Abstract

Monte Carlo (MC) simulation is widely recognized as a gold standard in biophotonics for its high accuracy. Here we analyze several issues associated with tetrahedron-based optical Monte Carlo simulation in the context of TIM-OS, MMCM, MCML, and CUDAMCML in terms of accuracy and efficiency. Our results show that TIM-OS has significant better performance in the complex geometry cases and has comparable performance with CUDAMCML in the multi-layered tissue model.

© 2010 OSA

Full Article  |  PDF Article

References

  • View by:
  • |
  • |
  • |

  1. L. Wang, S. L. Jacques, and L. Zheng, “MCML--Monte Carlo modeling of light transport in multi-layered tissues,” Comput. Methods Programs Biomed. 47(2), 131–146 (1995).
    [CrossRef] [PubMed]
  2. A. Appel, “Some techniques for shading machine renderings of solids,” AFIPS Joint Computer Conferences. Atlantic City, New Jersey (1968).
  3. J. D. Foley, Computer Graphics: Principles and Practice, 2nd ed (Addison-Wesley, Reading, Mass., 1995).
  4. E. Margallo-Balbás and P. J. French, “Shape based Monte Carlo code for light transport in complex heterogeneous tissues,” Opt. Express 15(21), 14086–14098 (2007).
    [CrossRef] [PubMed]
  5. B. W. Rice, M. D. Cable, and M. B. Nelson, “In vivo imaging of light-emitting probes,” J. Biomed. Opt. 6(4), 432–440 (2001).
    [CrossRef] [PubMed]
  6. W. F. Cheong, S. A. Prahl, and A. J. Welch, “A review of the optical-properties of biological tissues,” IEEE J. Quantum Electron. 26(12), 2166–2185 (1990).
    [CrossRef]
  7. H. Shen and G. Wang, “A tetrahedron-based inhomogeneous Monte Carlo optical simulator,” Phys. Med. Biol. 55(4), 947–962 (2010).
    [CrossRef] [PubMed]
  8. H. Li, J. Tian, F. Zhu, W. Cong, L. V. Wang, E. A. Hoffman, and G. Wang, “A mouse optical simulation environment (MOSE) to investigate bioluminescent phenomena in the living mouse with the Monte Carlo method,” Acad. Radiol. 11(9), 1029–1038 (2004).
    [CrossRef] [PubMed]
  9. W. Vogt, H. Shen, G. Wang, and C. G. Rylander, “Parametric study of tissue optical clearing by localized mechanical compression using combined finite element and Monte Carlo simulation,” J. Innovative Opt. Health Sci. (JIOHS) 3(3), 203–211 (2010).
    [CrossRef]
  10. Y. Lu, B. Zhu, H. Shen, J. C. Rasmussen, G. Wang, and E. M. Sevick-Muraca, “A parallel adaptive finite element simplified spherical harmonics approximation solver for frequency domain fluorescence molecular imaging,” Phys. Med. Biol. 55(16), 4625–4645 (2010).
    [CrossRef] [PubMed]
  11. C. G. Rylander, D. P. Davé, T. Akkin, T. E. Milner, K. R. Diller, and A. J. Welch, “Quantitative phase-contrast imaging of cells with phase-sensitive optical coherence microscopy,” Opt. Lett. 29(13), 1509–1511 (2004).
    [CrossRef] [PubMed]
  12. G. Yao and L. V. Wang, “Monte Carlo simulation of an optical coherence tomography signal in homogeneous turbid media,” Phys. Med. Biol. 44(9), 2307–2320 (1999).
    [CrossRef] [PubMed]
  13. M. N. Rylander, Y. Feng, J. Bass, and K. R. Diller, “Heat shock protein expression and injury optimization for laser therapy design,” Lasers Surg. Med. 39(9), 731–746 (2007).
    [CrossRef] [PubMed]
  14. T. J. Pfefer, J. K. Barton, D. J. Smithies, T. E. Milner, J. S. Nelson, M. J. van Gemert, and A. J. Welch, “Modeling laser treatment of port wine stains with a computer-reconstructed biopsy,” Lasers Surg. Med. 24(2), 151–166 (1999).
    [CrossRef] [PubMed]
  15. G. Wang, W. Cong, K. Durairaj, X. Qian, H. Shen, P. Sinn, E. Hoffman, G. McLennan, and M. Henry, “In vivo mouse studies with bioluminescence tomography,” Opt. Express 14(17), 7801–7809 (2006).
    [CrossRef] [PubMed]
  16. V. Ntziachristos, J. Ripoll, L. V. Wang, and R. Weissleder, “Looking and listening to light: the evolution of whole-body photonic imaging,” Nat. Biotechnol. 23(3), 313–320 (2005).
    [CrossRef] [PubMed]
  17. K. H. Song, G. Stoica, and L. V. Wang, “In vivo three-dimensional photoacoustic tomography of a whole mouse head,” Opt. Lett. 31(16), 2453–2455 (2006).
    [CrossRef] [PubMed]
  18. A. Rosenthal, D. Razansky, and V. Ntziachristos, “Fast semi-analytical model-based acoustic inversion for quantitative optoacoustic tomography,” IEEE Trans. Med. Imaging 29(6), 1275–1285 (2010).
    [CrossRef] [PubMed]
  19. Q. Fang, “Mesh-based Monte Carlo method using fast ray-tracing in Plücker coordinates.,” Biomed. Opt. Express 1(1), 165–175 (2010).
    [CrossRef]
  20. N. Platis and T. Theoharis, “Fast ray-tetrahedron intersection using Plücker coordinates,” J. Graphics GPU Game Tools 8(4), 37–48 (2003).
  21. E. Alerstam, T. Svensson, and S. Andersson-Engels, “CUDAMCML, User manual and implementation notes,” Available from http://www.atomic.physics.lu.se/fileadmin/atomfysik/Biophotonics/Software/CUDAMCML.pdf . (2009).
  22. E. Alerstam, T. Svensson, and S. Andersson-Engels, “Parallel computing with graphics processing units for high-speed Monte Carlo simulation of photon migration,” J. Biomed. Opt. 13(6), 060504 (2008).
    [CrossRef] [PubMed]
  23. L. A. Piegl, and W. Tiller, The NURBS Book, 2nd ed, Monographs in Visual Communications. (Springer, Berlin, 1997).
  24. J. Schöberl, “NETGEN: An advancing front 2D/3D-mesh generator based on abstract rules,” Comput. Visualization Sci. 1(1), 41–52 (1997).
    [CrossRef]
  25. B. Dogdas, D. Stout, A. F. Chatziioannou, and R. M. Leahy, “Digimouse: a 3D whole body mouse atlas from CT and cryosection data,” Phys. Med. Biol. 52(3), 577–587 (2007).
    [CrossRef] [PubMed]

