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On the noise attenuation in DNA microarray images

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In this paper a novel method of noise reduction in color images is presented. The new technique is capable of attenuating both impulsive and Gaussian noise, while preserving and even enhancing sharpness of the image edges. Extensive simulations reveal that the new method outperforms significantly the standard techniques widely used in multivariate signal processing. In this work we apply the new noise reduction method for the enhancement of the images of gene chips. We demonstrate that the new technique is capable of reducing various kinds of noise present in microarray images and that it enables efficient spot location and estimation of the gene expression level due to the smoothing effect and preservation of the spot edges. This paper contains the comparison of the new technique of noise reduction with the standard procedures used for the processing of vector valued images, as well as examples of the efficiency of the new algorithm when applied to typical microarray images.
Rocznik
Strony
MI19--MI27
Opis fizyczny
Bibliogr. 16 poz., rys., tab., wykr.
Twórcy
autor
  • Silesian University of Technology, Department of Automatic Control, Akademicka 16 Str, 44-101 Gliwice, Poland
  • Silesian University of Technology, Department of Automatic Control, Akademicka 16 Str, 44-101 Gliwice, Poland
  • Silesian University of Technology, Department of Automatic Control, Akademicka 16 Str, 44-101 Gliwice, Poland
  • Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto,10 King's College Road, Toronto, Canada,
Bibliografia
  • [1] Astola J., Haavisto P., Neuovo Y., (1990) Vector median filters, IEEE Proc., 78, 678-689
  • [2] Borgefors G., (1986) Distances transformations in digital images, Computer Vision, Graphics and Imagt Processing, 34:334-371
  • [3] Chen Y., Dougherty E. R., Bittner M. L., (1997) Ratio-based decisions and the quantitative analysis of cDNA microarray images, Journal of Biomedical Optics, 2, 4, 364-374
  • [4] Chu S., DeRisi j., Eisen M., Mulholland J., Bottstein D., Brown P.O., Herskowitz I., (1998) The transcriptiona program of sporulation in budding yeast, Science, 282, 699-705
  • [5] Eisen M. B., Brown P. 0., (1999) DNA arrays for analysis of gene expression, Methods in Enzymology, 303, 179-205
  • [6] Heijmans H., (1995) Mathematical Morphology: Basic Principles, Proceedings of the Summer School or Morphological Image and Signal Processing, Zakopane, Poland
  • [7] Matheron G., (1975) Random Sets and Integral Geometry, New York, John Willey
  • [8] Pitas I., Tsakalides P., (1991) Multivariate ordering in color image processing, IEEE Trans. on Circuits anc Systems for Video Technology, 1, 3, 247-256
  • [9] Pitas I., Venetsanopoulos A. N, (1990) Nonlinear Digital Filters: Principles and Applications, Kluwer, Boston, MA,
  • [10] Pitas I., Venetsanopoulos A.N., (1992) Order statistics in digital image processing, Proceedings of IEEE, 80, 12. 1893-1923
  • [11] Plataniotis K.N., Venetsanopoulos A.N., (June 2000) Color Image Processing and Applications, Springer Verlag
  • [12] Schena M., Shalon D., Davis R. W., Brown P.O., (1995) Quantitative monitoring of gene expression patterns with a complimentary DNA microarray, Science 270, 467-470
  • [13] Schmitt M., Lecture Notes on Geodesy and Morphological Measurements, Proceedings of the Summer School on Morphological Image and Signal Processing, Zakopane, Poland (1995)
  • [14] Smolka B., Wojciechowski K., (2001) Random walk approach to image enhancement, Signal Processing, Vol. 81, No. 4
  • [15] Toivanen P.J., (1996) New geodesic distance transforms for gray scale images, Pattern Recognition Letters, 17, 437-450
  • [16] Venetsanopoulos A.N., Plataniotis K.N., (1995) Multichannel image processing, Proceedings of the IEEE Workshop on Nonlinear Signal/Image Processing, 2-6
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-fd981e73-b7ce-42f0-bfd6-94d90cfbc625
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