Abstract

Conceptual engineering design and optimization of laser-based imaging techniques and optical diagnostic systems used in the field of biomedical optics requires a clear understanding of the light-tissue interaction and peculiarities of localization of the detected optical radiation within the medium. The description of photon migration within the turbid tissue-like media is based on the concept of radiative transfer that forms a basis of Monte Carlo (MC) modeling. An opportunity of direct simulation of influence of structural variations of biological tissues on the probing light makes MC a primary tool for biomedical optics and optical engineering. Due to the diversity of optical modalities utilizing different properties of light and mechanisms of light-tissue interactions a new MC code is typically required to be developed for the particular diagnostic application. In current paper introducing an object oriented concept of MC modeling and utilizing modern web applications we present the generalized online computational tool suitable for the major applications in biophotonics. The computation is supported by NVIDEA CUDA Graphics Processing Unit providing acceleration of modeling up to 340 times.

© 2011 OSA

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2011 (1)

2010 (4)

Q. Fang, “Mesh-based Monte Carlo method using fast ray-tracing in Plücker coordinates,” Biomed. Opt. Express 1(1), 165–175 (2010).
[CrossRef] [PubMed]

V. L. Kuz’min and I. V. Meglinski, “Anomalous polarization effects during light scattering in random media,” J. Exp. Theor. Phys. 110(5), 742–753 (2010).
[CrossRef]

V. L. Kuzmin and I. V. Meglinski, “Helicity flip of backscattered circularly polarized light,” Proc. SPIE 7573, 75730Z, 75730Z-7 (2010).
[CrossRef]

M. Kirillin, I. Meglinski, V. Kuzmin, E. Sergeeva, and R. Myllylä, “Simulation of optical coherence tomography images by Monte Carlo modeling based on polarization vector approach,” Opt. Express 18(21), 21714–21724 (2010).
[CrossRef] [PubMed]

2009 (2)

C. Balas, “Review of biomedical optical imaging—a powerful, non-invasive, non-ionizing technology for improving in vivo diagnosis,” Meas. Sci. Technol. 20(10), 104020 (2009).
[CrossRef]

L. S. Dolin, “Development of radiative transfer theory as applied to instrumental imaging in turbid media,” Phys.-Usp. 52(5), 519–526 (2009).
[CrossRef]

2008 (2)

I. V. Meglinski, M. Kirillin, V. L. Kuzmin, and R. Myllylä, “Simulation of polarization-sensitive optical coherence tomography images by a Monte Carlo method,” Opt. Lett. 33(14), 1581–1583 (2008).
[CrossRef] [PubMed]

I. V. Meglinski, M. Kirillin, and V. L. Kuzmin, “The concept of a unified modelling of optical radiation propagation in complex turbid media,” Proc. SPIE 7142, 714204, 714204-5 (2008).
[CrossRef]

2007 (2)

E. Berrocal, D. Sedarsky, M. Paciaroni, I. V. Meglinski, and M. A. Linne, “Laser light scattering in turbid media Part I: Experimental and simulated results for the spatial intensity distribution,” Opt. Express 15(17), 10649–10665 (2007).
[CrossRef] [PubMed]

V. L. Kuzmin and I. V. Meglinski, “Coherent effects of multiple scattering for scalar and electromagnetic fields: Monte-Carlo simulation and Milne-like solutions,” Opt. Commun. 273(2), 307–310 (2007).
[CrossRef]

2006 (2)

M. Y. Kirillin, I. V. Meglinskii, and A. V. Priezzhev, “Effect of photons of different scattering orders on the formation of a signal in optical low-coherence tomography of highly scattering media,” Quantum Electron. 36(3), 247–252 (2006).
[CrossRef]

E. Berrocal, I. V. Meglinski, D. A. Greenhalgh, and M. A. Linne, “Image transfer through the complex scattering turbid media,” Laser Phys. Lett. 3(9), 464–467 (2006).
[CrossRef]

2005 (3)

