Abstract

The current approaches to imaging the tissue blood flow index (BFI) from diffuse correlation tomography (DCT) data are either an analytical solution or a finite element method, both of which are unable to simultaneously account for the tissue heterogeneity and fully utilize the DCT data. In this study, a new imaging concept for DCT, namely NL-DCT, was created by us in which the medical images are combined with light Monte Carlo simulation to provide geometrical and heterogeneous information in tissue. Moreover, the DCT data at multiple delay time are fully utilized via iterative linear regression. The unique merit of NL-DCT in utilizing the medical images as prior information, when combined with a split Bregman algorithm for total variation minimization (Bregman-TV), was validated on a realistic human head model. Computer simulation outcomes demonstrate the accuracy and robustness of NL-DCT in localizing and separating the flow anomalies as well as the capability to preserve edges of anomalies.

© 2018 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

Full Article  |  PDF Article
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References

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  1. F. F. Jöbsis, “Noninvasive, infrared monitoring of cerebral and myocardial oxygen sufficiency and circulatory parameters,” Science 198(4323), 1264–1267 (1977).
    [Crossref] [PubMed]
  2. D. A. Boas, T. Gaudette, G. Strangman, X. Cheng, J. J. A. Marota, and J. B. Mandeville, “The accuracy of near infrared spectroscopy and imaging during focal changes in cerebral hemodynamics,” Neuroimage 13(1), 76–90 (2001).
    [Crossref] [PubMed]
  3. M. Vardi and A. Nini, “Near-infrared spectroscopy for evaluation of peripheral vascular disease. A systematic review of literature,” Eur. J. Vasc. Endovasc. Surg. 35(1), 68–74 (2008).
    [Crossref] [PubMed]
  4. 4J. M. Murkin and M. Arango, “Near-infrared spectroscopy as an index of brain and tissue oxygenation,” British Journal of Anaesthesia 103, i3–i13 (2009).
  5. M. Ferrari, M. Muthalib, and V. Quaresima, “The use of near-infrared spectroscopy in understanding skeletal muscle physiology: recent developments,” Philos Trans A Math Phys Eng Sci 369(1955), 4577–4590 (2011).
    [Crossref] [PubMed]
  6. J. C. Hebden, A. Gibson, T. Austin, R. M. Yusof, N. Everdell, D. T. Delpy, S. R. Arridge, J. H. Meek, and J. S. Wyatt, “Imaging changes in blood volume and oxygenation in the newborn infant brain using three-dimensional optical tomography,” Phys. Med. Biol. 49(7), 1117–1130 (2004).
    [Crossref] [PubMed]
  7. H. Dehghani, M. E. Eames, P. K. Yalavarthy, S. C. Davis, S. Srinivasan, C. M. Carpenter, B. W. Pogue, and K. D. Paulsen, “Near infrared optical tomography using NIRFAST: Algorithm for numerical model and image reconstruction,” Commun. Numer. Methods Eng. 25(6), 711–732 (2009).
    [Crossref] [PubMed]
  8. A. T. Eggebrecht, S. L. Ferradal, A. Robichaux-Viehoever, M. S. Hassanpour, H. Dehghani, A. Z. Snyder, T. Hershey, and J. P. Culver, “Mapping distributed brain function and networks with diffuse optical tomography,” Nat. Photonics 8(6), 448–454 (2014).
    [Crossref] [PubMed]
  9. 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]
  10. D. 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).
    [Crossref] [PubMed]
  11. S. R. Arridge and J. C. Hebden, “Optical imaging in medicine: II. Modelling and reconstruction,” Phys. Med. Biol. 42(5), 841–853 (1997).
    [Crossref] [PubMed]
  12. T. Durduran, R. Choe, W. B. Baker, and A. G. Yodh, “Diffuse optics for tissue monitoring and tomography,” Rep. Prog. Phys. 73(7), 076701 (2010).
    [Crossref] [PubMed]
  13. G. Yu, “Near-infrared diffuse correlation spectroscopy in cancer diagnosis and therapy monitoring,” J. Biomed. Opt. 17(1), 010901 (2012).
    [Crossref] [PubMed]
