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cDNA Microarray Image Segmentation Using Root Signals

机译:使用根信号的cDNA微阵列图像分割

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摘要

A vector processing based framework suitable for cDNA microarray image segmentation is introduced and analyzed in this paper. By using nonlinear, generalized selection vector filters the framework proposed here classifies the cDNA image data as either microarray spots or image background. The solution converges to a root signal that represents the segmented cDNA microarray image with the regular spots ideally separated from the background and with their coloration uniquely described by dominant color vectors. It will be demonstrated that the framework readily unifies image denois-ing, enhancement, data normalization, irregular spot rejection, and spot segmentation in one processing step delivering excellent performance at reasonable computational cost.
机译:本文介绍并分析了一种适用于cDNA微阵列图像分割的基于向量处理的框架。通过使用非线性,广义选择向量滤波器,此处提出的框架将cDNA图像数据分类为微阵列斑点或图像背景。该解决方案收敛到一个代表分割的cDNA微阵列图像的根信号,该信号具有理想的与背景分离的规则斑点,并且其显色由主要颜色向量唯一描述。将会证明,该框架可以在一个处理步骤中轻松地将图像去噪,增强,数据归一化,不规则斑点剔除和斑点分割统一起来,以合理的计算成本提供出色的性能。

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