Title :
An improved automatic gridding method for cDNA microarray images
Author :
Guifang Shao ; Tingna Wang ; Zhigang Chen ; Yushu Huang ; Yuhua Wen
Author_Institution :
Dept. of Autom., Xiamen Univ., Xiamen, China
Abstract :
Gridding, which has a large impact on the identification of differentially expressed genes, is the first and key step for microarray image analysis. Most gridding methods are semi-automatic or require parameter preset. In this paper, an improved method was proposed for rapid and accurate gridding compared to the mathematical morphology based method. First, the image quality was enhanced by using the logarithm transformation. Then, an optimal threshold was gained based on Otsu method. Experiments on microarray images drawn from SMD and GEO prove that our method is fully automatic and need no parameter, with high accuracy in the presence of lots of noise.
Keywords :
biology computing; image segmentation; lab-on-a-chip; GEO; Otsu method; SMD; cDNA microarray image analysis; differentially expressed gene identification; image quality; improved automatic gridding method; logarithm transformation; mathematical morphology based method; optimal threshold; Accuracy; Bioinformatics; DNA; Image segmentation; Morphology; Noise; Support vector machines;
Conference_Titel :
Pattern Recognition (ICPR), 2012 21st International Conference on
Conference_Location :
Tsukuba
Print_ISBN :
978-1-4673-2216-4