  14. Y. Shang, K. Gurley, B. Symons, D. Long, R. Srikuea, L. J. Crofford, C. A. Peterson, and G. Yu, “Noninvasive optical characterization of muscle blood flow, oxygenation, and metabolism in women with fibromyalgia,” Arthritis Res. Ther. 14(6), R236 (2012).
    [Crossref] [PubMed]
  15. N. Roche-Labarbe, S. A. Carp, A. Surova, M. Patel, D. A. Boas, P. E. Grant, and M. A. Franceschini, “Noninvasive optical measures of CBV, StO(2), CBF index, and rCMRO(2) in human premature neonates’ brains in the first six weeks of life,” Hum. Brain Mapp. 31(3), 341–352 (2010).
    [Crossref] [PubMed]
  16. C. Cheung, J. P. Culver, K. Takahashi, J. H. Greenberg, and A. G. Yodh, “In vivo cerebrovascular measurement combining diffuse near-infrared absorption and correlation spectroscopies,” Phys. Med. Biol. 46(8), 2053–2065 (2001).
    [Crossref] [PubMed]
  17. D. A. Boas, L. E. Campbell, and A. G. Yodh, “Scattering and imaging with diffusing temporal field correlations,” Phys. Rev. Lett. 75(9), 1855–1858 (1995).
    [Crossref] [PubMed]
  18. G. Maret and P. E. Wolf, “Multiple Light-Scattering from Disordered Media - the Effect of Brownian-Motion of Scatterers,” Z. Phys. B Condens. Matter 65(4), 409–413 (1987).
    [Crossref]
  19. D. J. Pine, D. A. Weitz, P. M. Chaikin, and E. Herbolzheimer, “Diffusing Wave Spectroscopy,” Phys. Rev. Lett. 60(12), 1134–1137 (1988).
    [Crossref] [PubMed]
  20. J. P. Culver, T. Durduran, D. Furuya, C. Cheung, J. H. Greenberg, and A. G. Yodh, “Diffuse optical tomography of cerebral blood flow, oxygenation, and metabolism in rat during focal ischemia,” J. Cereb. Blood Flow Metab. 23(8), 911–924 (2003).
    [Crossref] [PubMed]
  21. C. Zhou, G. Yu, D. Furuya, J. Greenberg, A. Yodh, and T. Durduran, “Diffuse optical correlation tomography of cerebral blood flow during cortical spreading depression in rat brain,” Opt. Express 14(3), 1125–1144 (2006).
    [Crossref] [PubMed]
  22. Y. Lin, C. Huang, D. Irwin, L. He, Y. Shang, and G. Yu, “Three-dimensional flow contrast imaging of deep tissue using noncontact diffuse correlation tomography,” Appl. Phys. Lett. 104(12), 121103 (2014).
    [Crossref] [PubMed]
  23. L. He, Y. Lin, C. Huang, D. Irwin, M. M. Szabunio, and G. Yu, “Noncontact diffuse correlation tomography of human breast tumor,” J. Biomed. Opt. 20(8), 086003 (2015).
    [Crossref] [PubMed]
  24. Y. Shang, T. Li, L. Chen, Y. Lin, M. Toborek, and G. Yu, “Extraction of diffuse correlation spectroscopy flow index by integration of Nth-order linear model with Monte Carlo simulation,” Appl. Phys. Lett. 104(19), 193703 (2014).
    [Crossref] [PubMed]
  25. Y. Shang and G. Yu, “A Nth-order linear algorithm for extracting diffuse correlation spectroscopy blood flow indices in heterogeneous tissues,” Appl. Phys. Lett. 105(13), 133702 (2014).
    [Crossref] [PubMed]
  26. E. Y. Sidky and X. Pan, “Image reconstruction in circular cone-beam computed tomography by constrained, total-variation minimization,” Phys. Med. Biol. 53(17), 4777–4807 (2008).
    [Crossref] [PubMed]
  27. A. Douiri, M. Schweiger, J. Riley, and S. R. Arridge, “Anisotropic diffusion regularization methods for diffuse optical tomography using edge prior information,” Meas. Sci. Technol. 18(1), 87–95 (2007).
    [Crossref]
  28. M. Dehghan and R. Mohammadi-Arani, “Generalized product-type methods based on bi-conjugate gradient (GPBiCG) for solving shifted linear systems,” Comput. Appl. Math. 36(4), 1591–1606 (2017).
    [Crossref]
  29. T. Li, H. Gong, and Q. M. Luo, “Mcvm: Monte Carlo Modeling of Photon Migration in Voxelized Media,” J. Innov. Opt. Heal, Sci. 3, 91–102 (2010).
  30. J. Guo, Z. Gui, H. Hou, and Y. Shang, “Flexible positioning of source-detector arrays in 3D visualization platform for Monte Carlo simulation of light propagation,” IEEE Access 5(12), 26673–26680 (2017).
    [Crossref]
  31. D. E. Koppel, “Statistical Accuracy in Fluorescence Correlation Spectroscopy,” Phys. Rev. A 10(6), 1938–1945 (1974).
    [Crossref]

