Abstract

Dense sampling of illumination and detection offers an effective way of improving the image-reconstruction performance of near-infrared diffuse optical tomography (DOT) at a cost of lengthy computation times. In this paper, we describe a fast DOT scheme for reconstructing the absorption coefficient image of a slab medium from dense sampling of both illumination and detection in the noncontact DOT. The proposed method is carried out with spatial-frequency encoding in both the source and detection spaces, and involves a spatial-frequency-compression (SFC) strategy for selecting the useful spatial frequency based on the tissue transfer function. The method is expected to considerably reduce the calculation time for reconstruction while improving the quality of the reconstructed images. Results from the simulated data show that the speed for absorption reconstruction with the proposed SFC method is more than 400 times faster than that with the conventional one. A noncontact DOT system for dense sampling of both illumination and detection is developed by using laser raster scanning and CCD-based data acquisition. Experimental measurements on several solid phantoms demonstrate that a high quantitativeness ratio can be obtained from the proposed method thanks to reduction of the ill-posedness of the inverse calculation. It takes less than 20 s for the proposed method to experimentally reconstruct one absorption image from a 256×256-sized dataset, which would take a few hours with the conventional method.

© 2013 Optical Society of America

Full Article  |  PDF Article

References

  • View by:
  • |
  • |
  • |

  1. A. Corlu, R. Choe, T. Durduran, M. A. Rosen, M. Schweiger, S. R. Arridge, M. D. Schnall, and A. G. Yodh, “Three-dimensional in vivo fluorescence diffuse optical tomography of breast cancer in humans,” Opt. Express 15, 6696–6716 (2007).
    [CrossRef]
  2. C. Bonnéry, M. Desjardins, P. Pouliot, and F. Lesage, “Changes in diffusion path length, with old age in diffuse optical tomography,” J. Biomed. Opt. 17, 056002 (2012).
    [CrossRef]
  3. K. L. Perdue, Q. Fang, and S. G. Diamond, “Quantitative assessment of diffuse optical tomography sensitivity to the cerebral cortex using a whole-head probe,” Phys. Med. Biol. 57, 2857–2872 (2012).
    [CrossRef]
  4. J. K. Willmann, N. V. Bruggen, L. M. Dinkelborg, and S. S. Gambhir, “Molecular imaging in drug development,” Nat. Med. 7, 591–607 (2008).
    [CrossRef]
  5. A. Koenig, L. Hervé, V. Josserand, M. Berger, J. Boutet, A. D. Silva, J.-M. Dinten, P. Peltié, J.-L. Coll, and P. Rizo, “In vivo mice lung tumor follow-up with fluorescence diffuse optical tomography,” J. Biomed. Opt. 13, 011008 (2008).
    [CrossRef]
  6. O. Lehtikangas, T. Tarvainen, and A. D. Kim, “Modeling boundary measurements of scattered light using the corrected diffusion approximation,” Biomed. Opt. Express 3, 552–571 (2012).
    [CrossRef]
  7. V. Y. Soloviev and S. R. Arridge, “Optical tomography in weakly scattering media in the presence of highly scattering inclusions,” Biomed. Opt. Express 2, 440–451 (2011).
    [CrossRef]
  8. C. D’Andrea, N. Ducros, A. Bassi, S. Arridge, and G. Valentini, “Fast 3D optical reconstruction in turbid media using spatially modulated light,” Biomed. Opt. Express 1, 471–481 (2010).
    [CrossRef]
  9. T. Shimokawa, T. Kosaka, O. Yamashita, N. Hiroe, T. Amita, Y. Inoue, and M. Sato, “Hierarchical Bayesian estimation improves depth accuracy and spatial resolution of diffuse optical tomography,” Opt. Express 20, 20427–20446(2012).
    [CrossRef]
  10. S. B. M. Abran, X. Intes, C. Casanova, and F. Lesage, “Real-time diffuse optical tomography based on structured illumination,” J. Biomed. Opt. 15, 016006 (2010).
    [CrossRef]
  11. S. R. Arridge and J. C. Schotland, “Optical tomography: forward and inverse problems,” Inverse Probl. 25, 123010 (2009).
    [CrossRef]
  12. N. Ducros, A. Bassi, G. Valentini, M. Schweiger, S. Arridge, and C. D. Andrea, “Multiple-view fluorescence optical tomography reconstruction using compression of experimental data,” Opt. Lett. 36, 1377–1379 (2011).
    [CrossRef]
  13. A. Zacharopoulos, M. Schweiger, V. Kolehmainen, and S. Arridge, “3D shape based reconstruction of experimental data in diffuse optical tomography,” Opt. Express 17, 18940–18956 (2009).
    [CrossRef]
  14. F. Yang, F. Gao, P. Ruan, and H. Zhao, “Combined domain-decomposition and matrix-decomposition scheme for large-scale diffuse optical tomography,” Appl. Opt. 49, 3111–3126 (2010).
    [CrossRef]
