3-D Spot Modeling for Automatic Segmentation of cDNA Microarray Images

Morphological Spot Segmentation for Gene Microarray Images

DNA microarray technology is one of the most powerful techniques used in modern biology and is extensively used for identification of sequence (gene/gene mutation) and determination of gene expression. A typical microarray image consists of a few hundred to several thousand spots and the extent of hybridization of these spots determines the level of gene expression (abundance) in the sample. A ...

Segmentation of cDNA Microarray Images using Parallel Spectral Clustering

Microarray Image Microarray technology generates large amounts of expression level of genes to be analyzed simultaneously. This analysis implies microarray image segmentation to extract the quantitative information from spots. Spectral clustering is one of the most relevant unsupervised methods able to gather data without a priori information on shapes or locality. We propose and test on micro...

Segmentation of cDNA microarray images by kernel density estimation

The segmentation of cDNA microarray spots is essential in analyzing the intensities of microarray images for biological and medical investigation. In this work, nonparametric methods using kernel density estimation are applied to segment two-channel cDNA microarray images. This approach groups pixels into both a foreground and a background. The segmentation performance of this model is tested a...

A Spot Modeling Evolutionary Algorithm for Segmenting Microarray Images

Segmentation of Microarray cDNA Spots Using Markov Random Field Modeling

Motivation: Spot segmentation is a critical step in microarray gene expression data