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The Spectral Analysis of Human Skin Tissue Using Multi-spectral Images

  • Andrzej Zacher
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6375)

Abstract

This paper analyses the properties of human skin, when the light source from different angles and positions was applied. It answers the question how the tissue appearance varies and how the changes of radiance distribution can be observed on multi-spectral images. As long as they contain raw data, that wasn’t changed by any postprocessing algorithm, they directly represent light spectrum and its intensity. All images were taken at wavelengths ranging from 400nm to 720nm with step 16nm long. As the next experiment the reflectance spectrum of healthy and diseased tissue was compared. Due to fluorophore concentration and utilizing multi-spectra images, it was possible to unambiguously determine cancerous part of human skin tissue.

Keywords

Human Skin Light Spectrum Port Wine Inherent Optical Property Photodynamic Diagnosis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Nielsen, K.P., Zhao, L., Stamnes, J.J., Stamnes, K., Moan, J.: The optics of human skin: Aspects important for human health. In: Proceedings from the symposium Solar Radiation and Human Health (2008)Google Scholar
  2. 2.
    Katikaa, K.M., Pilona, L., Dippleb, K., Levinc, S., Blackwell, J., Berberoglu, H.: In-Vivo Time-Resolved Autofluorescence Measurements on Human Skin. In: Proceedings of the SPIE, vol. 6078, pp. 83–93 (2006)Google Scholar
  3. 3.
    Meglinski, I.V., Matcher, S.J.: Computer simulation of the skin reflectance spectra. Computer Methods and Programs in Biomedicine 70(2), 179–186 (2003)CrossRefGoogle Scholar
  4. 4.
    Wilkie, A., Weidlich, A., Larboulette, C., Purgathofer, W.: A Reflectance Model for Diffuse Fluorescent Surfaces. In: Proceedings of Graphite 2006, pp. 321–328 (2006)Google Scholar
  5. 5.
    Palmer, G.M., Ramanujam, N.: Monte-Carlo-based model for the extraction of intrinsic fluorescence from turbid media. Journal of Biomedical Optics 13(2) (2008)Google Scholar
  6. 6.
    Barton, J.K., Pfefer, T.J., Welch, A.J., Smithies, D.J., Nelson, J.S., van Gemert, M.J.C.: Optical Monte Carlo modeling of a true port wine stain anatomy. Optics Express 2(9), 391–396 (1998)CrossRefGoogle Scholar
  7. 7.
    Latimer, P., Pyle, B.E.: Light Scattering at various angles. Theoretical predictions of the effects of particle volume changes. Biophysical Journal 12, 764–773 (1972)Google Scholar
  8. 8.
    Sil, S., Bose, T., Roy, D., Chakraborti, A.S.: Protoporphyrin IX-induced structural and functional changes in human red blood cells, haemoglobin and myoglobin. Journal of Biosciences 29(3), 281–291 (2004)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Andrzej Zacher
    • 1
  1. 1.Institute of InformaticsThe Silesian University of TechnologyGliwicePoland

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