2010 (5)

H. Shen and G. Wang, “A tetrahedron-based inhomogeneous Monte Carlo optical simulator,” Phys. Med. Biol. 55(4), 947–962 (2010).
[CrossRef] [PubMed]

W. Vogt, H. Shen, G. Wang, and C. G. Rylander, “Parametric study of tissue optical clearing by localized mechanical compression using combined finite element and Monte Carlo simulation,” J. Innovative Opt. Health Sci. (JIOHS) 3(3), 203–211 (2010).
[CrossRef]

Y. Lu, B. Zhu, H. Shen, J. C. Rasmussen, G. Wang, and E. M. Sevick-Muraca, “A parallel adaptive finite element simplified spherical harmonics approximation solver for frequency domain fluorescence molecular imaging,” Phys. Med. Biol. 55(16), 4625–4645 (2010).
[CrossRef] [PubMed]

A. Rosenthal, D. Razansky, and V. Ntziachristos, “Fast semi-analytical model-based acoustic inversion for quantitative optoacoustic tomography,” IEEE Trans. Med. Imaging 29(6), 1275–1285 (2010).
[CrossRef] [PubMed]

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

2008 (1)

E. Alerstam, T. Svensson, and S. Andersson-Engels, “Parallel computing with graphics processing units for high-speed Monte Carlo simulation of photon migration,” J. Biomed. Opt. 13(6), 060504 (2008).
[CrossRef] [PubMed]

2007 (3)

M. N. Rylander, Y. Feng, J. Bass, and K. R. Diller, “Heat shock protein expression and injury optimization for laser therapy design,” Lasers Surg. Med. 39(9), 731–746 (2007).
[CrossRef] [PubMed]

B. Dogdas, D. Stout, A. F. Chatziioannou, and R. M. Leahy, “Digimouse: a 3D whole body mouse atlas from CT and cryosection data,” Phys. Med. Biol. 52(3), 577–587 (2007).
[CrossRef] [PubMed]

E. Margallo-Balbás and P. J. French, “Shape based Monte Carlo code for light transport in complex heterogeneous tissues,” Opt. Express 15(21), 14086–14098 (2007).
[CrossRef] [PubMed]

2006 (2)

2005 (1)

V. Ntziachristos, J. Ripoll, L. V. Wang, and R. Weissleder, “Looking and listening to light: the evolution of whole-body photonic imaging,” Nat. Biotechnol. 23(3), 313–320 (2005).
[CrossRef] [PubMed]

2004 (2)

C. G. Rylander, D. P. Davé, T. Akkin, T. E. Milner, K. R. Diller, and A. J. Welch, “Quantitative phase-contrast imaging of cells with phase-sensitive optical coherence microscopy,” Opt. Lett. 29(13), 1509–1511 (2004).
[CrossRef] [PubMed]

H. Li, J. Tian, F. Zhu, W. Cong, L. V. Wang, E. A. Hoffman, and G. Wang, “A mouse optical simulation environment (MOSE) to investigate bioluminescent phenomena in the living mouse with the Monte Carlo method,” Acad. Radiol. 11(9), 1029–1038 (2004).
[CrossRef] [PubMed]

2003 (1)

N. Platis and T. Theoharis, “Fast ray-tetrahedron intersection using Plücker coordinates,” J. Graphics GPU Game Tools 8(4), 37–48 (2003).

