Reconstruction of object location for diffuse fluorescence tomography on the basis of hybrid models of light scattering in biotissues

  • I. I. Fiks
  • M. Yu. Kirillin
  • E. A. Sergeeva
  • I. V. TurchinEmail author

We propose a new method for reconstructing the spatial distribution of fluorophore in a highly scattering object from its images obtained by the method of diffuse fluorescence tomography. This method is intended for diagnostics of the fluorophore-marked tumors and is based on the algebraic-reconstruction principle combined with a new theoretical model and simulation of light propagation in randomly scattering media, such as biotissues, by the Monte Carlo method. The model experiments show that for 18-mm thick objects, the developed method allows one to determine location of the geometric center of a fluorescent inhomogeneity and its transverse and longitudinal dimensions with accuracies of up to 0.5 and 1.5 mm, respectively.


Monte Carlo Method Point Spread Function Light Propagation Reconstruction Accuracy Algebraic Reconstruction Technique 
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.


  1. 1.
    V. Ntziachristos, C. H. Tung, C. Bremer, and R. Weissleder, Nat. Med., 8, No. 7, 757 (2002).CrossRefGoogle Scholar
  2. 2.
    M. Busse and P.W. Vaupel, Acta Oncologica, 34, No. 3, 405 (1995).CrossRefGoogle Scholar
  3. 3.
    E. M. Treshchalina, O. S. Zhukova, and G.K. Gerasimova, in: R.U. Khabriev, ed., Methodical Instructions on the Study of Antitumoral Activity of Pharmaceutical Substances. Guidelines for Experimental (Preclinical) Study of New Pharmaceutical Substances [in Russian], Meditsina, Moscow (2005).Google Scholar
  4. 4.
    M.Yu. Kirillin, I.V. Turchin, I. I. Fiks, and M. S. Kleshnin, Technique for Determining the Spatial Resolution during Visualization of the Internal Structure of the Scattering Objects by the Method of Diffuse Fluorescence tomography, Met. GSSSD ME 159-2009 (2009).Google Scholar
  5. 5.
    I.P. Gurov and E. A. Vorob’eva, Problems of Coherent and Nonlinear Optics [in Russian], Inst. Theor. Mech. Opt., St.Petersburg Univ., St.Petersburg (2006), p. 82.Google Scholar
  6. 6.
    A. Ishimaru, Wave Propagation and Scattering in Random and Inhomogeneous Media, Academic Press., New York (1978).Google Scholar
  7. 7.
    V. V. Tuchin, Optical Biomedical Diagnostics, Vol. 1 [in Russian], Fizmatlit, Moscow (2007).Google Scholar
  8. 8.
    V. V. Tuchin, Lasers and Fiber Optics in Medical Studies [in Russian], Saratov Univ. Press, Saratov (1998).Google Scholar
  9. 9.
    I.V. Shutov, Diffuse Optical Tomography of Strongly Scattering Objects on the Basis of the Fast Algorithm for Projection Reconstruction of Internal Structure [in Russian], Moscow State Univ., Moscow (2002).Google Scholar
  10. 10.
    A. Soubret and V.Ntziachristos, Phys. Med. Biol., 51, No. 16, 3983 (2006).CrossRefGoogle Scholar
  11. 11.
    M. Gao, G. Lewis, G. M. Turner, et al., Appl. Opt., 44, No. 26, 5468 (2005).ADSCrossRefGoogle Scholar
  12. 12.
    L. S. Dolin and E.A. Sergeeva, Radiophys. Quantum Electron., 44, No. 11, 858 (2001).CrossRefGoogle Scholar
  13. 13.
    G. A. Korn and T.M. Korn, Mathematical Handbook for Scientists and Engineers, McGraw-Hill, New York (1968).Google Scholar
  14. 14.
    W.F. Cheong, S.A. Prahl, and A. J. Welch, IEEE J. Quantum Electron., 26, 2166 (1990).ADSCrossRefGoogle Scholar
  15. 15.
    A.T. Kumar, S. B. Raymond, G. Boverman, et al., Opt. Express, 14, No. 25, 12255 (2006).ADSCrossRefGoogle Scholar
  16. 16.
    S. Lam, F. Lesage, and X. Intes, Opt. Express, 13, No. 7, 2263 (2005).ADSCrossRefGoogle Scholar
  17. 17.
    V. Ntziachristos and R. Weissleder, Opt. Lett., 26, No. 12, 893 (2001).ADSCrossRefGoogle Scholar
  18. 18.
    E. A. Sergeeva and M. Y. Kirillin, Proc. SPIE, 7369, 73690H-6 (2009).Google Scholar
  19. 19.
    É.P. Zege, A.P. Ivanov, and I. L. Katsev, Image Transfer in a Scattering Medium [in Russian], Nauka i Tekhnika, Minsk (1985).Google Scholar
  20. 20.
    I. M. Sobol’, Numerical Monte Carlo Methods [in Russian], Nauka, Moscow (1973).Google Scholar
  21. 21.
    L. Wang, S. L. Jacques, and L. Zheng, Comp. Meth. Programs Biomed., 47, No. 2, 131 (1995).CrossRefGoogle Scholar
  22. 22.
    L. Wang, S. L. Jacques, and L. Zheng, Comp. Meth. Programs Biomed., 54, No. 3, 141 (1997).CrossRefGoogle Scholar
  23. 23.
    A. V. Bykov, M.Yu. Kirillin, and A. V. Priyezzhev, Opt. Spectrosc., 101, 33 (2006).ADSCrossRefGoogle Scholar
  24. 24.
    I. I. Fiks and M.Yu. Kirillin, in Calculations using Graphical Processors in Molecular Biology and Bioinformatics [in Russian], Moscow State Univ., Moscow (2010).Google Scholar
  25. 25.
    C. Byrne, IEEE Trans. Image Process., 14, No. 3, 321 (2005).MathSciNetADSCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, Inc. 2011

Authors and Affiliations

  • I. I. Fiks
    • 1
  • M. Yu. Kirillin
    • 1
  • E. A. Sergeeva
    • 1
  • I. V. Turchin
    • 1
    Email author
  1. 1.Institute of Applied Physics of the Russian Academy of SciencesNizhny NovgorodRussia

Personalised recommendations