A comparative study of goodness-of-fit tests for multivariate normality
Journal of Multivariate Analysis
A Parametric Texture Model Based on Joint Statistics of Complex Wavelet Coefficients
International Journal of Computer Vision - Special issue on statistical and computational theories of vision: modeling, learning, sampling and computing, Part I
Image Analysis for Detecting Faulty Spots from Microarray Images
DS '02 Proceedings of the 5th International Conference on Discovery Science
Microarray image compression: SLOCO and the effect of information loss
Signal Processing - Special issue: Genomic signal processing
Complex Daubechies wavelets: properties and statistical image modelling
Signal Processing
Efficiently Mining Gene Expression Data via a Novel Parameterless Clustering Method
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Correlation Statistics for cDNA Microarray Image Analysis
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Journal of Biomedical Informatics
Probability Distributions Involving Gaussian Random Variables: A Handbook for Engineers, Scientists and Mathematicians
On denoising and compression of DNA microarray images
Pattern Recognition
Data-Dependent Kernel Machines for Microarray Data Classification
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
cDNA microarray image processing using fuzzy vector filtering framework
Fuzzy Sets and Systems
Bivariate shrinkage functions for wavelet-based denoising exploiting interscale dependency
IEEE Transactions on Signal Processing
A new framework for complex wavelet transforms
IEEE Transactions on Signal Processing
The design of approximate Hilbert transform pairs of wavelet bases
IEEE Transactions on Signal Processing
Spatially adaptive wavelet thresholding with context modeling for image denoising
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Image denoising using scale mixtures of Gaussians in the wavelet domain
IEEE Transactions on Image Processing
Building robust wavelet estimators for multicomponent images using Stein's principle
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Image Modeling Using Interscale Phase Properties of Complex Wavelet Coefficients
IEEE Transactions on Image Processing
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Noise reduction is an essential step of cDNA microarray image analysis for obtaining better-quality gene expression measurements. Wavelet-based denoising methods have shown significant success in traditional image processing. The complex wavelet transform (CWT) is preferred to the classical discrete wavelet transform for denoising of microarray images due to its improved directional selectivity for better representation of the circular edges of spots and near shift-invariance property. Existing CWT-based denoising methods are not efficient for microarray image processing because they fail to take into account the signal as well as noise correlations that exist between red and green channel images. In this paper, two bivariate estimators are developed for the CWT-based denoising of microarray images using the standard maximum a posteriori and linear minimum mean squared error estimation criteria. The proposed denoising methods are capable of taking into account both the interchannel signal and noise correlations. Significance of the proposed denoising methods is assessed by examining the effect of noise reduction on the estimation of the log-intensity ratio. Extensive experimentations are carried out to show that the proposed methods provide better noise reduction of microarray images leading to more accurate estimation of the log-intensity ratios as compared to the other CWT-based denoising methods.