2001 (1)

B. W. Rice, M. D. Cable, and M. B. Nelson, “In vivo imaging of light-emitting probes,” J. Biomed. Opt. 6(4), 432–440 (2001).
[CrossRef] [PubMed]

1999 (2)

T. J. Pfefer, J. K. Barton, D. J. Smithies, T. E. Milner, J. S. Nelson, M. J. van Gemert, and A. J. Welch, “Modeling laser treatment of port wine stains with a computer-reconstructed biopsy,” Lasers Surg. Med. 24(2), 151–166 (1999).
[CrossRef] [PubMed]

G. Yao and L. V. Wang, “Monte Carlo simulation of an optical coherence tomography signal in homogeneous turbid media,” Phys. Med. Biol. 44(9), 2307–2320 (1999).
[CrossRef] [PubMed]

1997 (1)

J. Schöberl, “NETGEN: An advancing front 2D/3D-mesh generator based on abstract rules,” Comput. Visualization Sci. 1(1), 41–52 (1997).
[CrossRef]

1995 (1)

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

1990 (1)

W. F. Cheong, S. A. Prahl, and A. J. Welch, “A review of the optical-properties of biological tissues,” IEEE J. Quantum Electron. 26(12), 2166–2185 (1990).
[CrossRef]

Akkin, T.

Alerstam, E.

E. Alerstam, T. Svensson, and S. Andersson-Engels, “Parallel computing with graphics processing units for high-speed Monte Carlo simulation of photon migration,” J. Biomed. Opt. 13(6), 060504 (2008).
[CrossRef] [PubMed]

Andersson-Engels, S.

E. Alerstam, T. Svensson, and S. Andersson-Engels, “Parallel computing with graphics processing units for high-speed Monte Carlo simulation of photon migration,” J. Biomed. Opt. 13(6), 060504 (2008).
[CrossRef] [PubMed]

Barton, J. K.

T. J. Pfefer, J. K. Barton, D. J. Smithies, T. E. Milner, J. S. Nelson, M. J. van Gemert, and A. J. Welch, “Modeling laser treatment of port wine stains with a computer-reconstructed biopsy,” Lasers Surg. Med. 24(2), 151–166 (1999).
[CrossRef] [PubMed]

Bass, J.

M. N. Rylander, Y. Feng, J. Bass, and K. R. Diller, “Heat shock protein expression and injury optimization for laser therapy design,” Lasers Surg. Med. 39(9), 731–746 (2007).
[CrossRef] [PubMed]

Cable, M. D.

B. W. Rice, M. D. Cable, and M. B. Nelson, “In vivo imaging of light-emitting probes,” J. Biomed. Opt. 6(4), 432–440 (2001).
[CrossRef] [PubMed]

Chatziioannou, A. F.

B. Dogdas, D. Stout, A. F. Chatziioannou, and R. M. Leahy, “Digimouse: a 3D whole body mouse atlas from CT and cryosection data,” Phys. Med. Biol. 52(3), 577–587 (2007).
[CrossRef] [PubMed]

Cheong, W. F.

W. F. Cheong, S. A. Prahl, and A. J. Welch, “A review of the optical-properties of biological tissues,” IEEE J. Quantum Electron. 26(12), 2166–2185 (1990).
[CrossRef]

Cong, W.

G. Wang, W. Cong, K. Durairaj, X. Qian, H. Shen, P. Sinn, E. Hoffman, G. McLennan, and M. Henry, “In vivo mouse studies with bioluminescence tomography,” Opt. Express 14(17), 7801–7809 (2006).
[CrossRef] [PubMed]

H. Li, J. Tian, F. Zhu, W. Cong, L. V. Wang, E. A. Hoffman, and G. Wang, “A mouse optical simulation environment (MOSE) to investigate bioluminescent phenomena in the living mouse with the Monte Carlo method,” Acad. Radiol. 11(9), 1029–1038 (2004).
[CrossRef] [PubMed]

Davé, D. P.

Diller, K. R.

M. N. Rylander, Y. Feng, J. Bass, and K. R. Diller, “Heat shock protein expression and injury optimization for laser therapy design,” Lasers Surg. Med. 39(9), 731–746 (2007).
[CrossRef] [PubMed]

C. G. Rylander, D. P. Davé, T. Akkin, T. E. Milner, K. R. Diller, and A. J. Welch, “Quantitative phase-contrast imaging of cells with phase-sensitive optical coherence microscopy,” Opt. Lett. 29(13), 1509–1511 (2004).
[CrossRef] [PubMed]

Dogdas, B.

