Microarray image enhancement by denoising using stationary wavelet transform

X. H. Wang*, Robert S.H. Istepanian, Yong Hua Song

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

172 Citations (Scopus)

Abstract

Microarray imaging is considered an important tool for large scale analysis of gene expression. The accuracy of the gene expression depends on the experiment itself and further image processing. It's well known that the noises introduced during the experiment will greatly affect the accuracy of the gene expression. How to eliminate the effect of the noise constitutes a challenging problem in microarray analysis. Traditionally, statistical methods are used to estimate the noises while the microarray images are being processed. In this paper, we present a new approach to deal with the noise inherent in the microarray image processing procedure. That is, to denoise the image noises before further image processing using stationary wavelet transform (SWT). The time invariant characteristic of SWT is particularly useful in image denoising. The testing result on sample microarray images has shown an enhanced image quality. The results also show that it has a superior performance than conventional discrete wavelet transform and widely used adaptive Wiener filter in this procedure.

Original languageEnglish
Pages (from-to)184-189
Number of pages6
JournalIEEE Transactions on Nanobioscience
Volume2
Issue number4
DOIs
Publication statusPublished - Dec 2003
Externally publishedYes

Keywords

  • Denoising
  • Microarray images
  • Stationary wavelet transform

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