Estimation and Reduction of Resonant Mie Scattering (RMieS) From IR Spectra of Biological Cells by Optimization Algorithm

  • Sahar Barzegari Banadkoki
  • Farah Torkamani Azar
  • Farshad Hosseini Shirazi
Original Article


Infrared spectroscopy has attracted considerable attention at many fields of study such as pharmaceutical sciences. How much scattering we have would be based on the similarities range of mid-infrared wavelength and uneven biological samples like cells and tissues. In such cases, the part of the input irradiance wave which does not reach the detector could erroneously be interpreted as absorption intensity. So it shows itself as a broad sinusoidal oscillation in the baseline, and even it would have frequency shifts in the absorbance bands. Based on the studies conducted in this area, the main cause of spectral distortion is the Resonant Mie Scattering. In other words, the real refractive index spectrum plays a prominent role in high scattering. However, pure absorptive components extraction suffers from requiring an appropriate reference spectrum for initialization. It must not contain any scattering contributions which unfortunately cannot be always happened. In this article, a cost function under a clear constraint is presented with regard to the biological data and the scattering structure to spectrum correction. The results show that the creation of eligible cost function using optimization algorithms could have the desired accuracy for biological spectra even without selecting appropriate reference spectrum.


Infrared (IR) spectra Scattering Optimization Signal processing 


  1. 1.
    Pavia, D. L., Lampman, G. M., Kriz, G. S., & Vyvyan, J. A. (2008). Introduction to spectroscopy. Belmont, CA: Cengage Learning.Google Scholar
  2. 2.
    Ostrovsky, E., Zelig, U., Gusakova, I., Ariad, S., Mordechai, S., Nisky, I., et al. (2013). Detection of cancer using advanced computerized analysis of infrared spectra of peripheral blood. IEEE Transactions on Biomedical Engineering, 60(2), 343–353.CrossRefGoogle Scholar
  3. 3.
    Bassan, P., Kohler, A., Martens, H., Lee, J., Byrne, H. J., Dumas, P., et al. (2010). Resonant Mie scattering (RMieS) correction of infrared spectra from highly scattering biological samples. Analyst, 135(2), 268–277.CrossRefGoogle Scholar
  4. 4.
    Bassan, P., Kohler, A., Martens, H., Lee, J., Jackson, E., Lockyer, N., et al. (2010). RMieS-EMSC correction for infrared spectra of biological cells: Extension using full Mie theory and GPU computing. Journal of Biophotonics, 3(8–9), 609–620.CrossRefGoogle Scholar
  5. 5.
    Diem, M., Miljković, M., Bird, B., Chernenko, T., Schubert, J., Marcsisin, E., et al. (2012). Applications of infrared and Raman microspectroscopy of cells and tissue in medical diagnostics: Present status and future promises. Journal of Spectroscopy, 27(5–6), 463–496.CrossRefGoogle Scholar
  6. 6.
    Mohlenhoff, B., Romeo, M., Diem, M., & Wood, B. R. (2005). Mie-type scattering and non-Beer-Lambert absorption behavior of human cells in infrared microspectroscopy. Biophysical Journal, 88(5), 3635–3640.CrossRefGoogle Scholar
  7. 7.
    Bassan, P., Byrne, H. J., Lee, J., Bonnier, F., Clarke, C., Dumas, P., et al. (2009). Reflection contributions to the dispersion artefact in FTIR spectra of single biological cells. Analyst, 134(6), 1171–1175.CrossRefGoogle Scholar
  8. 8.
    Dazzi, A., Deniset-Besseau, A., & Lasch, P. (2013). Minimising contributions from scattering in infrared spectra by means of an integrating sphere. Analyst, 138(14), 4191–4201.CrossRefGoogle Scholar
  9. 9.