  15. F. Gao, H. Zhao, L. Zhang, Y. Tanikawa, A. Marjono, and Y. Yamada, “A self-normalized, full time-resolved method for fluorescence diffuse optical tomography,” Opt. Express 16, 13104–13121 (2008).
    [CrossRef]
  16. Y. Zhai and S. A. Cummer, “Fast tomographic reconstruction strategy for diffuse optical tomography,” Opt. Express 17, 5285–5297 (2009).
    [CrossRef]
  17. A. D. Zacharopoulos, P. Svenmarker, J. Axelsson, M. Schweiger, S. R. Arridge, and S. Engels, “A matrix-free algorithm for multiple wavelength fluorescence tomography,” Opt. Express 17, 3025–3035 (2009).
    [CrossRef]
  18. D. Han, X. Yang, K. Liu, C. Qin, B. Zhang, X. Ma, and J. Tian, “Efficient reconstruction method for L1 regularization in fluorescence molecular tomography,” Appl. Opt. 49, 6930–6937 (2010).
    [CrossRef]
  19. Q. Fang and D. A. Boas, “Monte Carlo simulation of photon migration in 3D turbid media accelerated by graphics processing units,” Opt. Express 17, 20178–20190 (2009).
    [CrossRef]
  20. J. Ripoll, “Hybrid Fourier-real space method for diffuse optical tomography,” Opt. Lett. 35, 688–690 (2010).
    [CrossRef]
  21. T. J. Rudge, V. Y. Soloviev, and S. R. Arridge, “Fast image reconstruction in fluorescence optical tomography using data compression,” Opt. Lett. 35, 763–765 (2010).
    [CrossRef]
  22. V. Lukic, V. A. Markel, and J. C. Schotland, “Optical tomography with structured illumination,” Opt. Lett. 34, 983–985 (2009).
    [CrossRef]
  23. N. Ducros, C. D. Andrea, G. Valentini, T. Rudge, S. Arridge, and A. Bassi, “Full-wavelet approach for fluorescence diffuse optical tomography with structured illumination,” Opt. Lett. 35, 3676–3678 (2010).
    [CrossRef]
  24. A. Bassi, C. D. Andrea, G. Valentini, R. Cubeddu, and S. Arridge, “Detection of inhomogeneities in diffusive media using spatially modulated light,” Opt. Lett. 34, 2156–2158 (2009).
    [CrossRef]
  25. J. Dutta, S. Ahn, A. A. Joshi, and R. M. Leahy, “Illumination pattern optimization for fluorescence tomography: theory and simulation studies,” Phys. Med. Biol. 55, 2961–2982 (2010).
    [CrossRef]
  26. N. Ducros, C. D’Andrea, A. Bassi, Gianluca Valentini, and S. Arridge, “A virtual source pattern method for fluorescence tomography with structured light,” Phys. Med. Biol. 57, 3811–3832 (2012).
    [CrossRef]
  27. S. D. Konecky, G. Y. Panasyuk, K. Lee, V. Markel, A. G. Yodh, and J. C. Schotland, “Imaging complex structures with diffuse light,” Opt. Express 16, 5048–5060 (2008).
    [CrossRef]
  28. V. A. Markel and J. C. Schotland, “Symmetries, inversion formulas and image reconstruction for optical tomography,” Phys. Rev. E 70, 056616 (2004).
    [CrossRef]
  29. Z. M. Wang, G. Y. Panasyuk, V. A. Markel, and J. C. Schotland, “Experimental demonstration of an analytic method for image reconstruction in optical diffusion tomography with large data sets,” Opt. Lett. 30, 3338–3340 (2005).
    [CrossRef]
  30. S. R. Arridge, “Optical tomography in medical imaging,” Inverse Probl. 15, R41–R93 (1999).
    [CrossRef]
  31. W. G. Egan and T. W. Hilgeman, Optical Properties of Inhomogeneous Materials (Academic, 1979).
  32. V. A. Markel, V. Mital, and J. C. Schotland, “Inverse problem in optical diffusion tomography. III. Inversion formulas and singular-value decomposition,” J. Opt. Soc. Am. A 20, 890–902 (2003).
    [CrossRef]
  33. J. Ripoll and M. N. Vesperinas, “Spatial resolution of diffuse photon density waves,” J. Opt. Soc. Am. A 16, 1466–1476 (1999).
    [CrossRef]
  34. J. F. Kaiser and W. A. Reed, “Data smoothing using low-pass digital filters,” Rev. Sci. Instrum. 48, 1447–1457 (1977).
    [CrossRef]
  35. Y. C. Lim, “Frequency-response masking approach for the synthesis of sharp linear phase digital filters,” IEEE Trans. Circuits Syst. 33, 357–364 (1986).
    [CrossRef]
  36. J.-W. Sheen, “A compact semi-lumped low-pass filter for harmonics and spurious suppression,” IEEE Microw. Guide. Wave Lett. 10, 92–93 (2000).
    [CrossRef]
  37. L. V. Wang and H.-i Wu, Biomedical Optics: Principles and Imaging (Wiley, 2007).
  38. R. Roy and E. M. Sevick-Muraca, “Three-dimensional unconstrained and constrained image-reconstruction techniques applied to fluorescence, frequency-domain photon migration,” Appl. Opt. 40, 2206–2215 (2001).
    [CrossRef]
  39. L. Zhang, F. Gao, H. He, and H. Zhao, “Three-dimensional scheme for time-domain fluorescence molecular tomography based on Laplace transforms with noise-robust factors,” Opt. Express 16, 7214–7223 (2008).
    [CrossRef]
  40. R. Michels, F. Foschum, and A. Kienle, “Optical properties of fat emulsions,” Opt. Express 16, 5907–5925 (2008).
    [CrossRef]