I. V. Meglinski, V. L. Kuzmin, D. Y. Churmakov, and D. A. Greenhalgh, “Monte Carlo simulation of coherent effects in multiple scattering,” Proc. R. Soc. A 461(2053), 43–53 (2005).
[CrossRef]

V. L. Kuz’min, I. V. Meglinski, and D. Y. Churmakov, “Stochastic modeling of coherent phenomena in strongly inhomogeneous media,” J. Exp. Theor. Phys. 101(1), 22–32 (2005).
[CrossRef]

J. Ramella-Roman, S. Prahl, and S. Jacques, “Three Monte Carlo programs of polarized light transport into scattering media: part I,” Opt. Express 13(12), 4420–4438 (2005).
[CrossRef] [PubMed]

2004 (2)

V. L. Kuzmin and I. V. Meglinski, “Coherent multiple scattering effects and Monte Carlo method,” JETP Lett. 79(3), 109–112 (2004).
[CrossRef]

D. Y. Churmakov, I. V. Meglinski, and D. A. Greenhalgh, “Amending of fluorescence sensor signal localization in human skin by matching of the refractive index,” J. Biomed. Opt. 9(2), 339–346 (2004).
[CrossRef] [PubMed]

2003 (2)

D. Y. Churmakov, I. V. Meglinski, S. A. Piletsky, and D. A. Greenhalgh, “Analysis of skin tissues spatial fluorescence distribution by the Monte Carlo simulation,” J. Phys. D Appl. Phys. 36(14), 1722–1728 (2003).
[CrossRef]

I. V. Meglinski and S. J. Matcher, “Computer simulation of the skin reflectance spectra,” Comput. Methods Programs Biomed. 70(2), 179–186 (2003).
[CrossRef] [PubMed]

2002 (1)

2001 (2)

I. V. Meglinsky and S. J. Matcher, “Modelling the sampling volume for skin blood oxygenation measurements,” Med. Biol. Eng. Comput. 39(1), 44–50 (2001).
[CrossRef] [PubMed]

I. V. Meglinski, “Modeling the reflectance spectra of the optical radiation for random inhomogeneous multi-layered highly scattering and absorbing media by the Monte Carlo technique,” Quantum Electron. 31, 1101–1107 (2001).

1995 (1)

L. H. Wang, S. L. Jacques, and L.-Q. Zheng, “MCML—Monte Carlo modeling of light transport in multi-layered tissues,” Comput. Methods Programs Biomed. 47(2), 131–146 (1995).
[CrossRef]

1955 (1)

R. Giovanelli, “Reflection by semi-infinite diffusers,” Opt. Acta (Lond.) 2, 153–162 (1955).

Balas, C.

C. Balas, “Review of biomedical optical imaging—a powerful, non-invasive, non-ionizing technology for improving in vivo diagnosis,” Meas. Sci. Technol. 20(10), 104020 (2009).
[CrossRef]

Berrocal, E.

Boas, D. A.

Churmakov, D. Y.

V. L. Kuz’min, I. V. Meglinski, and D. Y. Churmakov, “Stochastic modeling of coherent phenomena in strongly inhomogeneous media,” J. Exp. Theor. Phys. 101(1), 22–32 (2005).
[CrossRef]

I. V. Meglinski, V. L. Kuzmin, D. Y. Churmakov, and D. A. Greenhalgh, “Monte Carlo simulation of coherent effects in multiple scattering,” Proc. R. Soc. A 461(2053), 43–53 (2005).
[CrossRef]

D. Y. Churmakov, I. V. Meglinski, and D. A. Greenhalgh, “Amending of fluorescence sensor signal localization in human skin by matching of the refractive index,” J. Biomed. Opt. 9(2), 339–346 (2004).
[CrossRef] [PubMed]

D. Y. Churmakov, I. V. Meglinski, S. A. Piletsky, and D. A. Greenhalgh, “Analysis of skin tissues spatial fluorescence distribution by the Monte Carlo simulation,” J. Phys. D Appl. Phys. 36(14), 1722–1728 (2003).
[CrossRef]

Culver, J. P.