2017 (2)

M. Dehghan and R. Mohammadi-Arani, “Generalized product-type methods based on bi-conjugate gradient (GPBiCG) for solving shifted linear systems,” Comput. Appl. Math. 36(4), 1591–1606 (2017).
[Crossref]

J. Guo, Z. Gui, H. Hou, and Y. Shang, “Flexible positioning of source-detector arrays in 3D visualization platform for Monte Carlo simulation of light propagation,” IEEE Access 5(12), 26673–26680 (2017).
[Crossref]

2015 (1)

L. He, Y. Lin, C. Huang, D. Irwin, M. M. Szabunio, and G. Yu, “Noncontact diffuse correlation tomography of human breast tumor,” J. Biomed. Opt. 20(8), 086003 (2015).
[Crossref] [PubMed]

2014 (4)

Y. Shang, T. Li, L. Chen, Y. Lin, M. Toborek, and G. Yu, “Extraction of diffuse correlation spectroscopy flow index by integration of Nth-order linear model with Monte Carlo simulation,” Appl. Phys. Lett. 104(19), 193703 (2014).
[Crossref] [PubMed]

Y. Shang and G. Yu, “A Nth-order linear algorithm for extracting diffuse correlation spectroscopy blood flow indices in heterogeneous tissues,” Appl. Phys. Lett. 105(13), 133702 (2014).
[Crossref] [PubMed]

Y. Lin, C. Huang, D. Irwin, L. He, Y. Shang, and G. Yu, “Three-dimensional flow contrast imaging of deep tissue using noncontact diffuse correlation tomography,” Appl. Phys. Lett. 104(12), 121103 (2014).
[Crossref] [PubMed]

A. T. Eggebrecht, S. L. Ferradal, A. Robichaux-Viehoever, M. S. Hassanpour, H. Dehghani, A. Z. Snyder, T. Hershey, and J. P. Culver, “Mapping distributed brain function and networks with diffuse optical tomography,” Nat. Photonics 8(6), 448–454 (2014).
[Crossref] [PubMed]

2012 (2)

G. Yu, “Near-infrared diffuse correlation spectroscopy in cancer diagnosis and therapy monitoring,” J. Biomed. Opt. 17(1), 010901 (2012).
[Crossref] [PubMed]

Y. Shang, K. Gurley, B. Symons, D. Long, R. Srikuea, L. J. Crofford, C. A. Peterson, and G. Yu, “Noninvasive optical characterization of muscle blood flow, oxygenation, and metabolism in women with fibromyalgia,” Arthritis Res. Ther. 14(6), R236 (2012).
[Crossref] [PubMed]

2011 (1)

M. Ferrari, M. Muthalib, and V. Quaresima, “The use of near-infrared spectroscopy in understanding skeletal muscle physiology: recent developments,” Philos Trans A Math Phys Eng Sci 369(1955), 4577–4590 (2011).
[Crossref] [PubMed]