2012 (5)

C. Bonnéry, M. Desjardins, P. Pouliot, and F. Lesage, “Changes in diffusion path length, with old age in diffuse optical tomography,” J. Biomed. Opt. 17, 056002 (2012).
[CrossRef]

K. L. Perdue, Q. Fang, and S. G. Diamond, “Quantitative assessment of diffuse optical tomography sensitivity to the cerebral cortex using a whole-head probe,” Phys. Med. Biol. 57, 2857–2872 (2012).
[CrossRef]

N. Ducros, C. D’Andrea, A. Bassi, Gianluca Valentini, and S. Arridge, “A virtual source pattern method for fluorescence tomography with structured light,” Phys. Med. Biol. 57, 3811–3832 (2012).
[CrossRef]

O. Lehtikangas, T. Tarvainen, and A. D. Kim, “Modeling boundary measurements of scattered light using the corrected diffusion approximation,” Biomed. Opt. Express 3, 552–571 (2012).
[CrossRef]

T. Shimokawa, T. Kosaka, O. Yamashita, N. Hiroe, T. Amita, Y. Inoue, and M. Sato, “Hierarchical Bayesian estimation improves depth accuracy and spatial resolution of diffuse optical tomography,” Opt. Express 20, 20427–20446(2012).
[CrossRef]

2011 (2)

2010 (8)

J. Ripoll, “Hybrid Fourier-real space method for diffuse optical tomography,” Opt. Lett. 35, 688–690 (2010).
[CrossRef]

T. J. Rudge, V. Y. Soloviev, and S. R. Arridge, “Fast image reconstruction in fluorescence optical tomography using data compression,” Opt. Lett. 35, 763–765 (2010).
[CrossRef]

F. Yang, F. Gao, P. Ruan, and H. Zhao, “Combined domain-decomposition and matrix-decomposition scheme for large-scale diffuse optical tomography,” Appl. Opt. 49, 3111–3126 (2010).
[CrossRef]

C. D’Andrea, N. Ducros, A. Bassi, S. Arridge, and G. Valentini, “Fast 3D optical reconstruction in turbid media using spatially modulated light,” Biomed. Opt. Express 1, 471–481 (2010).
[CrossRef]

N. Ducros, C. D. Andrea, G. Valentini, T. Rudge, S. Arridge, and A. Bassi, “Full-wavelet approach for fluorescence diffuse optical tomography with structured illumination,” Opt. Lett. 35, 3676–3678 (2010).
[CrossRef]

D. Han, X. Yang, K. Liu, C. Qin, B. Zhang, X. Ma, and J. Tian, “Efficient reconstruction method for L1 regularization in fluorescence molecular tomography,” Appl. Opt. 49, 6930–6937 (2010).
[CrossRef]

S. B. M. Abran, X. Intes, C. Casanova, and F. Lesage, “Real-time diffuse optical tomography based on structured illumination,” J. Biomed. Opt. 15, 016006 (2010).
[CrossRef]

J. Dutta, S. Ahn, A. A. Joshi, and R. M. Leahy, “Illumination pattern optimization for fluorescence tomography: theory and simulation studies,” Phys. Med. Biol. 55, 2961–2982 (2010).
[CrossRef]

2009 (7)

2008 (6)

2007 (1)

2005 (1)

2004 (1)

V. A. Markel and J. C. Schotland, “Symmetries, inversion formulas and image reconstruction for optical tomography,” Phys. Rev. E 70, 056616 (2004).
[CrossRef]

2003 (1)

2001 (1)

2000 (1)

J.-W. Sheen, “A compact semi-lumped low-pass filter for harmonics and spurious suppression,” IEEE Microw. Guide. Wave Lett. 10, 92–93 (2000).
[CrossRef]

1999 (2)

1986 (1)

Y. C. Lim, “Frequency-response masking approach for the synthesis of sharp linear phase digital filters,” IEEE Trans. Circuits Syst. 33, 357–364 (1986).
[CrossRef]

1977 (1)

J. F. Kaiser and W. A. Reed, “Data smoothing using low-pass digital filters,” Rev. Sci. Instrum. 48, 1447–1457 (1977).
[CrossRef]

Abran, S. B. M.