B. Dogdas, D. Stout, A. F. Chatziioannou, and R. M. Leahy, “Digimouse: a 3D whole body mouse atlas from CT and cryosection data,” Phys. Med. Biol. 52(3), 577–587 (2007).
[CrossRef] [PubMed]

Durairaj, K.

Fang, Q.

Feng, Y.

M. N. Rylander, Y. Feng, J. Bass, and K. R. Diller, “Heat shock protein expression and injury optimization for laser therapy design,” Lasers Surg. Med. 39(9), 731–746 (2007).
[CrossRef] [PubMed]

French, P. J.

Henry, M.

Hoffman, E.

Hoffman, E. A.

H. Li, J. Tian, F. Zhu, W. Cong, L. V. Wang, E. A. Hoffman, and G. Wang, “A mouse optical simulation environment (MOSE) to investigate bioluminescent phenomena in the living mouse with the Monte Carlo method,” Acad. Radiol. 11(9), 1029–1038 (2004).
[CrossRef] [PubMed]

Jacques, S. L.

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

Leahy, R. M.

B. Dogdas, D. Stout, A. F. Chatziioannou, and R. M. Leahy, “Digimouse: a 3D whole body mouse atlas from CT and cryosection data,” Phys. Med. Biol. 52(3), 577–587 (2007).
[CrossRef] [PubMed]

Li, H.

H. Li, J. Tian, F. Zhu, W. Cong, L. V. Wang, E. A. Hoffman, and G. Wang, “A mouse optical simulation environment (MOSE) to investigate bioluminescent phenomena in the living mouse with the Monte Carlo method,” Acad. Radiol. 11(9), 1029–1038 (2004).
[CrossRef] [PubMed]

Lu, Y.

Y. Lu, B. Zhu, H. Shen, J. C. Rasmussen, G. Wang, and E. M. Sevick-Muraca, “A parallel adaptive finite element simplified spherical harmonics approximation solver for frequency domain fluorescence molecular imaging,” Phys. Med. Biol. 55(16), 4625–4645 (2010).
[CrossRef] [PubMed]

Margallo-Balbás, E.

McLennan, G.

Milner, T. E.

C. G. Rylander, D. P. Davé, T. Akkin, T. E. Milner, K. R. Diller, and A. J. Welch, “Quantitative phase-contrast imaging of cells with phase-sensitive optical coherence microscopy,” Opt. Lett. 29(13), 1509–1511 (2004).
[CrossRef] [PubMed]

T. J. Pfefer, J. K. Barton, D. J. Smithies, T. E. Milner, J. S. Nelson, M. J. van Gemert, and A. J. Welch, “Modeling laser treatment of port wine stains with a computer-reconstructed biopsy,” Lasers Surg. Med. 24(2), 151–166 (1999).
[CrossRef] [PubMed]

Nelson, J. S.

T. J. Pfefer, J. K. Barton, D. J. Smithies, T. E. Milner, J. S. Nelson, M. J. van Gemert, and A. J. Welch, “Modeling laser treatment of port wine stains with a computer-reconstructed biopsy,” Lasers Surg. Med. 24(2), 151–166 (1999).
[CrossRef] [PubMed]

Nelson, M. B.

B. W. Rice, M. D. Cable, and M. B. Nelson, “In vivo imaging of light-emitting probes,” J. Biomed. Opt. 6(4), 432–440 (2001).
[CrossRef] [PubMed]

Ntziachristos, V.

A. Rosenthal, D. Razansky, and V. Ntziachristos, “Fast semi-analytical model-based acoustic inversion for quantitative optoacoustic tomography,” IEEE Trans. Med. Imaging 29(6), 1275–1285 (2010).
[CrossRef] [PubMed]

V. Ntziachristos, J. Ripoll, L. V. Wang, and R. Weissleder, “Looking and listening to light: the evolution of whole-body photonic imaging,” Nat. Biotechnol. 23(3), 313–320 (2005).
[CrossRef] [PubMed]

Pfefer, T. J.

T. J. Pfefer, J. K. Barton, D. J. Smithies, T. E. Milner, J. S. Nelson, M. J. van Gemert, and A. J. Welch, “Modeling laser treatment of port wine stains with a computer-reconstructed biopsy,” Lasers Surg. Med. 24(2), 151–166 (1999).
[CrossRef] [PubMed]

Platis, N.

N. Platis and T. Theoharis, “Fast ray-tetrahedron intersection using Plücker coordinates,” J. Graphics GPU Game Tools 8(4), 37–48 (2003).

Prahl, S. A.

W. F. Cheong, S. A. Prahl, and A. J. Welch, “A review of the optical-properties of biological tissues,” IEEE J. Quantum Electron. 26(12), 2166–2185 (1990).
[CrossRef]

Qian, X.

Rasmussen, J. C.

