cDNA microarray image processing using mathematical morphological segmentation

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. It can affect subsequent analysis such as identification of differentially expressed genes. Microarray image analysis includes three tasks: spot gridding, segmentation and information extraction. This paper presents a new algorithm that achieves an automated way for applying mathematical morphology and morphological segmentation. It compares experimental results with those obtained from the widely used software GenePixPro (USA), Angulo J (France) and Hongwei Li (China). The result of experiment shows that it is robustness and precision. The way is adaptive to different shape, conglutination and deviant spot image.

[1]  Edward R. Dougherty,et al.  Hands-on Morphological Image Processing , 2003 .

[2]  A. Weeraratna,et al.  Gene Expression Profiling: From Microarrays to Medicine , 2004, Journal of Clinical Immunology.

[3]  R. Istepanian Microarray image processing: current status and future directions , 2003, IEEE Transactions on NanoBioscience.

[4]  Rafael C. González,et al.  Digital image processing using MATLAB , 2006 .

[5]  Ye Fang Microarray Images Analysis Using Mathematical Morphology , 2007 .

[6]  Junior Barrera,et al.  Microarray gridding by mathematical morphology , 2001, Proceedings XIV Brazilian Symposium on Computer Graphics and Image Processing.

[7]  Claudio Nicolini,et al.  DNASER I: layout and data analysis. , 2002, IEEE transactions on nanobioscience.

[8]  Jesús Angulo,et al.  Automatic analysis of DNA microarray images using mathematical morphology , 2003, Bioinform..