S. B. M. Abran, X. Intes, C. Casanova, and F. Lesage, “Real-time diffuse optical tomography based on structured illumination,” J. Biomed. Opt. 15, 016006 (2010).
[CrossRef]

Ahn, S.

J. Dutta, S. Ahn, A. A. Joshi, and R. M. Leahy, “Illumination pattern optimization for fluorescence tomography: theory and simulation studies,” Phys. Med. Biol. 55, 2961–2982 (2010).
[CrossRef]

Amita, T.

Andrea, C. D.

Arridge, S.

Arridge, S. R.

Axelsson, J.

Bassi, A.

Berger, M.

A. Koenig, L. Hervé, V. Josserand, M. Berger, J. Boutet, A. D. Silva, J.-M. Dinten, P. Peltié, J.-L. Coll, and P. Rizo, “In vivo mice lung tumor follow-up with fluorescence diffuse optical tomography,” J. Biomed. Opt. 13, 011008 (2008).
[CrossRef]

Boas, D. A.

Bonnéry, C.

C. Bonnéry, M. Desjardins, P. Pouliot, and F. Lesage, “Changes in diffusion path length, with old age in diffuse optical tomography,” J. Biomed. Opt. 17, 056002 (2012).
[CrossRef]

Boutet, J.

A. Koenig, L. Hervé, V. Josserand, M. Berger, J. Boutet, A. D. Silva, J.-M. Dinten, P. Peltié, J.-L. Coll, and P. Rizo, “In vivo mice lung tumor follow-up with fluorescence diffuse optical tomography,” J. Biomed. Opt. 13, 011008 (2008).
[CrossRef]

Bruggen, N. V.

J. K. Willmann, N. V. Bruggen, L. M. Dinkelborg, and S. S. Gambhir, “Molecular imaging in drug development,” Nat. Med. 7, 591–607 (2008).
[CrossRef]

Casanova, C.

S. B. M. Abran, X. Intes, C. Casanova, and F. Lesage, “Real-time diffuse optical tomography based on structured illumination,” J. Biomed. Opt. 15, 016006 (2010).
[CrossRef]

Choe, R.

Coll, J.-L.

A. Koenig, L. Hervé, V. Josserand, M. Berger, J. Boutet, A. D. Silva, J.-M. Dinten, P. Peltié, J.-L. Coll, and P. Rizo, “In vivo mice lung tumor follow-up with fluorescence diffuse optical tomography,” J. Biomed. Opt. 13, 011008 (2008).
[CrossRef]

Corlu, A.

Cubeddu, R.

Cummer, S. A.

D’Andrea, C.

N. Ducros, C. D’Andrea, A. Bassi, Gianluca Valentini, and S. Arridge, “A virtual source pattern method for fluorescence tomography with structured light,” Phys. Med. Biol. 57, 3811–3832 (2012).
[CrossRef]

C. D’Andrea, N. Ducros, A. Bassi, S. Arridge, and G. Valentini, “Fast 3D optical reconstruction in turbid media using spatially modulated light,” Biomed. Opt. Express 1, 471–481 (2010).
[CrossRef]

Desjardins, M.

C. Bonnéry, M. Desjardins, P. Pouliot, and F. Lesage, “Changes in diffusion path length, with old age in diffuse optical tomography,” J. Biomed. Opt. 17, 056002 (2012).
[CrossRef]

Diamond, S. G.

K. L. Perdue, Q. Fang, and S. G. Diamond, “Quantitative assessment of diffuse optical tomography sensitivity to the cerebral cortex using a whole-head probe,” Phys. Med. Biol. 57, 2857–2872 (2012).
[CrossRef]

Dinkelborg, L. M.

J. K. Willmann, N. V. Bruggen, L. M. Dinkelborg, and S. S. Gambhir, “Molecular imaging in drug development,” Nat. Med. 7, 591–607 (2008).
[CrossRef]

Dinten, J.-M.

A. Koenig, L. Hervé, V. Josserand, M. Berger, J. Boutet, A. D. Silva, J.-M. Dinten, P. Peltié, J.-L. Coll, and P. Rizo, “In vivo mice lung tumor follow-up with fluorescence diffuse optical tomography,” J. Biomed. Opt. 13, 011008 (2008).
[CrossRef]

Ducros, N.