    Baker, M. J., Trevisan, J., Bassan, P., Bhargava, R., Butler, H. J., Dorling, K. M., et al. (2014). Using Fourier transform IR spectroscopy to analyze biological materials. Nature Protocols, 9(8), 1771.CrossRefGoogle Scholar
  10. 10.
    Mie, G. (1908). Beiträge zur Optik trüber Medien, speziell kolloidaler Metallösungen. Annalen der Physik, 330(3), 377–445.CrossRefzbMATHGoogle Scholar
  11. 11.
    Hulst, H. C., & van de Hulst, H. C. (1957). Light scattering by small particles. North Chelmsford: Courier Corporation.zbMATHGoogle Scholar
  12. 12.
    Romeo, M., Mohlenhoff, B., & Diem, M. (2006). Infrared micro-spectroscopy of human cells: Causes for the spectral variance of oral mucosa (buccal) cells. Vibrational Spectroscopy, 42(1), 9–14.CrossRefGoogle Scholar
  13. 13.
    Bassan, P., Byrne, H. J., Bonnier, F., Lee, J., Dumas, P., & Gardner, P. (2009). Resonant Mie scattering in infrared spectroscopy of biological materials–understanding the ‘dispersion artefact’. Analyst, 134(8), 1586–1593.CrossRefGoogle Scholar
  14. 14.
    Bassan, P. (2011). Light scattering during infrared spectroscopic measurements of biomedical samples (Doctoral dissertation, University of Manchester).Google Scholar
  15. 15.
    Ogilvie, J. F., & Fee, G. J. (2013). Equivalence of Kramers Kronig and Fourier transforms to convert between optical dispersion and optical spectra. Mathch-Communications in Mathematical and in Computer Chemistry, 69(2), 249–262.MathSciNetzbMATHGoogle Scholar
  16. 16.
    Martens, H., Nielsen, J. P., & Engelsen, S. B. (2003). Light scattering and light absorbance separated by extended multiplicative signal correction. Application to near-infrared transmission analysis of powder mixtures. Analytical Chemistry, 75(3), 394–404.CrossRefGoogle Scholar
  17. 17.
    Kohler, A., Sule-Suso, J., Sockalingum, G. D., Tobin, M., Bahrami, F., Yang, Y., et al. (2008). Estimating and correcting Mie scattering in synchrotron-based microscopic Fourier transform infrared spectra by extended multiplicative signal correction. Applied Spectroscopy, 62(3), 259–266.CrossRefGoogle Scholar
  18. 18.
    Duarte, L. T., Moussaoui, S., & Jutten, C. (2014). Source separation in chemical analysis: Recent achievements and perspectives. IEEE Signal Processing Magazine, 31(3), 135–146.CrossRefGoogle Scholar
  19. 19.
    Whittaker, K. A., Keaveney, J., Hughes, I. G., & Adams, C. S. (2015). Hilbert transform: Applications to atomic spectra. Physical Review A, 91(3), 032513.MathSciNetCrossRefGoogle Scholar
  20. 20.
    Bertie, J. E., & Zhang, S. L. (1992). Infrared intensities of liquids. IX. The Kramers-Kronig transform, and its approximation by the finite Hilbert transform via fast Fourier transforms. Canadian Journal of Chemistry, 70(2), 520–531.CrossRefGoogle Scholar
  21. 21.
    Diem, M. (2015). Modern vibrational spectroscopy and micro-spectroscopy: Theory, instrumentation and biomedical applications. New York: Wiley.CrossRefGoogle Scholar
  22. 22.
    Konevskikh, T., Lukacs, R., Blümel, R., Ponossov, A., & Kohler, A. (2016). Mie scatter corrections in single cell infrared microspectroscopy. Faraday Discussions, 187, 235–257.CrossRefGoogle Scholar
  23. 23.
    Bassan, P., Sachdeva, A., Kohler, A., Hughes, C., Henderson, A., Boyle, J., et al. (2012). FTIR microscopy of biological cells and tissue: Data analysis using resonant Mie scattering (RMieS) EMSC algorithm. Analyst, 137(6), 1370–1377.CrossRefGoogle Scholar

Copyright information

© Taiwanese Society of Biomedical Engineering 2018

Authors and Affiliations

  1. 1.Department of Communication Engineering, Faculty of Electrical EngineeringShahid Beheshti UniversityTehranIran
  2. 2.Pharmaceutical Sciences Reasearch CenterShahid Beheshti University of Medical SciencesTehranIran

Personalised recommendations