2010 (3)

N. Roche-Labarbe, S. A. Carp, A. Surova, M. Patel, D. A. Boas, P. E. Grant, and M. A. Franceschini, “Noninvasive optical measures of CBV, StO(2), CBF index, and rCMRO(2) in human premature neonates’ brains in the first six weeks of life,” Hum. Brain Mapp. 31(3), 341–352 (2010).
[Crossref] [PubMed]

T. Durduran, R. Choe, W. B. Baker, and A. G. Yodh, “Diffuse optics for tissue monitoring and tomography,” Rep. Prog. Phys. 73(7), 076701 (2010).
[Crossref] [PubMed]

T. Li, H. Gong, and Q. M. Luo, “Mcvm: Monte Carlo Modeling of Photon Migration in Voxelized Media,” J. Innov. Opt. Heal, Sci. 3, 91–102 (2010).

2009 (2)

H. Dehghani, M. E. Eames, P. K. Yalavarthy, S. C. Davis, S. Srinivasan, C. M. Carpenter, B. W. Pogue, and K. D. Paulsen, “Near infrared optical tomography using NIRFAST: Algorithm for numerical model and image reconstruction,” Commun. Numer. Methods Eng. 25(6), 711–732 (2009).
[Crossref] [PubMed]

4J. M. Murkin and M. Arango, “Near-infrared spectroscopy as an index of brain and tissue oxygenation,” British Journal of Anaesthesia 103, i3–i13 (2009).

2008 (2)

M. Vardi and A. Nini, “Near-infrared spectroscopy for evaluation of peripheral vascular disease. A systematic review of literature,” Eur. J. Vasc. Endovasc. Surg. 35(1), 68–74 (2008).
[Crossref] [PubMed]

E. Y. Sidky and X. Pan, “Image reconstruction in circular cone-beam computed tomography by constrained, total-variation minimization,” Phys. Med. Biol. 53(17), 4777–4807 (2008).
[Crossref] [PubMed]

2007 (1)

A. Douiri, M. Schweiger, J. Riley, and S. R. Arridge, “Anisotropic diffusion regularization methods for diffuse optical tomography using edge prior information,” Meas. Sci. Technol. 18(1), 87–95 (2007).
[Crossref]

2006 (1)

2004 (1)

J. C. Hebden, A. Gibson, T. Austin, R. M. Yusof, N. Everdell, D. T. Delpy, S. R. Arridge, J. H. Meek, and J. S. Wyatt, “Imaging changes in blood volume and oxygenation in the newborn infant brain using three-dimensional optical tomography,” Phys. Med. Biol. 49(7), 1117–1130 (2004).
[Crossref] [PubMed]

2003 (1)

J. P. Culver, T. Durduran, D. Furuya, C. Cheung, J. H. Greenberg, and A. G. Yodh, “Diffuse optical tomography of cerebral blood flow, oxygenation, and metabolism in rat during focal ischemia,” J. Cereb. Blood Flow Metab. 23(8), 911–924 (2003).
[Crossref] [PubMed]

2002 (1)

2001 (2)

C. Cheung, J. P. Culver, K. Takahashi, J. H. Greenberg, and A. G. Yodh, “In vivo cerebrovascular measurement combining diffuse near-infrared absorption and correlation spectroscopies,” Phys. Med. Biol. 46(8), 2053–2065 (2001).
[Crossref] [PubMed]

D. A. Boas, T. Gaudette, G. Strangman, X. Cheng, J. J. A. Marota, and J. B. Mandeville, “The accuracy of near infrared spectroscopy and imaging during focal changes in cerebral hemodynamics,” Neuroimage 13(1), 76–90 (2001).
[Crossref] [PubMed]

1997 (1)

S. R. Arridge and J. C. Hebden, “Optical imaging in medicine: II. Modelling and reconstruction,” Phys. Med. Biol. 42(5), 841–853 (1997).
[Crossref] [PubMed]

