An Automated Gridding and Segmentation Method for cDNA Microarray Image Analysis

2006 ◽  
Author(s):  
Wei-Bang Chen ◽  
Chengcui Zhang ◽  
Wen-Lin Liu
Keyword(s):  
Image Analysis ◽  
Cdna Microarray ◽  
Segmentation Method ◽  
Microarray Image

Segmentation of cDNA Microarray Image Using Fuzzy c-Mean Algorithm and Mathematical Morphology

2011 ◽  
Vol 464 ◽  
pp. 159-162 ◽  
Author(s):  
Zhi Yao Li ◽  
Gui Rong Weng
Keyword(s):  
Image Analysis ◽  
Image Segmentation ◽  
Cdna Microarray ◽  
Glass Slide ◽  
Sequence Information ◽  
Microarray Technology ◽  
Segmentation Method ◽  
Microarray Image ◽  
Adaptive Partitioning ◽  
Low Expression

cDNA microarray technology provides an effectual tool to explore the enormous genome. cDNA microarray consists of thousands of gene sequences which are printed on glass slide and these sequence information can be obtained by forming a microarray image. So image analysis is crucial. However, image segmentation is another key point. How to deal with the gene spots which are always comprised with imperfection such as irregular contours, donut shapes, artifact and spots with low expression is important to the robustness of the segmentation method. The paper proposed a method based on fuzzy c-mean algorithm which can effectively avoid the influence of various types of artifacts through adaptive partitioning.

Microarray Image Analysis and Gene Expression Ratio Statistics

2005 ◽  
pp. 1-21
Author(s):  
Yidong Chen ◽  
Edward R. Dougherty ◽  
Michael L. Bittner ◽  
Paul Meltzer ◽  
Jeffery Trent
Keyword(s):  
Gene Expression ◽  
Image Analysis ◽  
Expression Ratio ◽  
Microarray Image ◽  
Gene Expression Ratio
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