Durduran, T.

Dutta, J.

J. Dutta, S. Ahn, A. A. Joshi, and R. M. Leahy, “Illumination pattern optimization for fluorescence tomography: theory and simulation studies,” Phys. Med. Biol. 55, 2961–2982 (2010).
[CrossRef]

Egan, W. G.

W. G. Egan and T. W. Hilgeman, Optical Properties of Inhomogeneous Materials (Academic, 1979).

Engels, S.

Fang, Q.

K. L. Perdue, Q. Fang, and S. G. Diamond, “Quantitative assessment of diffuse optical tomography sensitivity to the cerebral cortex using a whole-head probe,” Phys. Med. Biol. 57, 2857–2872 (2012).
[CrossRef]

Q. Fang and D. A. Boas, “Monte Carlo simulation of photon migration in 3D turbid media accelerated by graphics processing units,” Opt. Express 17, 20178–20190 (2009).
[CrossRef]

Foschum, F.

Gambhir, S. S.

J. K. Willmann, N. V. Bruggen, L. M. Dinkelborg, and S. S. Gambhir, “Molecular imaging in drug development,” Nat. Med. 7, 591–607 (2008).
[CrossRef]

Gao, F.

Han, D.

He, H.

Hervé, L.

A. Koenig, L. Hervé, V. Josserand, M. Berger, J. Boutet, A. D. Silva, J.-M. Dinten, P. Peltié, J.-L. Coll, and P. Rizo, “In vivo mice lung tumor follow-up with fluorescence diffuse optical tomography,” J. Biomed. Opt. 13, 011008 (2008).
[CrossRef]

Hilgeman, T. W.

W. G. Egan and T. W. Hilgeman, Optical Properties of Inhomogeneous Materials (Academic, 1979).

Hiroe, N.

Inoue, Y.

Intes, X.

S. B. M. Abran, X. Intes, C. Casanova, and F. Lesage, “Real-time diffuse optical tomography based on structured illumination,” J. Biomed. Opt. 15, 016006 (2010).
[CrossRef]

Joshi, A. A.

J. Dutta, S. Ahn, A. A. Joshi, and R. M. Leahy, “Illumination pattern optimization for fluorescence tomography: theory and simulation studies,” Phys. Med. Biol. 55, 2961–2982 (2010).
[CrossRef]

Josserand, V.

A. Koenig, L. Hervé, V. Josserand, M. Berger, J. Boutet, A. D. Silva, J.-M. Dinten, P. Peltié, J.-L. Coll, and P. Rizo, “In vivo mice lung tumor follow-up with fluorescence diffuse optical tomography,” J. Biomed. Opt. 13, 011008 (2008).
[CrossRef]

Kaiser, J. F.

J. F. Kaiser and W. A. Reed, “Data smoothing using low-pass digital filters,” Rev. Sci. Instrum. 48, 1447–1457 (1977).
[CrossRef]

Kienle, A.

Kim, A. D.

Koenig, A.

A. Koenig, L. Hervé, V. Josserand, M. Berger, J. Boutet, A. D. Silva, J.-M. Dinten, P. Peltié, J.-L. Coll, and P. Rizo, “In vivo mice lung tumor follow-up with fluorescence diffuse optical tomography,” J. Biomed. Opt. 13, 011008 (2008).
[CrossRef]

Kolehmainen, V.

Konecky, S. D.

Kosaka, T.

Leahy, R. M.

J. Dutta, S. Ahn, A. A. Joshi, and R. M. Leahy, “Illumination pattern optimization for fluorescence tomography: theory and simulation studies,” Phys. Med. Biol. 55, 2961–2982 (2010).
[CrossRef]

Lee, K.

Lehtikangas, O.

Lesage, F.

C. Bonnéry, M. Desjardins, P. Pouliot, and F. Lesage, “Changes in diffusion path length, with old age in diffuse optical tomography,” J. Biomed. Opt. 17, 056002 (2012).
[CrossRef]

S. B. M. Abran, X. Intes, C. Casanova, and F. Lesage, “Real-time diffuse optical tomography based on structured illumination,” J. Biomed. Opt. 15, 016006 (2010).
[CrossRef]

Lim, Y. C.

Y. C. Lim, “Frequency-response masking approach for the synthesis of sharp linear phase digital filters,” IEEE Trans. Circuits Syst. 33, 357–364 (1986).
[CrossRef]

Liu, K.

Lukic, V.

Ma, X.

Marjono, A.

Markel, V.

Markel, V. A.

Michels, R.

Mital, V.

Panasyuk, G. Y.

Peltié, P.