Dolin, L. S.

L. S. Dolin, “Development of radiative transfer theory as applied to instrumental imaging in turbid media,” Phys.-Usp. 52(5), 519–526 (2009).
[CrossRef]

Dunn, A. K.

Fang, Q.

Giovanelli, R.

R. Giovanelli, “Reflection by semi-infinite diffusers,” Opt. Acta (Lond.) 2, 153–162 (1955).

Greenhalgh, D. A.

E. Berrocal, I. V. Meglinski, D. A. Greenhalgh, and M. A. Linne, “Image transfer through the complex scattering turbid media,” Laser Phys. Lett. 3(9), 464–467 (2006).
[CrossRef]

I. V. Meglinski, V. L. Kuzmin, D. Y. Churmakov, and D. A. Greenhalgh, “Monte Carlo simulation of coherent effects in multiple scattering,” Proc. R. Soc. A 461(2053), 43–53 (2005).
[CrossRef]

D. Y. Churmakov, I. V. Meglinski, and D. A. Greenhalgh, “Amending of fluorescence sensor signal localization in human skin by matching of the refractive index,” J. Biomed. Opt. 9(2), 339–346 (2004).
[CrossRef] [PubMed]

D. Y. Churmakov, I. V. Meglinski, S. A. Piletsky, and D. A. Greenhalgh, “Analysis of skin tissues spatial fluorescence distribution by the Monte Carlo simulation,” J. Phys. D Appl. Phys. 36(14), 1722–1728 (2003).
[CrossRef]

Jacques, S.

Jacques, S. L.

L. H. Wang, S. L. Jacques, and L.-Q. Zheng, “MCML—Monte Carlo modeling of light transport in multi-layered tissues,” Comput. Methods Programs Biomed. 47(2), 131–146 (1995).
[CrossRef]

Kirillin, M.

Kirillin, M. Y.

M. Y. Kirillin, I. V. Meglinskii, and A. V. Priezzhev, “Effect of photons of different scattering orders on the formation of a signal in optical low-coherence tomography of highly scattering media,” Quantum Electron. 36(3), 247–252 (2006).
[CrossRef]

Kuz’min, V. L.

V. L. Kuz’min and I. V. Meglinski, “Anomalous polarization effects during light scattering in random media,” J. Exp. Theor. Phys. 110(5), 742–753 (2010).
[CrossRef]

V. L. Kuz’min, I. V. Meglinski, and D. Y. Churmakov, “Stochastic modeling of coherent phenomena in strongly inhomogeneous media,” J. Exp. Theor. Phys. 101(1), 22–32 (2005).
[CrossRef]

Kuzmin, V.

Kuzmin, V. L.

V. L. Kuzmin and I. V. Meglinski, “Helicity flip of backscattered circularly polarized light,” Proc. SPIE 7573, 75730Z, 75730Z-7 (2010).
[CrossRef]

I. V. Meglinski, M. Kirillin, and V. L. Kuzmin, “The concept of a unified modelling of optical radiation propagation in complex turbid media,” Proc. SPIE 7142, 714204, 714204-5 (2008).
[CrossRef]

I. V. Meglinski, M. Kirillin, V. L. Kuzmin, and R. Myllylä, “Simulation of polarization-sensitive optical coherence tomography images by a Monte Carlo method,” Opt. Lett. 33(14), 1581–1583 (2008).
[CrossRef] [PubMed]

V. L. Kuzmin and I. V. Meglinski, “Coherent effects of multiple scattering for scalar and electromagnetic fields: Monte-Carlo simulation and Milne-like solutions,” Opt. Commun. 273(2), 307–310 (2007).
[CrossRef]

I. V. Meglinski, V. L. Kuzmin, D. Y. Churmakov, and D. A. Greenhalgh, “Monte Carlo simulation of coherent effects in multiple scattering,” Proc. R. Soc. A 461(2053), 43–53 (2005).
[CrossRef]

V. L. Kuzmin and I. V. Meglinski, “Coherent multiple scattering effects and Monte Carlo method,” JETP Lett. 79(3), 109–112 (2004).
[CrossRef]

Linne, M. A.

