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Fuzzy Vector Filters for cDNA Microarray Image Processing

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Fuzzy Systems in Bioinformatics and Computational Biology

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 242))

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Summary

A data-adaptive fuzzy filtering framework is designed to remove noise in microarray images without the requirement for fuzzy rules and local statistics estimation, or under unrealistic assumptions that the original signal is available. This is achieved by utilizing the inference engine in the form of transformed distance metrics between the samples within the supporting window. The training of the filter coefficients is thus based on local image features. Proposed fuzzy filters can preserve important structural elements and eliminate degradations introduced during microarray image formation.

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References

  1. Adjeroh, D.A., Zhang, Y., Parthe, R.: On denoising and compression of DNA microarray images. Pattern Recognition 39, 2478–2493 (2006)

    Article  MATH  Google Scholar 

  2. Ajay, N., Tokuyasu, T., Snijders, A., Segraves, R., Albertson, D., Pinkel, D.: Fully automatic quantification of microarray image data. Genome Research 12, 325–332 (2002)

    Article  Google Scholar 

  3. Alfano, R.R., Yang, Y.: Stokes shift emission spectroscopy of human tissue and key biomolecules. IEEE Journal of Selected Topics in Quantum Electronics 9, 48–152 (2003)

    Google Scholar 

  4. Arakawa, K.: Median filters based on fuzzy rules and its application to image processing. Fuzzy Sets and Systems 77, 3–13 (1996)

    Article  Google Scholar 

  5. Arena, P., Bucolo, M., Fortuna, L., Occhipinty, L.: Celular neural networks for real-time DNA microarray analysis. IEEE Engineering in Medicine and Biology 21, 17–25 (2002)

    Article  Google Scholar 

  6. Bajcsy, P.: Gridline: Automatic grid allignment in DNA microarray scans. IEEE Transactions on Image Processing 13, 15–25 (2004)

    Article  Google Scholar 

  7. Chen, Y., Dougherty, E., Bittner, M.: Ratio-based decisions and the quantitative analysis cDNA microarray images. Journal of Biomedical Optics 2, 364–374 (1997)

    Article  Google Scholar 

  8. Damiance, A.P.G., Zhao, L., Carvalho, A.C.: A dynamic model with adaptive pixel moving for microarray images segmentation. Real-Time Imaging 10, 189–195 (2004)

    Article  Google Scholar 

  9. Eisen, M.B., Brown, P.O.: DNA arrays for analysis of gene expression. Methods in Enzymology 303, 179–205 (1999)

    Article  Google Scholar 

  10. Filkov, V., Skiena, S., Zhi, J.: Analysis techniques for microarray time-series data. Journal of Computational Biology 9, 317–330 (2002)

    Article  Google Scholar 

  11. Goldberg, D.: Genetic algorithms in search, optimisation, and machine learning. Addison-Wesley, Reading (1989)

    Google Scholar 

  12. Hirata, R., Barrera, J., Hashimoto, R.F., Dantas, D.O., Esteves, G.H.: Segmentation of microarray images by mathematical morphology. Real-Time Imaging 8, 491–505 (2002)

    Article  MATH  Google Scholar 

  13. Hou, L.R., Yi, Z.: Fuzzy logic controller based on genetic algorithms. Fuzzy Sets and Systems 83, 1–10 (1996)

    Article  Google Scholar 

  14. Istepanian, R.S.H.: Microarray image processing: Current status and future directions. IEEE Transactions on Nanobioscience 2, 173–175 (2003)

    Article  Google Scholar 

  15. Katzer, M., Kummert, F., Sagerer, G.: Methods for automatic microarray image segmentation. IEEE Transactions on Nanobioscience 2, 202–213 (2003)

    Article  Google Scholar 

  16. Khriji, L., Gabbouj, M.: Adaptive fuzzy order statistics-rational hybrid filters for color image processing. Fuzzy sets and Systems 128, 35–46 (2002)

    Article  MATH  Google Scholar 

  17. Kim, J.H., Kim, H.Y., Lee, Y.S.: A novel method using edge detection for signal extraction from cDNA microarray image analysis. Experimental and Molecular Medicine 33, 83–88 (2001)

    Google Scholar 

  18. Kim, J.H., Shin, D.M., Lee, Y.S.: Effect of local background intensities in the normalization of cDNA microarray data with a skewed expression profiles. Experimental and Molecular Medicine 34, 224–232 (2002)

    Google Scholar 

  19. Liew, A.W.C., Yana, H., Yang, M.: Robust adaptive spot segmentation of DNA microarray images. Pattern Recognition 36, 1251–1254 (2003)

    Article  Google Scholar 

  20. Lukac, R., Plataniotis, K.N., Smolka, B., Venetsanopoulos, A.N.: A multichannel order-statistic technique for cDNA microarray image processing. IEEE Transactions on Nanobioscience 3, 272–285 (2004)

    Article  Google Scholar 

  21. Lukac, R., Plataniotis, K.N., Smolka, B., Venetsanopoulos, A.N.: cDNA microarray image processing using fuzzy vector filtering framework. Journal of Fuzzy Sets and Systems 152, 17–35 (2005)

    Article  MATH  MathSciNet  Google Scholar 

  22. Lukac, R., Smolka, B., Martin, K., Plataniotis, K.N., Venetsanopulos, A.N.: Vector filtering for color imaging. IEEE Signal Processing Magazine 22, 74–86 (2005)

    Article  Google Scholar 

  23. Lukac, R., Plataniotis, K.N.: cDNA microarray image segmentation using root signals. International Journal of Imaging Systems and Technology 16, 51–64 (2006)