Y. Lu, B. Zhu, H. Shen, J. C. Rasmussen, G. Wang, and E. M. Sevick-Muraca, “A parallel adaptive finite element simplified spherical harmonics approximation solver for frequency domain fluorescence molecular imaging,” Phys. Med. Biol. 55(16), 4625–4645 (2010).
[CrossRef] [PubMed]

Razansky, D.

A. Rosenthal, D. Razansky, and V. Ntziachristos, “Fast semi-analytical model-based acoustic inversion for quantitative optoacoustic tomography,” IEEE Trans. Med. Imaging 29(6), 1275–1285 (2010).
[CrossRef] [PubMed]

Rice, B. W.

B. W. Rice, M. D. Cable, and M. B. Nelson, “In vivo imaging of light-emitting probes,” J. Biomed. Opt. 6(4), 432–440 (2001).
[CrossRef] [PubMed]

Ripoll, J.

V. Ntziachristos, J. Ripoll, L. V. Wang, and R. Weissleder, “Looking and listening to light: the evolution of whole-body photonic imaging,” Nat. Biotechnol. 23(3), 313–320 (2005).
[CrossRef] [PubMed]

Rosenthal, A.

A. Rosenthal, D. Razansky, and V. Ntziachristos, “Fast semi-analytical model-based acoustic inversion for quantitative optoacoustic tomography,” IEEE Trans. Med. Imaging 29(6), 1275–1285 (2010).
[CrossRef] [PubMed]

Rylander, C. G.

W. Vogt, H. Shen, G. Wang, and C. G. Rylander, “Parametric study of tissue optical clearing by localized mechanical compression using combined finite element and Monte Carlo simulation,” J. Innovative Opt. Health Sci. (JIOHS) 3(3), 203–211 (2010).
[CrossRef]

C. G. Rylander, D. P. Davé, T. Akkin, T. E. Milner, K. R. Diller, and A. J. Welch, “Quantitative phase-contrast imaging of cells with phase-sensitive optical coherence microscopy,” Opt. Lett. 29(13), 1509–1511 (2004).
[CrossRef] [PubMed]

Rylander, M. N.

M. N. Rylander, Y. Feng, J. Bass, and K. R. Diller, “Heat shock protein expression and injury optimization for laser therapy design,” Lasers Surg. Med. 39(9), 731–746 (2007).
[CrossRef] [PubMed]

Schöberl, J.

J. Schöberl, “NETGEN: An advancing front 2D/3D-mesh generator based on abstract rules,” Comput. Visualization Sci. 1(1), 41–52 (1997).
[CrossRef]

Sevick-Muraca, E. M.

Y. Lu, B. Zhu, H. Shen, J. C. Rasmussen, G. Wang, and E. M. Sevick-Muraca, “A parallel adaptive finite element simplified spherical harmonics approximation solver for frequency domain fluorescence molecular imaging,” Phys. Med. Biol. 55(16), 4625–4645 (2010).
[CrossRef] [PubMed]

Shen, H.

Y. Lu, B. Zhu, H. Shen, J. C. Rasmussen, G. Wang, and E. M. Sevick-Muraca, “A parallel adaptive finite element simplified spherical harmonics approximation solver for frequency domain fluorescence molecular imaging,” Phys. Med. Biol. 55(16), 4625–4645 (2010).
[CrossRef] [PubMed]

W. Vogt, H. Shen, G. Wang, and C. G. Rylander, “Parametric study of tissue optical clearing by localized mechanical compression using combined finite element and Monte Carlo simulation,” J. Innovative Opt. Health Sci. (JIOHS) 3(3), 203–211 (2010).
[CrossRef]

H. Shen and G. Wang, “A tetrahedron-based inhomogeneous Monte Carlo optical simulator,” Phys. Med. Biol. 55(4), 947–962 (2010).
[CrossRef] [PubMed]

G. Wang, W. Cong, K. Durairaj, X. Qian, H. Shen, P. Sinn, E. Hoffman, G. McLennan, and M. Henry, “In vivo mouse studies with bioluminescence tomography,” Opt. Express 14(17), 7801–7809 (2006).
[CrossRef] [PubMed]

Sinn, P.

Smithies, D. J.

T. J. Pfefer, J. K. Barton, D. J. Smithies, T. E. Milner, J. S. Nelson, M. J. van Gemert, and A. J. Welch, “Modeling laser treatment of port wine stains with a computer-reconstructed biopsy,” Lasers Surg. Med. 24(2), 151–166 (1999).
[CrossRef] [PubMed]

Song, K. H.

Stoica, G.

Stout, D.

B. Dogdas, D. Stout, A. F. Chatziioannou, and R. M. Leahy, “Digimouse: a 3D whole body mouse atlas from CT and cryosection data,” Phys. Med. Biol. 52(3), 577–587 (2007).
[CrossRef] [PubMed]

Svensson, T.

E. Alerstam, T. Svensson, and S. Andersson-Engels, “Parallel computing with graphics processing units for high-speed Monte Carlo simulation of photon migration,” J. Biomed. Opt. 13(6), 060504 (2008).
[CrossRef] [PubMed]

Theoharis, T.