A. Koenig, L. Hervé, V. Josserand, M. Berger, J. Boutet, A. D. Silva, J.-M. Dinten, P. Peltié, J.-L. Coll, and P. Rizo, “In vivo mice lung tumor follow-up with fluorescence diffuse optical tomography,” J. Biomed. Opt. 13, 011008 (2008).
[CrossRef]

Perdue, K. L.

K. L. Perdue, Q. Fang, and S. G. Diamond, “Quantitative assessment of diffuse optical tomography sensitivity to the cerebral cortex using a whole-head probe,” Phys. Med. Biol. 57, 2857–2872 (2012).
[CrossRef]

Pouliot, P.

C. Bonnéry, M. Desjardins, P. Pouliot, and F. Lesage, “Changes in diffusion path length, with old age in diffuse optical tomography,” J. Biomed. Opt. 17, 056002 (2012).
[CrossRef]

Qin, C.

Reed, W. A.

J. F. Kaiser and W. A. Reed, “Data smoothing using low-pass digital filters,” Rev. Sci. Instrum. 48, 1447–1457 (1977).
[CrossRef]

Ripoll, J.

Rizo, P.

A. Koenig, L. Hervé, V. Josserand, M. Berger, J. Boutet, A. D. Silva, J.-M. Dinten, P. Peltié, J.-L. Coll, and P. Rizo, “In vivo mice lung tumor follow-up with fluorescence diffuse optical tomography,” J. Biomed. Opt. 13, 011008 (2008).
[CrossRef]

Rosen, M. A.

Roy, R.

Ruan, P.

Rudge, T.

Rudge, T. J.

Sato, M.

Schnall, M. D.

Schotland, J. C.

Schweiger, M.

Sevick-Muraca, E. M.

Sheen, J.-W.

J.-W. Sheen, “A compact semi-lumped low-pass filter for harmonics and spurious suppression,” IEEE Microw. Guide. Wave Lett. 10, 92–93 (2000).
[CrossRef]

Shimokawa, T.

Silva, A. D.

A. Koenig, L. Hervé, V. Josserand, M. Berger, J. Boutet, A. D. Silva, J.-M. Dinten, P. Peltié, J.-L. Coll, and P. Rizo, “In vivo mice lung tumor follow-up with fluorescence diffuse optical tomography,” J. Biomed. Opt. 13, 011008 (2008).
[CrossRef]

Soloviev, V. Y.

Svenmarker, P.

Tanikawa, Y.

Tarvainen, T.

Tian, J.

Valentini, G.

Valentini, Gianluca

N. Ducros, C. D’Andrea, A. Bassi, Gianluca Valentini, and S. Arridge, “A virtual source pattern method for fluorescence tomography with structured light,” Phys. Med. Biol. 57, 3811–3832 (2012).
[CrossRef]

Vesperinas, M. N.

Wang, L. V.

L. V. Wang and H.-i Wu, Biomedical Optics: Principles and Imaging (Wiley, 2007).

Wang, Z. M.

Willmann, J. K.

J. K. Willmann, N. V. Bruggen, L. M. Dinkelborg, and S. S. Gambhir, “Molecular imaging in drug development,” Nat. Med. 7, 591–607 (2008).
[CrossRef]

Wu, H.-i

L. V. Wang and H.-i Wu, Biomedical Optics: Principles and Imaging (Wiley, 2007).

Yamada, Y.

Yamashita, O.

Yang, F.

Yang, X.

Yodh, A. G.

Zacharopoulos, A.

Zacharopoulos, A. D.

Zhai, Y.

Zhang, B.

Zhang, L.

Zhao, H.

Appl. Opt. (3)

Biomed. Opt. Express (3)

IEEE Microw. Guide. Wave Lett. (1)

J.-W. Sheen, “A compact semi-lumped low-pass filter for harmonics and spurious suppression,” IEEE Microw. Guide. Wave Lett. 10, 92–93 (2000).
[CrossRef]

IEEE Trans. Circuits Syst. (1)

Y. C. Lim, “Frequency-response masking approach for the synthesis of sharp linear phase digital filters,” IEEE Trans. Circuits Syst. 33, 357–364 (1986).
[CrossRef]

Inverse Probl. (2)

S. R. Arridge, “Optical tomography in medical imaging,” Inverse Probl. 15, R41–R93 (1999).
[CrossRef]

S. R. Arridge and J. C. Schotland, “Optical tomography: forward and inverse problems,” Inverse Probl. 25, 123010 (2009).
[CrossRef]

J. Biomed. Opt. (3)

C. Bonnéry, M. Desjardins, P. Pouliot, and F. Lesage, “Changes in diffusion path length, with old age in diffuse optical tomography,” J. Biomed. Opt. 17, 056002 (2012).
[CrossRef]