Matcher, S. J.

I. V. Meglinski and S. J. Matcher, “Computer simulation of the skin reflectance spectra,” Comput. Methods Programs Biomed. 70(2), 179–186 (2003).
[CrossRef] [PubMed]

I. V. Meglinsky and S. J. Matcher, “Modelling the sampling volume for skin blood oxygenation measurements,” Med. Biol. Eng. Comput. 39(1), 44–50 (2001).
[CrossRef] [PubMed]

Meglinski, I.

Meglinski, I. V.

V. L. Kuz’min and I. V. Meglinski, “Anomalous polarization effects during light scattering in random media,” J. Exp. Theor. Phys. 110(5), 742–753 (2010).
[CrossRef]

V. L. Kuzmin and I. V. Meglinski, “Helicity flip of backscattered circularly polarized light,” Proc. SPIE 7573, 75730Z, 75730Z-7 (2010).
[CrossRef]

I. V. Meglinski, M. Kirillin, and V. L. Kuzmin, “The concept of a unified modelling of optical radiation propagation in complex turbid media,” Proc. SPIE 7142, 714204, 714204-5 (2008).
[CrossRef]

I. V. Meglinski, M. Kirillin, V. L. Kuzmin, and R. Myllylä, “Simulation of polarization-sensitive optical coherence tomography images by a Monte Carlo method,” Opt. Lett. 33(14), 1581–1583 (2008).
[CrossRef] [PubMed]

V. L. Kuzmin and I. V. Meglinski, “Coherent effects of multiple scattering for scalar and electromagnetic fields: Monte-Carlo simulation and Milne-like solutions,” Opt. Commun. 273(2), 307–310 (2007).
[CrossRef]

E. Berrocal, D. Sedarsky, M. Paciaroni, I. V. Meglinski, and M. A. Linne, “Laser light scattering in turbid media Part I: Experimental and simulated results for the spatial intensity distribution,” Opt. Express 15(17), 10649–10665 (2007).
[CrossRef] [PubMed]

E. Berrocal, I. V. Meglinski, D. A. Greenhalgh, and M. A. Linne, “Image transfer through the complex scattering turbid media,” Laser Phys. Lett. 3(9), 464–467 (2006).
[CrossRef]

V. L. Kuz’min, I. V. Meglinski, and D. Y. Churmakov, “Stochastic modeling of coherent phenomena in strongly inhomogeneous media,” J. Exp. Theor. Phys. 101(1), 22–32 (2005).
[CrossRef]

I. V. Meglinski, V. L. Kuzmin, D. Y. Churmakov, and D. A. Greenhalgh, “Monte Carlo simulation of coherent effects in multiple scattering,” Proc. R. Soc. A 461(2053), 43–53 (2005).
[CrossRef]

V. L. Kuzmin and I. V. Meglinski, “Coherent multiple scattering effects and Monte Carlo method,” JETP Lett. 79(3), 109–112 (2004).
[CrossRef]

D. Y. Churmakov, I. V. Meglinski, and D. A. Greenhalgh, “Amending of fluorescence sensor signal localization in human skin by matching of the refractive index,” J. Biomed. Opt. 9(2), 339–346 (2004).
[CrossRef] [PubMed]

D. Y. Churmakov, I. V. Meglinski, S. A. Piletsky, and D. A. Greenhalgh, “Analysis of skin tissues spatial fluorescence distribution by the Monte Carlo simulation,” J. Phys. D Appl. Phys. 36(14), 1722–1728 (2003).
[CrossRef]

I. V. Meglinski and S. J. Matcher, “Computer simulation of the skin reflectance spectra,” Comput. Methods Programs Biomed. 70(2), 179–186 (2003).
[CrossRef] [PubMed]

I. V. Meglinski, “Modeling the reflectance spectra of the optical radiation for random inhomogeneous multi-layered highly scattering and absorbing media by the Monte Carlo technique,” Quantum Electron. 31, 1101–1107 (2001).

