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Noise Removal using Empirical Mode Decomposition and Wavelet Transform in Microarray Images

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International Journal of Computer Applications
© 2013 by IJCA Journal
Volume 68 - Number 2
Year of Publication: 2013
Authors:
D. Rama Krishna
J. Harikiran
P. V. Lakshmi
K. Ramesh
10.5120/11548-6822

Rama D Krishna, J Harikiran, P V Lakshmi and K Ramesh. Article: Noise Removal using Empirical Mode Decomposition and Wavelet Transform in Microarray Images. International Journal of Computer Applications 68(2):1-7, April 2013. Full text available. BibTeX

@article{key:article,
	author = {D. Rama Krishna and J. Harikiran and P. V. Lakshmi and K. Ramesh},
	title = {Article: Noise Removal using Empirical Mode Decomposition and Wavelet Transform in Microarray Images},
	journal = {International Journal of Computer Applications},
	year = {2013},
	volume = {68},
	number = {2},
	pages = {1-7},
	month = {April},
	note = {Full text available}
}

Abstract

A Deoxyribonucleic Acid (DNA) microarray is a collection of microscopic DNA spots attached to a solid surface, such as glass, plastic or silicon chip forming an array. The analysis of DNA microarray images allows the identification of gene expressions to draw biological conclusions for applications ranging from genetic profiling to diagnosis of cancer. The DNA microarray image analysis includes three tasks: gridding, segmentation and intensity extraction. In this paper, a method for noise removal in microarray image using Bi-dimensional Empirical Mode Decomposition (BEMD) is presented. The BEMD decomposes the image into IMFs and residual components. Then, the selected high frequency IMFs are de-noised with wavelet model and finally the BEMD reconstruction gives the de-noised image. The experimental results show the proposed algorithm can perform significantly better in terms of noise suppression and detail preservation in microarray images.

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