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Spectroscopy: An International Journal
Volume 27 (2012), Article ID 530791, 7 pages
http://dx.doi.org/10.1155/2012/530791

Background Estimation of Biomedical Raman Spectra Using a Geometric Approach

1Department of Medical Physics, Medical School, University of Ioannina, Ioannina 45110, Greece
2Department of Physics, University of Ioannina, Ioannina 45110, Greece

Copyright © 2012 Nikolaos Kourkoumelis et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. C. A. Lieber and A. Mahadevan-Jansen, “Automated method for subtraction of fluorescence from biological Raman spectra,” Applied Spectroscopy, vol. 57, no. 11, pp. 1363–1367, 2003. View at Publisher · View at Google Scholar · View at Scopus
  2. B. D. Beier and A. J. Berger, “Method for automated background subtraction from Raman spectra containing known contaminants,” Analyst, vol. 134, no. 6, pp. 1198–1202, 2009. View at Publisher · View at Google Scholar · View at Scopus
  3. A. Jirasek, G. Schulze, M. M. L. Yu, M. W. Blades, and R. F. B. Turner, “Accuracy and precision of manual baseline determination,” Applied Spectroscopy, vol. 58, no. 12, pp. 1488–1499, 2004. View at Publisher · View at Google Scholar · View at Scopus
  4. V. Mazet, C. Carteret, D. Brie, J. Idier, and B. Humbert, “Background removal from spectra by designing and minimising a non-quadratic cost function,” Chemometrics and Intelligent Laboratory Systems, vol. 76, no. 2, pp. 121–133, 2005. View at Publisher · View at Google Scholar · View at Scopus
  5. M. N. Leger and A. G. Ryder, “Comparison of derivative preprocessing and automated polynomial baseline correction method for classification and quantification of narcotics in solid mixtures,” Applied Spectroscopy, vol. 60, no. 2, pp. 182–193, 2006. View at Publisher · View at Google Scholar · View at Scopus
  6. J. Zhao, H. Lui, D. I. Mclean, and H. Zeng, “Automated autofluorescence background subtraction algorithm for biomedical raman spectroscopy,” Applied Spectroscopy, vol. 61, no. 11, pp. 1225–1232, 2007. View at Publisher · View at Google Scholar · View at Scopus
  7. T. J. Vickers, R. E. Wambles, and C. K. Mann, “Curve fitting and linearity: data processing in Raman spectroscopy,” Applied Spectroscopy, vol. 55, no. 4, pp. 389–393, 2001. View at Publisher · View at Google Scholar · View at Scopus
  8. D. Zhang and D. Ben-Amotz, “Enhanced chemical classification of raman images in the presence of strong fluorescence interference,” Applied Spectroscopy, vol. 54, no. 9, pp. 1379–1383, 2000. View at Google Scholar · View at Scopus
  9. A. O'Grady, A. C. Dennis, D. Denvir, J. J. McGarvey, and S. E. J. Bell, “Quantitative Raman spectroscopy of highly fluorescent samples using pseudosecond derivatives and multivariate analysis,” Analytical Chemistry, vol. 73, no. 9, pp. 2058–2065, 2001. View at Publisher · View at Google Scholar · View at Scopus
  10. T. T. Cai, D. Zhang, and D. Ben-Amotz, “Enhanced chemical classification of Raman images using multiresolution wavelet transformation,” Applied Spectroscopy, vol. 55, no. 9, pp. 1124–1130, 2001. View at Publisher · View at Google Scholar · View at Scopus
  11. C. Camerlingo, F. Zenone, G. M. Gaeta, R. Riccio, and M. Lepore, “Wavelet data processing of micro-Raman spectra of biological samples,” Measurement Science and Technology, vol. 17, no. 2, pp. 298–303, 2006. View at Publisher · View at Google Scholar · View at Scopus
  12. Y. Hu, T. Jiang, A. Shen, W. Li, X. Wang, and J. Hu, “A background elimination method based on wavelet transform for Raman spectra,” Chemometrics and Intelligent Laboratory Systems, vol. 85, no. 1, pp. 94–101, 2007. View at Publisher · View at Google Scholar · View at Scopus
  13. P. M. Ramos and I. Ruisánchez, “Noise and background removal in Raman spectra of ancient pigments using wavelet transform,” Journal of Raman Spectroscopy, vol. 36, no. 9, pp. 848–856, 2005. View at Publisher · View at Google Scholar · View at Scopus
  14. J. Li, L. P. Choo-Smith, Z. Tang, and M. G. Sowa, “Background removal from polarized Raman spectra of tooth enamel using the wavelet transform,” Journal of Raman Spectroscopy, vol. 42, no. 4, pp. 580–585, 2011. View at Publisher · View at Google Scholar · View at Scopus
  15. Z. M. Zhang, S. Chen, Y. Z. Liang et al., “An intelligent background-correction algorithm for highly fluorescent samples in Raman spectroscopy,” Journal of Raman Spectroscopy, vol. 41, no. 6, pp. 659–669, 2010. View at Publisher · View at Google Scholar · View at Scopus
  16. P. A. Mosier-Boss, S. H. Lieberman, and R. Newbery, “Fluorescence rejection in Raman-spectroscopy by shifted-Spectra, edge-detection, and FFT filtering techniques,” Applied Spectroscopy, vol. 49, pp. 630–638, 1995. View at Google Scholar
  17. T. Hasegawa, J. Nishijo, and J. Umemura, “Separation of Raman spectra from fluorescence emission background by principal component analysis,” Chemical Physics Letters, vol. 317, no. 6, pp. 642–646, 2000. View at Google Scholar · View at Scopus
  18. E. W. Weisstein, Convex Hull, MathWorld-A Wolfram Web Resource, http://mathworld.wolfram.com/ConvexHull.html.
  19. E. W. Weisstein, Fourier Series, MathWorld-A Wolfram Web Resource, http://mathworld.wolfram.com/FourierSeries.html/ConvexHull.html.
  20. E. W. Weisstein, Discrete Fourier Transform, MathWorld-A Wolfram Web Resource, http://mathworld.wolfram.com/DiscreteFourierTransform.html.