OSA's Digital Library

Virtual Journal for Biomedical Optics

Virtual Journal for Biomedical Optics

| EXPLORING THE INTERFACE OF LIGHT AND BIOMEDICINE

  • Editor: Gregory W. Faris
  • Vol. 5, Iss. 7 — Apr. 26, 2010

GPU-based Monte Carlo simulation for light propagation in complex heterogeneous tissues

Nunu Ren, Jimin Liang, Xiaochao Qu, Jianfeng Li, Bingjia Lu, and Jie Tian  »View Author Affiliations


Optics Express, Vol. 18, Issue 7, pp. 6811-6823 (2010)
http://dx.doi.org/10.1364/OE.18.006811


View Full Text Article

Enhanced HTML    Acrobat PDF (2488 KB) Open Access





Browse Journals / Lookup Meetings

Browse by Journal and Year


   


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools

Share
Citations

Abstract

As the most accurate model for simulating light propagation in heterogeneous tissues, Monte Carlo (MC) method has been widely used in the field of optical molecular imaging. However, MC method is time-consuming due to the calculations of a large number of photons propagation in tissues. The structural complexity of the heterogeneous tissues further increases the computational time. In this paper we present a parallel implementation for MC simulation of light propagation in heterogeneous tissues whose surfaces are constructed by different number of triangle meshes. On the basis of graphics processing units (GPU), the code is implemented with compute unified device architecture (CUDA) platform and optimized to reduce the access latency as much as possible by making full use of the constant memory and texture memory on GPU. We test the implementation in the homogeneous and heterogeneous mouse models with a NVIDIA GTX 260 card and a 2.40GHz Intel Xeon CPU. The experimental results demonstrate the feasibility and efficiency of the parallel MC simulation on GPU.

© 2010 OSA

OCIS Codes
(170.3660) Medical optics and biotechnology : Light propagation in tissues
(170.5280) Medical optics and biotechnology : Photon migration
(170.7050) Medical optics and biotechnology : Turbid media
(200.4960) Optics in computing : Parallel processing

ToC Category:
Medical Optics and Biotechnology

History
Original Manuscript: January 19, 2010
Revised Manuscript: February 15, 2010
Manuscript Accepted: March 11, 2010
Published: March 17, 2010

Virtual Issues
Vol. 5, Iss. 7 Virtual Journal for Biomedical Optics

Citation
Nunu Ren, Jimin Liang, Xiaochao Qu, Jianfeng Li, Bingjia Lu, and Jie Tian, "GPU-based Monte Carlo simulation for light propagation in complex heterogeneous tissues," Opt. Express 18, 6811-6823 (2010)
http://www.opticsinfobase.org/vjbo/abstract.cfm?URI=oe-18-7-6811


Sort:  Author  |  Year  |  Journal  |  Reset  

References

  1. R. Weissleder and U. Mahmood, “Molecular imaging,” Radiology 219(2), 316–333 (2001). [PubMed]
  2. R. Weissleder and M. J. Pittet, “Imaging in the era of molecular oncology,” Nature 452(7187), 580–589 (2008). [CrossRef] [PubMed]
  3. 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]
  4. 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]
  5. G. Wang, Y. Li, and M. Jiang, “Uniqueness theorems in bioluminescence tomography,” Med. Phys. 31(8), 2289–2299 (2004). [CrossRef] [PubMed]
  6. A. H. Hielscher, “Optical tomographic imaging of small animals,” Curr. Opin. Biotechnol. 16(1), 79–88 (2005). [CrossRef] [PubMed]
  7. A. P. Gibson, J. C. Hebden, and S. R. Arridge, “Recent advances in diffuse optical imaging,” Phys. Med. Biol. 50(4), R1–R43 (2005). [CrossRef] [PubMed]
  8. B. C. Wilson and G. Adam, “A Monte Carlo model for the absorption and flux distributions of light in tissue,” Med. Phys. 10(6), 824–830 (1983). [CrossRef] [PubMed]
  9. S. A. Prahl, M. Keijzer, S. L. Jacques, and A. J. Welch, “A Monte Carlo model of light propagation in tissue,” Proc. SPIE IS 5, 102–111 (1989).
  10. L. V. Wang, S. L. Jacques, and L. Q. Zheng, “MCML—Monte Carlo modeling of light transport in multi-layered tissues,” Comput. Meth. Prog. Biol. 47(2), 131–146 (1995). [CrossRef]
  11. D. A. Boas, J. Culver, J. Stott, and A. 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). [PubMed]
  12. H. Li, J. Tian, F. Zhu, W. X. 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]
  13. 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), http://www.opticsinfobase.org/abstract.cfm?URI=oe-15-21-14086 . [CrossRef] [PubMed]
  14. L. V. Wang and S. L. Jacques, “Hybrid model of Monte Carlo simulation and diffusion theory for light reflectance by turbid media,” J. Opt. Soc. Am. A 10(8), 1746–1752 (1993). [CrossRef]
  15. N. S. Zołek, A. Liebert, and R. Maniewski, “Optimization of the Monte Carlo code for modeling of photon migration in tissue,” Comput. Meth. Prog. Biol. 84(1), 50–57 (2006). [CrossRef]
  16. E. Alerstam, S. Andersson-Engels, and T. Svensson, “White Monte Carlo for time-resolved photon migration,” J. Biomed. Opt. 13(4), 041304 (2008). [CrossRef] [PubMed]
  17. 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]
  18. Q. Fang and D. A. Boas, “Monte Carlo simulation of photon migration in 3D turbid media accelerated by graphics processing units,” Opt. Express 17(22), 20178–20190 (2009), http://www.opticsinfobase.org/oe/abstract.cfm?URI=oe-17-22-20178 . [CrossRef] [PubMed]
  19. NVIDIA CUDA Compute Unified Device Architecture - Programming Guide, Version 2.3 (2009).
  20. N. Ren, and J. Tian, gpu-Molecular Optical Simulation Environment (2010). http://www.mosetm.net .
  21. J. Arenberg, “Re: Ray/Triangle Intersection with Barycentric Coordinates,” in Eric Haines, ed., Ray Tracing News, 1 (1988). http://tog.acm.org/resources/RTNews/html/rtnews5b.html#art3 .
  22. T. Möller and B. Trumbore, “Fast, minimum storage ray-triangle intersection,” J. Graphics Tools 2, 21–28 (1997).
  23. H. Lensch, and R. Strzodka, “Massively Parallel Computing with CUDA” (2008). http://www.mpi-inf.mpg.de/~strzodka/lectures/ParCo08/ .
  24. 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]
  25. G. Alexandrakis, F. R. Rannou, and A. F. Chatziioannou, “Tomographic bioluminescence imaging by use of a combined optical-PET (OPET) system: a computer simulation feasibility study,” Phys. Med. Biol. 50(17), 4225–4241 (2005). [CrossRef] [PubMed]
  26. S. Prahl, “Optical Properties Spectra” (Oregon Medical Laser Clinic, 2001). http://omlc.ogi.edu/spectra/index.html .

Cited By

Alert me when this paper is cited

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.


« Previous Article  |  Next Article »

OSA is a member of CrossRef.

CrossCheck Deposited