cDNA Microarray Image Processing Using Morphological Operator and Edge-Enhancing Diffusion

Abstract

Complementary DNA (cDNA) microarray imaging technology is a revolutionary innovation for genomic research that allows monitoring of expression levels for thousands of genes simultaneously. The raw data of cDNA microarray is shown as red and green channel images that are quantitatively analysed to obtain the gene expression measurements. It can affect the subsequent analysis such as identification of genes differentially expressed. cDNA microarray image analysis includes three tasks: image filtering, segmentation and information extraction. This paper presents a novel-filtering framework that is capable of processing cDNA microarray images. The experimental result is compared with those obtained from the widely used Gaussian de-noising techniques, wavelet de-noising techniques and morphological filtering technique. Simulation in this paper indicates that the proposed edge-enhancing diffusion filter and morphological operators are computationally attractive, yield excellent performance and are able to preserve structural information while efficiently suppressing noise in cDNA microarray data. The result of experiment shows that it is robust and precise.