Meglinskii, I. V.

M. Y. Kirillin, I. V. Meglinskii, and A. V. Priezzhev, “Effect of photons of different scattering orders on the formation of a signal in optical low-coherence tomography of highly scattering media,” Quantum Electron. 36(3), 247–252 (2006).
[CrossRef]

Meglinsky, I. V.

I. V. Meglinsky and S. J. Matcher, “Modelling the sampling volume for skin blood oxygenation measurements,” Med. Biol. Eng. Comput. 39(1), 44–50 (2001).
[CrossRef] [PubMed]

Myllylä, R.

Paciaroni, M.

Piletsky, S. A.

D. Y. Churmakov, I. V. Meglinski, S. A. Piletsky, and D. A. Greenhalgh, “Analysis of skin tissues spatial fluorescence distribution by the Monte Carlo simulation,” J. Phys. D Appl. Phys. 36(14), 1722–1728 (2003).
[CrossRef]

Prahl, S.

Priezzhev, A. V.

M. Y. Kirillin, I. V. Meglinskii, and A. V. Priezzhev, “Effect of photons of different scattering orders on the formation of a signal in optical low-coherence tomography of highly scattering media,” Quantum Electron. 36(3), 247–252 (2006).
[CrossRef]

Ramella-Roman, J.

Sedarsky, D.

Sergeeva, E.

Shen, H.

Stott, J. J.

Wang, G.

Wang, L. H.

L. H. Wang, S. L. Jacques, and L.-Q. Zheng, “MCML—Monte Carlo modeling of light transport in multi-layered tissues,” Comput. Methods Programs Biomed. 47(2), 131–146 (1995).
[CrossRef]

Zheng, L.-Q.

L. H. Wang, S. L. Jacques, and L.-Q. Zheng, “MCML—Monte Carlo modeling of light transport in multi-layered tissues,” Comput. Methods Programs Biomed. 47(2), 131–146 (1995).
[CrossRef]

Biomed. Opt. Express (2)

Comput. Methods Programs Biomed. (2)

L. H. Wang, S. L. Jacques, and L.-Q. Zheng, “MCML—Monte Carlo modeling of light transport in multi-layered tissues,” Comput. Methods Programs Biomed. 47(2), 131–146 (1995).
[CrossRef]

I. V. Meglinski and S. J. Matcher, “Computer simulation of the skin reflectance spectra,” Comput. Methods Programs Biomed. 70(2), 179–186 (2003).
[CrossRef] [PubMed]

J. Biomed. Opt. (1)

D. Y. Churmakov, I. V. Meglinski, and D. A. Greenhalgh, “Amending of fluorescence sensor signal localization in human skin by matching of the refractive index,” J. Biomed. Opt. 9(2), 339–346 (2004).
[CrossRef] [PubMed]

J. Exp. Theor. Phys. (2)

V. L. Kuz’min, I. V. Meglinski, and D. Y. Churmakov, “Stochastic modeling of coherent phenomena in strongly inhomogeneous media,” J. Exp. Theor. Phys. 101(1), 22–32 (2005).
[CrossRef]

V. L. Kuz’min and I. V. Meglinski, “Anomalous polarization effects during light scattering in random media,” J. Exp. Theor. Phys. 110(5), 742–753 (2010).
[CrossRef]

J. Phys. D Appl. Phys. (1)

D. Y. Churmakov, I. V. Meglinski, S. A. Piletsky, and D. A. Greenhalgh, “Analysis of skin tissues spatial fluorescence distribution by the Monte Carlo simulation,” J. Phys. D Appl. Phys. 36(14), 1722–1728 (2003).
[CrossRef]

JETP Lett. (1)

V. L. Kuzmin and I. V. Meglinski, “Coherent multiple scattering effects and Monte Carlo method,” JETP Lett. 79(3), 109–112 (2004).
[CrossRef]

