斑点的集合,例如玻璃,塑料或硅芯片形成阵列。 DNA微阵列图像的分析允许鉴定基因表达以吸引从遗传分析到诊断癌症的应用的生物结论。 DNA微阵列图像分析包括三个任务:网格,分段和强度提取。在处理微阵列图像期间,点位置和形状的不规则可能产生重大误差。本文介绍了使用双维经验模式分解的边缘检测方法。边缘检测技术在分离点形成背景下的应用降低了错误的概率,并提供了关于斑点状态的更准确的信息。所提出的方法识别具有低密度的斑点,从而提高了微阵列图像的性能。

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