scholarly journals A novel method using edge detection for signal extraction from cDNA microarray image analysis

2001 ◽  
Vol 33 (2) ◽  
pp. 83-88 ◽  
Author(s):  
Jin Hyuk Kim ◽  
Hye Young Kim ◽  
Yong Sung Lee
Keyword(s):  
Image Analysis ◽  
Edge Detection ◽  
Cdna Microarray ◽  
Signal Extraction ◽  
Microarray Image ◽  
Novel Method

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.

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