N. Platis and T. Theoharis, “Fast ray-tetrahedron intersection using Plücker coordinates,” J. Graphics GPU Game Tools 8(4), 37–48 (2003).

Tian, J.

H. Li, J. Tian, F. Zhu, W. Cong, L. V. Wang, E. A. Hoffman, and G. Wang, “A mouse optical simulation environment (MOSE) to investigate bioluminescent phenomena in the living mouse with the Monte Carlo method,” Acad. Radiol. 11(9), 1029–1038 (2004).
[CrossRef] [PubMed]

van Gemert, M. J.

T. J. Pfefer, J. K. Barton, D. J. Smithies, T. E. Milner, J. S. Nelson, M. J. van Gemert, and A. J. Welch, “Modeling laser treatment of port wine stains with a computer-reconstructed biopsy,” Lasers Surg. Med. 24(2), 151–166 (1999).
[CrossRef] [PubMed]

Vogt, W.

W. Vogt, H. Shen, G. Wang, and C. G. Rylander, “Parametric study of tissue optical clearing by localized mechanical compression using combined finite element and Monte Carlo simulation,” J. Innovative Opt. Health Sci. (JIOHS) 3(3), 203–211 (2010).
[CrossRef]

Wang, G.

W. Vogt, H. Shen, G. Wang, and C. G. Rylander, “Parametric study of tissue optical clearing by localized mechanical compression using combined finite element and Monte Carlo simulation,” J. Innovative Opt. Health Sci. (JIOHS) 3(3), 203–211 (2010).
[CrossRef]

Y. Lu, B. Zhu, H. Shen, J. C. Rasmussen, G. Wang, and E. M. Sevick-Muraca, “A parallel adaptive finite element simplified spherical harmonics approximation solver for frequency domain fluorescence molecular imaging,” Phys. Med. Biol. 55(16), 4625–4645 (2010).
[CrossRef] [PubMed]

H. Shen and G. Wang, “A tetrahedron-based inhomogeneous Monte Carlo optical simulator,” Phys. Med. Biol. 55(4), 947–962 (2010).
[CrossRef] [PubMed]

G. Wang, W. Cong, K. Durairaj, X. Qian, H. Shen, P. Sinn, E. Hoffman, G. McLennan, and M. Henry, “In vivo mouse studies with bioluminescence tomography,” Opt. Express 14(17), 7801–7809 (2006).
[CrossRef] [PubMed]

H. Li, J. Tian, F. Zhu, W. Cong, L. V. Wang, E. A. Hoffman, and G. Wang, “A mouse optical simulation environment (MOSE) to investigate bioluminescent phenomena in the living mouse with the Monte Carlo method,” Acad. Radiol. 11(9), 1029–1038 (2004).
[CrossRef] [PubMed]

Wang, L.

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

Wang, L. V.

K. H. Song, G. Stoica, and L. V. Wang, “In vivo three-dimensional photoacoustic tomography of a whole mouse head,” Opt. Lett. 31(16), 2453–2455 (2006).
[CrossRef] [PubMed]

V. Ntziachristos, J. Ripoll, L. V. Wang, and R. Weissleder, “Looking and listening to light: the evolution of whole-body photonic imaging,” Nat. Biotechnol. 23(3), 313–320 (2005).
[CrossRef] [PubMed]

H. Li, J. Tian, F. Zhu, W. Cong, L. V. Wang, E. A. Hoffman, and G. Wang, “A mouse optical simulation environment (MOSE) to investigate bioluminescent phenomena in the living mouse with the Monte Carlo method,” Acad. Radiol. 11(9), 1029–1038 (2004).
[CrossRef] [PubMed]

G. Yao and L. V. Wang, “Monte Carlo simulation of an optical coherence tomography signal in homogeneous turbid media,” Phys. Med. Biol. 44(9), 2307–2320 (1999).
[CrossRef] [PubMed]

Weissleder, R.

V. Ntziachristos, J. Ripoll, L. V. Wang, and R. Weissleder, “Looking and listening to light: the evolution of whole-body photonic imaging,” Nat. Biotechnol. 23(3), 313–320 (2005).
[CrossRef] [PubMed]

Welch, A. J.

C. G. Rylander, D. P. Davé, T. Akkin, T. E. Milner, K. R. Diller, and A. J. Welch, “Quantitative phase-contrast imaging of cells with phase-sensitive optical coherence microscopy,” Opt. Lett. 29(13), 1509–1511 (2004).
[CrossRef] [PubMed]

T. J. Pfefer, J. K. Barton, D. J. Smithies, T. E. Milner, J. S. Nelson, M. J. van Gemert, and A. J. Welch, “Modeling laser treatment of port wine stains with a computer-reconstructed biopsy,” Lasers Surg. Med. 24(2), 151–166 (1999).
[CrossRef] [PubMed]

W. F. Cheong, S. A. Prahl, and A. J. Welch, “A review of the optical-properties of biological tissues,” IEEE J. Quantum Electron. 26(12), 2166–2185 (1990).
[CrossRef]

Yao, G.

