Automatic Gridding Method for Microarray Images

A cDNA microarray is a powerful tool in biotechnology providing useful information in analyzing thousands of gene expressions simultaneously. The analysis of microarray images allows the identification of gene expressions to draw biological conclusions for applications ranging from genetic profiling to diagnosis of cancer. The DNA microarray image analysis includes three tasks: gridding, segmentation and intensity extraction. The gridding process is usually divided into two main steps: sub-gridding and spot detection. Most existing gridding algorithms are semiautomatic requiring human intervention and parameter presetting. Each spot is associated with a gene and contains the pixels that indicate the level of expression of that particular gene In addition, improper gridding will affect image analysis in extracting intensity values from each spot that represents gene expression level. In this paper, a fully automatic approach to sub-gridding and spot detection is presented. After gridding, the image is segmented using fuzzy c-means clustering algorithm for separation of spots from the background pixels. The result of the experiment shows that the method presented in this paper is accurate and automatic without human intervention and parameter presetting.