cDNA Microarray Genome Image Processing Using Fixed Spot Position

cDNA Microarray Genome Image Processing Using Fixed Spot Position

Complementary DNA (cDNA) microarray is one of the most recent and important technology for exploring the genome. cDNA microarray Image analysis aims to measure the intensity for each spot in the scanned image and this intensity represents the amount of a specific gene in the studied cell. This paper presents a new algorithm that achieves an automated way for applying grid in the cDNA microarray...

cDNA microarray image processing using fuzzy vector filtering framework

This paper presents a novel filtering framework capable of processing cDNA microarray images. The proposed two-component adaptive vector filters integrate well-known concepts from the areas of fuzzy set theory, nonlinear filtering, multidimensional scaling and robust order-statistics. By appropriately setting the weighting coefficients in a generalized framework, the method is capable of removi...

cDNA microarray image segmentation using root signals

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 regula...

Spotted cDNA microarray image segmentation using ACWE

The segmentation of the picture (and, implicitly, the segmentation method used) is one of the three important steps in microarray image processing, together with spot gridding and information extraction. It directly affects the accuracy of gene expression analysis in the data mining process that follows. In 2001 a segmentation method for arbitrary pictures using the Active Contours Without Edge...

cDNA Microarray Data Normalization