PERFORMANCE EVALUATION OF DNA MICROARRAY GRIDDING ALGORITHMS FOR DETERMINING OF HUMAN CANCEROUS CELLS

DNA microarray is a very useful way to simultaneously study express level of thousands of genes in a simple test. In a microarray test, the average value of fluorescent intensity is calculated. Calculated intensity values are very close to express levels of a specific gene. Thus, appropriately determining location of each spot (specific gene) leads to an accurate measurement of intensity value and as a result accurate classification of healthy and unhealthy (cancerous) cells in a microarray image. In this paper, different DNA microarray images networking algorithms is studied. Then three optimal algorithms based on mathematical morphology, cross correlation and local parameters estimation are presented and their performances are compared. Implementation results in MATLAB work space shows that proposed algorithms contain high accuracy when reticulating microarray cells and also good stability against all types of noises in images.