G. Yao and L. V. Wang, “Monte Carlo simulation of an optical coherence tomography signal in homogeneous turbid media,” Phys. Med. Biol. 44(9), 2307–2320 (1999).
[CrossRef] [PubMed]

Zheng, L.

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

Zhu, B.

Y. Lu, B. Zhu, H. Shen, J. C. Rasmussen, G. Wang, and E. M. Sevick-Muraca, “A parallel adaptive finite element simplified spherical harmonics approximation solver for frequency domain fluorescence molecular imaging,” Phys. Med. Biol. 55(16), 4625–4645 (2010).
[CrossRef] [PubMed]

Zhu, F.

H. Li, J. Tian, F. Zhu, W. Cong, L. V. Wang, E. A. Hoffman, and G. Wang, “A mouse optical simulation environment (MOSE) to investigate bioluminescent phenomena in the living mouse with the Monte Carlo method,” Acad. Radiol. 11(9), 1029–1038 (2004).
[CrossRef] [PubMed]

Acad. Radiol. (1)

H. Li, J. Tian, F. Zhu, W. Cong, L. V. Wang, E. A. Hoffman, and G. Wang, “A mouse optical simulation environment (MOSE) to investigate bioluminescent phenomena in the living mouse with the Monte Carlo method,” Acad. Radiol. 11(9), 1029–1038 (2004).
[CrossRef] [PubMed]

Biomed. Opt. Express (1)

Comput. Methods Programs Biomed. (1)

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

Comput. Visualization Sci. (1)

J. Schöberl, “NETGEN: An advancing front 2D/3D-mesh generator based on abstract rules,” Comput. Visualization Sci. 1(1), 41–52 (1997).
[CrossRef]

IEEE J. Quantum Electron. (1)

W. F. Cheong, S. A. Prahl, and A. J. Welch, “A review of the optical-properties of biological tissues,” IEEE J. Quantum Electron. 26(12), 2166–2185 (1990).
[CrossRef]

IEEE Trans. Med. Imaging (1)

A. Rosenthal, D. Razansky, and V. Ntziachristos, “Fast semi-analytical model-based acoustic inversion for quantitative optoacoustic tomography,” IEEE Trans. Med. Imaging 29(6), 1275–1285 (2010).
[CrossRef] [PubMed]

J. Biomed. Opt. (2)

E. Alerstam, T. Svensson, and S. Andersson-Engels, “Parallel computing with graphics processing units for high-speed Monte Carlo simulation of photon migration,” J. Biomed. Opt. 13(6), 060504 (2008).
[CrossRef] [PubMed]

B. W. Rice, M. D. Cable, and M. B. Nelson, “In vivo imaging of light-emitting probes,” J. Biomed. Opt. 6(4), 432–440 (2001).
[CrossRef] [PubMed]

J. Graphics GPU Game Tools (1)

N. Platis and T. Theoharis, “Fast ray-tetrahedron intersection using Plücker coordinates,” J. Graphics GPU Game Tools 8(4), 37–48 (2003).

J. Innovative Opt. Health Sci. (JIOHS) (1)

W. Vogt, H. Shen, G. Wang, and C. G. Rylander, “Parametric study of tissue optical clearing by localized mechanical compression using combined finite element and Monte Carlo simulation,” J. Innovative Opt. Health Sci. (JIOHS) 3(3), 203–211 (2010).
[CrossRef]

Lasers Surg. Med. (2)

M. N. Rylander, Y. Feng, J. Bass, and K. R. Diller, “Heat shock protein expression and injury optimization for laser therapy design,” Lasers Surg. Med. 39(9), 731–746 (2007).
[CrossRef] [PubMed]

T. J. Pfefer, J. K. Barton, D. J. Smithies, T. E. Milner, J. S. Nelson, M. J. van Gemert, and A. J. Welch, “Modeling laser treatment of port wine stains with a computer-reconstructed biopsy,” Lasers Surg. Med. 24(2), 151–166 (1999).
[CrossRef] [PubMed]

Nat. Biotechnol. (1)

V. Ntziachristos, J. Ripoll, L. V. Wang, and R. Weissleder, “Looking and listening to light: the evolution of whole-body photonic imaging,” Nat. Biotechnol. 23(3), 313–320 (2005).
[CrossRef] [PubMed]

Opt. Express (2)

Opt. Lett. (2)

Phys. Med. Biol. (4)

B. Dogdas, D. Stout, A. F. Chatziioannou, and R. M. Leahy, “Digimouse: a 3D whole body mouse atlas from CT and cryosection data,” Phys. Med. Biol. 52(3), 577–587 (2007).
[CrossRef] [PubMed]

