IEEE J Biomed Health Inform - Microarray image denoising using complex Gaussian scale mixtures of complex wavelets.

Tópicos

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Resumo

Microarray images when contaminated with noise may severely affect the detection and quantification of gene expression. In this paper, we propose to use the complex Gaussian scale mixture (CGSM) model in complex wavelet domain for noise reduction in complementary DNA microarray images. Based on the joint information in the red and green channel microarray images, we model the complex wavelet coefficients of the channel images jointly using the CGSM, and subsequently perform image denoising using Bayes least square estimator in complex wavelet domain. The experimental results show that using the CGSM of complex wavelet coefficients provides better noise reduction of microarray images compared to other complex wavelet-based models.

Resumo Limpo

microarray imag contamin nois may sever affect detect quantif gene express paper propos use complex gaussian scale mixtur cgsm model complex wavelet domain nois reduct complementari dna microarray imag base joint inform red green channel microarray imag model complex wavelet coeffici channel imag joint use cgsm subsequ perform imag denois use bay least squar estim complex wavelet domain experiment result show use cgsm complex wavelet coeffici provid better nois reduct microarray imag compar complex waveletbas model

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