Laser Phys. Lett. (1)

E. Berrocal, I. V. Meglinski, D. A. Greenhalgh, and M. A. Linne, “Image transfer through the complex scattering turbid media,” Laser Phys. Lett. 3(9), 464–467 (2006).
[CrossRef]

Meas. Sci. Technol. (1)

C. Balas, “Review of biomedical optical imaging—a powerful, non-invasive, non-ionizing technology for improving in vivo diagnosis,” Meas. Sci. Technol. 20(10), 104020 (2009).
[CrossRef]

Med. Biol. Eng. Comput. (1)

I. V. Meglinsky and S. J. Matcher, “Modelling the sampling volume for skin blood oxygenation measurements,” Med. Biol. Eng. Comput. 39(1), 44–50 (2001).
[CrossRef] [PubMed]

Opt. Acta (Lond.) (1)

R. Giovanelli, “Reflection by semi-infinite diffusers,” Opt. Acta (Lond.) 2, 153–162 (1955).

Opt. Commun. (1)

V. L. Kuzmin and I. V. Meglinski, “Coherent effects of multiple scattering for scalar and electromagnetic fields: Monte-Carlo simulation and Milne-like solutions,” Opt. Commun. 273(2), 307–310 (2007).
[CrossRef]

Opt. Express (4)

Opt. Lett. (1)

Phys.-Usp. (1)

L. S. Dolin, “Development of radiative transfer theory as applied to instrumental imaging in turbid media,” Phys.-Usp. 52(5), 519–526 (2009).
[CrossRef]

Proc. R. Soc. A (1)

I. V. Meglinski, V. L. Kuzmin, D. Y. Churmakov, and D. A. Greenhalgh, “Monte Carlo simulation of coherent effects in multiple scattering,” Proc. R. Soc. A 461(2053), 43–53 (2005).
[CrossRef]

Proc. SPIE (2)

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Figures (6)

Fig. 1
Fig. 1

Schematic presentation of the generalized object-oriented MC model structure. Data Input and selection of a particular application; Class objects represent exact experimental conditions including source-detector geometry & configuration, medium structure, properties of incident radiation, etc.

Fig. 2
Fig. 2

Schematic presentation of used GPU logical divided on hundreds of independent cores allowing creation of thousands of lightweight parallel threads.

Fig. 3
Fig. 3

Schematic presentation of the key components of the online MC solution. The server hosts a web frontend, which accepts user simulation requests and retrieves results. The developed components provide interoperability between the interactive user interface and GPUs.

Fig. 4
Fig. 4

The frontend of O3MC computational tool: (a) interactive user interface providing the selection of applications; (b), (c) and (d) are, respectively, the web-pages that allow customizing parameters of the medium, fiber-optic probe and the boundaries of sampling volume. Available online at: http://biophotonics.otago.ac.nz/MCOnline.aspx.

Fig. 5
Fig. 5

Example of sampling volume simulation for a fiber-optic probe applied for the measurements of human skin reflectance spectra by O3MC: side XZ (left) and surface XY (right) projections. Available online at http://biophotonics.otago.ac.nz/MCOnline.aspx.

Fig. 6
Fig. 6

Examples of reflectance spectrum simulation for Type I/II skin, melanin concentration 2% and normal concentration of blood (left) and skin color counting for Type V/VI skin, melanin concentration 25% and normal concentration of blood (right). Available online at http://biophotonics.otago.ac.nz/MCOnline.aspx.

Tables (2)

Tables Icon

Table 1 Comparison of the diffuse reflectance Rd given by analytical results tabulated by Giovanelli [42], the results of the adding-doubling method by Prahl [43], and the results of MCML code developed by Wang et al. [7] versus the developed O3MC code

Tables Icon

Table 2 Comparison of the diffuse reflectance Rd and transmittance Td given by tabulated data by van de Hulst [44], results of the adding-doubling method by Prahl [43], and the results of MCML developed by Wang et al. [7] versus the developed O3MC code.

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