A. Koenig, L. Hervé, V. Josserand, M. Berger, J. Boutet, A. D. Silva, J.-M. Dinten, P. Peltié, J.-L. Coll, and P. Rizo, “In vivo mice lung tumor follow-up with fluorescence diffuse optical tomography,” J. Biomed. Opt. 13, 011008 (2008).
[CrossRef]

S. B. M. Abran, X. Intes, C. Casanova, and F. Lesage, “Real-time diffuse optical tomography based on structured illumination,” J. Biomed. Opt. 15, 016006 (2010).
[CrossRef]

J. Opt. Soc. Am. A (2)

Nat. Med. (1)

J. K. Willmann, N. V. Bruggen, L. M. Dinkelborg, and S. S. Gambhir, “Molecular imaging in drug development,” Nat. Med. 7, 591–607 (2008).
[CrossRef]

Opt. Express (10)

Y. Zhai and S. A. Cummer, “Fast tomographic reconstruction strategy for diffuse optical tomography,” Opt. Express 17, 5285–5297 (2009).
[CrossRef]

A. Corlu, R. Choe, T. Durduran, M. A. Rosen, M. Schweiger, S. R. Arridge, M. D. Schnall, and A. G. Yodh, “Three-dimensional in vivo fluorescence diffuse optical tomography of breast cancer in humans,” Opt. Express 15, 6696–6716 (2007).
[CrossRef]

S. D. Konecky, G. Y. Panasyuk, K. Lee, V. Markel, A. G. Yodh, and J. C. Schotland, “Imaging complex structures with diffuse light,” Opt. Express 16, 5048–5060 (2008).
[CrossRef]

R. Michels, F. Foschum, and A. Kienle, “Optical properties of fat emulsions,” Opt. Express 16, 5907–5925 (2008).
[CrossRef]

L. Zhang, F. Gao, H. He, and H. Zhao, “Three-dimensional scheme for time-domain fluorescence molecular tomography based on Laplace transforms with noise-robust factors,” Opt. Express 16, 7214–7223 (2008).
[CrossRef]

F. Gao, H. Zhao, L. Zhang, Y. Tanikawa, A. Marjono, and Y. Yamada, “A self-normalized, full time-resolved method for fluorescence diffuse optical tomography,” Opt. Express 16, 13104–13121 (2008).
[CrossRef]

A. D. Zacharopoulos, P. Svenmarker, J. Axelsson, M. Schweiger, S. R. Arridge, and S. Engels, “A matrix-free algorithm for multiple wavelength fluorescence tomography,” Opt. Express 17, 3025–3035 (2009).
[CrossRef]

A. Zacharopoulos, M. Schweiger, V. Kolehmainen, and S. Arridge, “3D shape based reconstruction of experimental data in diffuse optical tomography,” Opt. Express 17, 18940–18956 (2009).
[CrossRef]

Q. Fang and D. A. Boas, “Monte Carlo simulation of photon migration in 3D turbid media accelerated by graphics processing units,” Opt. Express 17, 20178–20190 (2009).
[CrossRef]

T. Shimokawa, T. Kosaka, O. Yamashita, N. Hiroe, T. Amita, Y. Inoue, and M. Sato, “Hierarchical Bayesian estimation improves depth accuracy and spatial resolution of diffuse optical tomography,” Opt. Express 20, 20427–20446(2012).
[CrossRef]

Opt. Lett. (7)

Phys. Med. Biol. (3)

K. L. Perdue, Q. Fang, and S. G. Diamond, “Quantitative assessment of diffuse optical tomography sensitivity to the cerebral cortex using a whole-head probe,” Phys. Med. Biol. 57, 2857–2872 (2012).
[CrossRef]

J. Dutta, S. Ahn, A. A. Joshi, and R. M. Leahy, “Illumination pattern optimization for fluorescence tomography: theory and simulation studies,” Phys. Med. Biol. 55, 2961–2982 (2010).
[CrossRef]

N. Ducros, C. D’Andrea, A. Bassi, Gianluca Valentini, and S. Arridge, “A virtual source pattern method for fluorescence tomography with structured light,” Phys. Med. Biol. 57, 3811–3832 (2012).
[CrossRef]

Phys. Rev. E (1)

V. A. Markel and J. C. Schotland, “Symmetries, inversion formulas and image reconstruction for optical tomography,” Phys. Rev. E 70, 056616 (2004).
[CrossRef]

Rev. Sci. Instrum. (1)

J. F. Kaiser and W. A. Reed, “Data smoothing using low-pass digital filters,” Rev. Sci. Instrum. 48, 1447–1457 (1977).
[CrossRef]

Other (2)

W. G. Egan and T. W. Hilgeman, Optical Properties of Inhomogeneous Materials (Academic, 1979).

L. V. Wang and H.-i Wu, Biomedical Optics: Principles and Imaging (Wiley, 2007).

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 (13)

Fig. 1.
Fig. 1.

