SPIEDL Logo
Search Text Line
 
SPIE DL Tab Proceedings Tab Journals Tab JBO Tab EBooks Tab
JBO banner
My Subscription  | My Email Alerts  | My Article Collections

GENERAL INFORMATION

Journal of Biomedical Optics / Volume 13 / Issue 6 / JBO Letters

Parallel computing with graphics processing units for high-speed Monte Carlo simulation of photon migration

J. Biomed. Opt. 13, 060504 (Dec 16, 2008); http://dx.doi.org/10.1117/1.3041496

Erik Alerstam, Tomas Svensson, and Stefan Andersson-Engels

Lund University, Department of Physics, Lund 22100, Sweden

General-purpose computing on graphics processing units (GPGPU) is shown to dramatically increase the speed of Monte Carlo simulations of photon migration. In a standard simulation of time-resolved photon migration in a semi-infinite geometry, the proposed methodology executed on a low-cost graphics processing unit (GPU) is a factor 1000 faster than simulation performed on a single standard processor. In addition, we address important technical aspects of GPU-based simulations of photon migration. The technique is expected to become a standard method in Monte Carlo simulations of photon migration.

© 2008 Society of Photo-Optical Instrumentation Engineers

History
Received Jul 16, 2008
Accepted Oct 15, 2008
Revised Oct 08, 2008
Published online Dec 16, 2008
Digital Object Identifier
http://dx.doi.org/10.1117/1.3041496
Citation
Erik Alerstam, Tomas Svensson and Stefan Andersson-Engels, "Parallel computing with graphics processing units for high-speed Monte Carlo simulation of photon migration", J. Biomed. Opt. 13, 060504 (Dec 16, 2008); http://dx.doi.org/10.1117/1.3041496

DOWNLOAD ARTICLE

OPEN ACCESS

FULL-TEXT OPTIONS:

RELATED CONTENT

More Like This Article

loading

  1. D. A. Boas, J. P. Culver, J. J. Stott, and A. K. Dunn, “Three dimensional Monte Carlo code for photon migration through complex heterogeneous media including the adult human head,” Opt. Express 10(3), 159–170 (2002). [SPIN] [MEDLINE]
  2. K. Vishwanath, B. Pogue, and M. A. Mycek, “Quantitative fluorescence lifetime spectroscopy in turbid media: comparison of theoretical, experimental and computational methods,” Phys. Med. Biol. 47(18), 3387–3405 (2002). [MEDLINE]
  3. N. Everall, T. Hahn, P. Matousek, A. W. Parker, and M. Towrie, “Photon migration in Raman spectroscopy,” Appl. Spectrosc. 58(5), 591–597 (2004). [ISI] [MEDLINE]
  4. S. T. Flock, M. S. Patterson, B. C. Wilson, and D. R. Wyman, “Monte Carlo modeling of light-propagation in highly scattering tissues: I model predictions and comparison with diffusion-theory,” IEEE Trans. Biomed. Eng. 36(12), 1162–1168 (1989). [MEDLINE]
  5. M. S. Patterson, B. Chance, and B. C. Wilson, “Time resolved reflectance and transmittance for the noninvasive measurement of tissue optical-properties,” Appl. Opt. 28(12), 2331–2336 (1989). [ISI] [MEDLINE]
  6. F. Martelli, D. Contini, A. Taddeucci, and G. Zaccanti, “Photon migration through a turbid slab described by a model based on diffusion approximation: II. Comparison with Monte Carlo results,” Appl. Opt. 36(19), 4600–4612 (1997). [ISI] [MEDLINE]
  7. C. R. Simpson, M. Kohl, M. Essenpreis, and M. Cope, “Near-infrared optical properties of ex vivo human skin and subcutaneous tissues measured using the Monte Carlo inversion technique,” Phys. Med. Biol. 43(9), 2465–2478 (1998). [Inspec] [ISI] [MEDLINE]
  8. F. Bevilacqua, D. Piguet, P. Marquet, J. D. Gross, B. J. Tromberg, and C. Depeursinge, “In vivo local determination of tissue optical properties: applications to human brain,” Appl. Opt. 38(22), 4939–4950 (1999). [ISI] [MEDLINE]
  9. G. M. Palmer and N. Ramanujam, “Monte Carlo-based inverse model for calculating tissue optical properties. Part i: theory and validation on synthetic phantoms,” Appl. Opt. 45(5), 1062–1071 (2006). [MEDLINE]
  10. C. K. Hayakawa, J. Spanier, F. Bevilacqua, A. K. Dunn, J. S. You, B. J. Tromberg, and V. Venugopalan, “Perturbation Monte Carlo methods to solve inverse photon migration problems in heterogeneous tissues,” Opt. Lett. 26(17), 1335–1337 (2001). [MEDLINE]
  11. E. Alerstam, S. Andersson-Engels, and T. Svensson, “White Monte Carlo for time-resolved photon migration,” J. Biomed. Opt. 13(4), 041304 (2008)JBOPFO000013000004041304000001. [MEDLINE]
  12. E. Alerstam, S. Andersson-Engels, and T. Svensson, “Improved accuracy in time-resolved diffuse reflectance spectroscopy,” Opt. Express 16(14), 10434–10448 (2008). [MEDLINE]
  13. T. Svensson, E. Alerstam, M. Einarsdóttír, K. Svanberg, and S. Andersson-Engels, “Towards accuracte in vivo spectroscopy of the human prostate,” J. Biophoton., 1(3), 200–203 (2008).
  14. L. H. Wang, S. L. Jacques, and L. Q. Zheng, “MCML Monte Carlo modeling of light transport in multilayered tissues,” Comput. Methods Programs Biomed. 47(2), 131–146 (1995). [MEDLINE]
  15. N. Zolek, A. Liebert, and R. Maniewski, “Optimization of the Monte Carlo code for modeling of photon migration in tissue,” Comput. Methods Programs Biomed.84(1), 50–57 (2006). [MEDLINE]
  16. R. Graaff, M. H. Koelink, F. F. M. Demul, W. G. Zijlstra, A. C. M. Dassel, and J. G. Aarnoudse, “Condensed Monte Carlo simulations for the description of light transport,” Appl. Opt. 32(4), 426–434 (1993). [ISI]
  17. A. Pifferi, P. Taroni, G. Valentini, and S. Andersson-Engels, “Real-time method for fitting time-resolved reflectance and transmittance measurements with a Monte Carlo model,” Appl. Opt. 37(13), 2774–2780 (1998). [MEDLINE]
  18. A. Kienle and M. S. Patterson, “Determination of the optical properties of turbid media from a single Monte Carlo simulation,” Phys. Med. Biol. 41(10), 2221–2227 (1996). [Inspec] [ISI] [MEDLINE]
  19. T. R. Halfhill, “Parallel processing with CUDA,” Microprocessor Report, (Jan. 2008).
  20. NVIDIA webpage (June 2008): http://www.nvidia. com.
  21. D. Blythe, “Rise of the graphics processor,” Proc. IEEE 96(5), 761–778 (2008). [Inspec]
  22. K. Gossage, U.S. Patent No. 20070282575 (2006).
  23. S. Tomov, M. McGuigan, R. Bennett, G. Smith, and J. Spiletic, “Benchmarking and implementation of probability-based simulations on programmable graphics cards,” Comput. Graph. 29(1), 71–80 (2005).
  24. M. Matsumoto and T. Nishimura, “Mersenne twister: a 623-dimensionally equidistributed uniform pseudorandom number generator,” ACM Trans. Model. Comput. Simul. 8(1), 3–30 (1998).
  25. G. Marsaglia, “Random number generators,” J. Mod. Appl. Stat. Meth. 2(1), 2–13 (2003).
  26. D. R. Kirkby and D. T. Delpy, “Parallel operation of Monte Carlo simulations on a diverse network of computers,” Phys. Med. Biol. 42(6), 1203–1208 (1997). [Inspec] [ISI] [MEDLINE]
  27. A. Colasanti, G. Guida, A. Kisslinger, R. Liuzzi, M. Quarto, P. Riccio, G. Roberti, and F. Villani, “Multiple processor version of a Monte Carlo code for photon transport in turbid media,” Comput. Phys. Commun. 132(1–2), 84–93 (2000). [Inspec] [ISI]


Close

Your Recent History Recent History Help

Recently Viewed

  1. Parallel computing with graphics processing units for high-speed Monte Carlo simulation of photon migration
  2. Suture-free laser-assisted vessel repair using CO2 laser and liquid albumin solder
  3. Monitoring of hexyl 5-aminolevulinate-induced photodynamic therapy in rat bladder cancer by optical spectroscopy
  4. Erratum: Study on the in vitro and in vivo activation of rat hepatic stellate cells by Raman spectroscopy
  5. Two-photon bioimaging utilizing supercontinuum light generated by a high-peak-power picosecond semiconductor laser source
Home Proceedings Journals SPIE eBooks
Privacy Policy Terms of Use Contact Us

SPIE © 1990 - 2012

close