Y. Lu, B. Zhu, H. Shen, J. C. Rasmussen, G. Wang, and E. M. Sevick-Muraca, “A parallel adaptive finite element simplified spherical harmonics approximation solver for frequency domain fluorescence molecular imaging,” Phys. Med. Biol. 55(16), 4625–4645 (2010).
[CrossRef] [PubMed]

G. Yao and L. V. Wang, “Monte Carlo simulation of an optical coherence tomography signal in homogeneous turbid media,” Phys. Med. Biol. 44(9), 2307–2320 (1999).
[CrossRef] [PubMed]

H. Shen and G. Wang, “A tetrahedron-based inhomogeneous Monte Carlo optical simulator,” Phys. Med. Biol. 55(4), 947–962 (2010).
[CrossRef] [PubMed]

Other (4)

A. Appel, “Some techniques for shading machine renderings of solids,” AFIPS Joint Computer Conferences. Atlantic City, New Jersey (1968).

J. D. Foley, Computer Graphics: Principles and Practice, 2nd ed (Addison-Wesley, Reading, Mass., 1995).

L. A. Piegl, and W. Tiller, The NURBS Book, 2nd ed, Monographs in Visual Communications. (Springer, Berlin, 1997).

E. Alerstam, T. Svensson, and S. Andersson-Engels, “CUDAMCML, User manual and implementation notes,” Available from http://www.atomic.physics.lu.se/fileadmin/atomfysik/Biophotonics/Software/CUDAMCML.pdf . (2009).

Cited By

OSA participates in CrossRef's Cited-By Linking service. Citing articles from OSA journals and other participating publishers are listed here.

Alert me when this article is cited.


Figures (5)

Fig. 1
Fig. 1

Illustration of photon-mesh intersection under imaging rendering scenario and optical Monte Carlo simulation. (a) A photon may not hit the closest triangle in a general triangle mesh in imaging rendering, and (b) if a photon is inside a tetrahedron, then the photon will hit the closest triangle internally.

Fig. 2
Fig. 2

A cubic phantom with linearly varying optical parameter distributions and three sources.

Fig. 3
Fig. 3

Time resolved simulation for a laser pulse. (a) A spherical lens in air, (b), (c), (d) and (e) the simulation results for the phantom (a) at time instants 0.1 ps, 4.9 ps, 10 ps and 15 ps, respectively; (f) A spherical lens under tissue, (g), (h), (i) and (j) the simulation results for the phantom (f) at time instants 0.1 ps, 4.9 ps, 10 ps and 15 ps, respectively.

Fig. 4
Fig. 4

Pseudo-code for the photon-tetrahedron intersection test in the TIM-OS scheme.

Fig. 5
Fig. 5

Pseudo-code for the photon-tetrahedron intersection test in the Plücker scheme.

Tables (5)

Tables Icon

Table 1 Differences between the original and hybrid TIM-OS schemes. TIM-OS represents piece-wise constant scheme and TIM-OS-L stands for linear Lagrange scheme.

Tables Icon

Table 2 Optical parameters for air, glass, and tissue used in TIM-OS

Tables Icon

Table 3 Comparison among MCML, CUDAMCML, MMC, and TIM-OS in a numerical study with a single-layer and two-layer tissue phantoms

Tables Icon

Table 4 Absorbed fractions with the single layer tissue phantom and different numbers of photons

Tables Icon

Table 5 Absorbed fractions computed with the mouse atlas in the high and low absorption cases

Equations (9)

Equations on this page are rendered with MathJax. Learn more.

P = i = 1 4 l i P i  with  i = 1 4 l i = 1  and  0 l i 1.
[ l 1 l 2 l 3 ] = [ P 1 P 4 , P 2 P 4 , P 3 P 4 ] 1 [ P P 4 ] .
[ l ' 1 l ' 2 l ' 3 ] = [ P 1 P 4 , P 2 P 4 , P 3 P 4 ] 1 [ P + U s P 4 ] = [ l 1 l 2 l 3 ] + [ P 1 P 4 , P 2 P 4 , P 3 P 4 ] 1 [ U ] s .
[ Δ l 1 Δ l 2 Δ l 3 ] = [ P 1 P 4 , P 2 P 4 , P 3 P 4 ] 1 [ U ]
[ l ' 1 l ' 2 l ' 3 l ' 4 ] = [ l 1 l 2 l 3 l 4 ] + [ Δ l 1 Δ l 2 Δ l 3 ( Δ l 1 + Δ l 2 + Δ l 3 ) ] s .
μ ' = [ l ' 1 l ' 2 l ' 3 l ' 4 ] [ μ 1 μ 2 μ 3 μ 4 ] = μ + ( Δ l 1 ( μ 1 μ 4 ) + Δ l 2 ( μ 2 μ 4 ) + Δ l 3 ( μ 3 μ 4 ) ) s .
0 s μ t + a x d x = 1 2 a s 2 + μ t s = ln ( ξ )
g ' = i = 1 4 l i g i
Φ = ( E a j μ a j ) / V

Metrics