Geometry of the transmission measurement on a slab. δμa(r) represents the perturbation of the absorption coefficient in the target.

Fig. 2.
Fig. 2.

Amplitude distributions of the tissue transfer function of the sample with the heterogeneities at different volume percentages but a fixed absorption contrast of 2.

Fig. 3.
Fig. 3.

Cutoff frequency Fmax at different volume percentages and absorption contrasts of the heterogeneity.

Fig. 4.
Fig. 4.

Flowchart of the proposed SFC method.

Fig. 5.
Fig. 5.

Samples for generating simulated data: (a) sample 1 with one target and (b) sample 2 with two targets.

Fig. 6.
Fig. 6.

Reconstructed μa images of sample 1 with (upper row) and without (lower row) the SFC strategy, with target absorption coefficient of μa=0.02, 0.03, and 0.05mm1. The dashed lines indicate the original target.

Fig. 7.
Fig. 7.

(a) Reconstructed μa images of sample 2 with (upper row) and without (lower row) the SFC strategy, for CCS=20, 16, and 12 mm, respectively. The dashed lines indicate the original target. (b) Corresponding X profiles (profiles along the X axis) of the reconstructed μa images at y=50mm with (left) and without (right) the SFC strategy.

Fig. 8.
Fig. 8.

(a) Reconstructed μa images of sample 2 with (upper row) and without (lower row) the SFC strategy for CCS=20mm when the SNR of the simulated data is 35, 25, and 15 dB, respectively. The dashed lines indicate the original target. (b) Corresponding X profiles of the μa images at y=50mm.

Fig. 9.
Fig. 9.

(a) Reconstructed μa images of sample 2 for CCS=20mm with the conventional method when the SNR of the simulated data is 35, 25, and 15 dB, respectively. The dashed lines indicate the original target. (b) Comparison of the corresponding X profiles of the reconstructed μa images at y=50mm with the proposed SFC method and the conventional one.

Fig. 10.
Fig. 10.

(a) Schematic diagram and (b) photo of the noncontact DOT system.

Fig. 11.
Fig. 11.

Geometry sketch of the phantoms: (a) phantom 1 with one target and (b) phantoms 2, 3, and 4 with two CCS-different targets.

Fig. 12.
Fig. 12.

(a) Reconstructed μa images from the measured data of phantom 1 with the proposed SFC method (upper row) and the conventional method (lower row) with target absorption coefficients of μa=0.02, 0.03, and 0.05mm1, respectively. The dashed lines indicate the original target. (b) Corresponding X profiles of the above μa images at y=45mm.

Fig. 13.
Fig. 13.

(a) Reconstructed μa images from the measured data with the proposed SFC method (upper row) and the conventional method (lower row) of phantoms 2, 3, and 4; i.e. the CCS of the two targets is 20, 16, and 12 mm, respectively. The dashed lines indicate the original target. (b) Corresponding X profiles of the above μa images at y=45mm.

Tables (2)

Tables Icon

Table 1. Reconstruction Performance with and without the SFC Strategy

Tables Icon

Table 2. Computation Time of the Proposed SFC Method at Different Combinations of Neff_f and Nz

Equations (9)

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

ϕ(rs,rd)=G0(rs,rd)ln[T(rs,rd)]=αG0(rs,r)G0(r,rd)δμa(r)dr,
ϕ(fs,zs;fd,zd)=α0Lg(fs;zs,z)g(fd;z,zd)exp[i(fs+fd)·ρ]δμa(r)d3r,
ϕ(fs,zs;fd,zd)=0LA(fs,fd,z)δμ˜a(f,z)dz,
A(fs,fd,z)=4CR2c2(1+32CR)2sinh[U(fs)l]+2D0CRcU(fs)cosh[U(fs)l]([2D0CRcU(fs)]2+1)sinh[U(fs)l]+4D0CRcU(fs)cosh[U(fs)l]·sinh[U(fd)(lz)]+2D0CRcU(fd)cosh[U(fd)(lz)]([2D0CRcU(fd)]2+1)sinh[U(fd)l]+4D0CRcU(fd)cosh[U(fd)l],
Φ(f)=A(f)·X(f)
A(f)=[A[(fs,fd)1,z1]A[(fs,fd)1,z2]A[(fs,fd)1,zNz]A[(fs,fd)2,z1]A[(fs,fd)2,z2]A[(fs,fd)2,zNz]A((fs,fd)M,z1)A[(fs,fd)M,z2]A[(fs,fd)M,zNz]].
X(f)=A(f)T(A(f)A(f)T+βI)1Φ(f),
H(f,l)=exp[ih(f)l],
|f(λ)|=2kλln1020l+(λln1020l)2.

Metrics