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Ad-Hoc Segmentation Pipeline for Microarray Image Analysis

机译:用于芯片图像分析的Ad-Hoc分割管道

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Microarray is a new class of biotechnologies able to help biologist researches to extrapolate new knowledge from biological experiments. Image Analysis is devoted to extrapolate, process and visualize image information. For this reason it has found application also in Microarray, where it is a crucial step of this technology (e.g. segmentation). In this paper we describe MISP (Microarray Image Segmentation Pipeline), a new segmentation pipeline for Microarray Image Analysis. The pipeline uses a recent segmentation algorithm based on statistical analysis coupled with K-Means algorithm. The Spot masks produced by MISP are used to determinate spots information and quality measures. A software prototype system has been developed; it includes visualization, segmentation, information and quality measure extraction. Experiments show the effectiveness of the proposed pipeline both in terms of visual accuracy and measured quality values. Comparisons with existing solutions (e.g. Scanalyze) confirm the improvement with respect to previously published works.
机译:微阵列是一类新的生物技术,能够帮助生物学家研究从生物实验中推断出新知识。图像分析致力于外推,处理和可视化图像信息。因此,它也已经在微阵列中找到了应用,这是该技术的关键步骤(例如,分割)。在本文中,我们描述了MISP(微阵列图像分割管道),这是一种用于微阵列图像分析的新型分割管道。管道使用基于统计分析的最新分段算法以及K-Means算法。 MISP生产的点罩用于确定点信息和质量度量。开发了软件原型系统;它包括可视化,细分,信息和质量度量提取。实验从视觉准确性和测得的质量值两方面显示了所提议管道的有效性。与现有解决方案(例如Scanalyze)的比较证实了相对于先前发表的作品的改进。

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