    Article  Google Scholar 

  24. Lukac, R., Plataniotis, K.N.: A taxonomy of color image filtering and enhancement solutions. In: Hawkes, P.W. (ed.) Advances in imaging and electron physics, vol. 140, pp. 187–264. Elsevier / Academic Press, San Diego (2006)

    Google Scholar 

  25. Lukac, R., Plataniotis, K.N.: Vector edge operators for cDNA microarray spot localization. Computerized Medical Imaging and Graphics 31, 510–522 (2007)

    Article  Google Scholar 

  26. Nagarajan, R.: Intensity-based segmentation of microarrays images. IEEE Transactions on Medical Imaging 22, 882–889 (2003)

    Article  Google Scholar 

  27. Nagarajan, R., Upreti, M.: Correlation statistics for cDNA microarray image analysis. IEEE/ACM Transactions in Computational Biology and Bioinformatics 3, 232–238 (2006)

    Article  Google Scholar 

  28. O’Neill, P., Magoulas, G.D.: Improved processing of microarray data using image reconstruction techniques. IEEE Transactions on Nanobioscience 2, 176–183 (2003)

    Article  Google Scholar 

  29. Pickett, S.C.: Understanding and evaluating fluorescent microarray imaging instruments, IVD Technology (2003)

    Google Scholar 

  30. Pitas, I., Venetsanopoulos, A.N.: Order statistics in digital image processing. Proceedings of the IEEE 80, 1892–1919 (1992)

    Article  Google Scholar 

  31. Plataniotis, K.N., Androutsos, D., Venetsanopoulos, A.N.: Adaptive fuzzy systems for multichannel signal processing. Proceedings of the IEEE 87, 1601–1622 (1999)

    Article  Google Scholar 

  32. Plataniotis, K.N., Venetsanopoulos, A.N.: Color image processing and applications. Springer, Berlin (2000)

    Google Scholar 

  33. Russo, F., Ramponi, G.: A fuzzy filter for images corrupted by impulse noise. IEEE Signal Processing Letters 3, 168–170 (1996)

    Article  Google Scholar 

  34. Schena, M.: Microarray biochip technology. Eaton Publishing Company / Biotechniques Books (2000)

    Google Scholar 

  35. Tang, K., Astola, J., Neuvo, Y.: Nonlinear multivariate image filtering techniques. IEEE Transactions on Image Processing 4, 788–798 (1995)

    Article  Google Scholar 

  36. Tsai, H.H., Yu, P.T.: Genetic-based fuzzy hybrid multichannel filters for color image restoration. Fuzzy Sets and Systems 114, 203–224 (2000)

    Article  MATH  Google Scholar 

  37. Wang, X., Ghosh, S., Guo, S.W.: Quantitative quality control in microarray processing and data acquisition. Nucleic Acids Research 29, 1–8 (2001)

    Article  MATH  Google Scholar 

  38. Wang, Y., Lu, J., Lee, R., Gu, Z., Clarke, R.: Iterative normalization of CDNA microarray data. IEEE Transactions on Information Technology in Biomedicine 6, 29–37 (2002)

    Article  Google Scholar 

  39. Wang, X.H., Istepian, R.S.H., Song, Y.H.: Microarray image enhancement using stationary wavelet transform. IEEE Transactions on Nanobioscience 2, 184–189 (2003)

    Article  Google Scholar 

  40. Whitchurch, A.K.: Gene expression microarrays. IEEE Potentials 21, 30–34 (2002)

    Article  Google Scholar 

  41. Yang, Y.H., Buckley, M.J., Dudoit, S., Speed, T.P.: Comparison of methods for image analysis on cDNA microarray data. Journal of Computational and Graphical Statistics 11, 108–136 (2002)

    Article  MathSciNet  Google Scholar 

  42. Zhang, X.Y., Chen, F., Zhang, Y.T., Agner, S.G., Akay, M., Lu, Z.H., Waye, M.M.Y., Tsui, S.K.W.: Signal processing techniques in genomic engineering. Proceedings of the IEEE 90, 1822–1833 (2002)

    Article  Google Scholar 

  43. Zheng, J., Valavanis, K.P., Gauch, J.M.: Noise removal from color images. Journal of Intelligent and Robotic Systems 7, 257–285 (1993)

    Article  Google Scholar 

  44. Zilouchian, A., Jamshidi, M.: Intelligent control systems using soft computing methodology. CRC Press, Boca Raton (2001)

    Book  Google Scholar 

  45. Zimmermann, H.: Fuzzy set theory and its applications, 2nd edn. Kluwer Academic Publishers, Dordrecht (1991)

    MATH  Google Scholar 

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Author information

Authors and Affiliations

  1. Epson Edge, 3771 Victoria Park Avenue, Toronto, Ontario, M1W 3Z5, Canada

    Rastislav Lukac

  2. The Edward S. Rogers Sr. Department of ECE, University of Toronto, 10 King’s College Road, Toronto, Ontario, M5S 3G4, Canada

    Konstantinos N. Plataniotis

Authors
  1. Rastislav Lukac
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  2. Konstantinos N. Plataniotis
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Editor information

Editors and Affiliations

  1. Honda Research Institute Honda Research Institute Europe , Offenbach, Germany

    Yaochu Jin

  2. Nanyang Technological University, Singapore

    Lipo Wang

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© 2009 Springer-Verlag Berlin Heidelberg

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Lukac, R., Plataniotis, K.N. (2009). Fuzzy Vector Filters for cDNA Microarray Image Processing. In: Jin, Y., Wang, L. (eds) Fuzzy Systems in Bioinformatics and Computational Biology. Studies in Fuzziness and Soft Computing, vol 242. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89968-6_4

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  • DOI: https://doi.org/10.1007/978-3-540-89968-6_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-89967-9

  • Online ISBN: 978-3-540-89968-6

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