1995 (2)

D. A. Boas, L. E. Campbell, and A. G. Yodh, “Scattering and imaging with diffusing temporal field correlations,” Phys. Rev. Lett. 75(9), 1855–1858 (1995).
[Crossref] [PubMed]

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]

1988 (1)

D. J. Pine, D. A. Weitz, P. M. Chaikin, and E. Herbolzheimer, “Diffusing Wave Spectroscopy,” Phys. Rev. Lett. 60(12), 1134–1137 (1988).
[Crossref] [PubMed]

1987 (1)

G. Maret and P. E. Wolf, “Multiple Light-Scattering from Disordered Media - the Effect of Brownian-Motion of Scatterers,” Z. Phys. B Condens. Matter 65(4), 409–413 (1987).
[Crossref]

1977 (1)

F. F. Jöbsis, “Noninvasive, infrared monitoring of cerebral and myocardial oxygen sufficiency and circulatory parameters,” Science 198(4323), 1264–1267 (1977).
[Crossref] [PubMed]

1974 (1)

D. E. Koppel, “Statistical Accuracy in Fluorescence Correlation Spectroscopy,” Phys. Rev. A 10(6), 1938–1945 (1974).
[Crossref]

Arango, M.

4J. M. Murkin and M. Arango, “Near-infrared spectroscopy as an index of brain and tissue oxygenation,” British Journal of Anaesthesia 103, i3–i13 (2009).

Arridge, S. R.

A. Douiri, M. Schweiger, J. Riley, and S. R. Arridge, “Anisotropic diffusion regularization methods for diffuse optical tomography using edge prior information,” Meas. Sci. Technol. 18(1), 87–95 (2007).
[Crossref]

J. C. Hebden, A. Gibson, T. Austin, R. M. Yusof, N. Everdell, D. T. Delpy, S. R. Arridge, J. H. Meek, and J. S. Wyatt, “Imaging changes in blood volume and oxygenation in the newborn infant brain using three-dimensional optical tomography,” Phys. Med. Biol. 49(7), 1117–1130 (2004).
[Crossref] [PubMed]

S. R. Arridge and J. C. Hebden, “Optical imaging in medicine: II. Modelling and reconstruction,” Phys. Med. Biol. 42(5), 841–853 (1997).
[Crossref] [PubMed]

Austin, T.

J. C. Hebden, A. Gibson, T. Austin, R. M. Yusof, N. Everdell, D. T. Delpy, S. R. Arridge, J. H. Meek, and J. S. Wyatt, “Imaging changes in blood volume and oxygenation in the newborn infant brain using three-dimensional optical tomography,” Phys. Med. Biol. 49(7), 1117–1130 (2004).
[Crossref] [PubMed]

Baker, W. B.

T. Durduran, R. Choe, W. B. Baker, and A. G. Yodh, “Diffuse optics for tissue monitoring and tomography,” Rep. Prog. Phys. 73(7), 076701 (2010).
[Crossref] [PubMed]

Boas, D.

Boas, D. A.

N. Roche-Labarbe, S. A. Carp, A. Surova, M. Patel, D. A. Boas, P. E. Grant, and M. A. Franceschini, “Noninvasive optical measures of CBV, StO(2), CBF index, and rCMRO(2) in human premature neonates’ brains in the first six weeks of life,” Hum. Brain Mapp. 31(3), 341–352 (2010).
[Crossref] [PubMed]

D. A. Boas, T. Gaudette, G. Strangman, X. Cheng, J. J. A. Marota, and J. B. Mandeville, “The accuracy of near infrared spectroscopy and imaging during focal changes in cerebral hemodynamics,” Neuroimage 13(1), 76–90 (2001).
[Crossref] [PubMed]

D. A. Boas, L. E. Campbell, and A. G. Yodh, “Scattering and imaging with diffusing temporal field correlations,” Phys. Rev. Lett. 75(9), 1855–1858 (1995).
[Crossref] [PubMed]

Campbell, L. E.

D. A. Boas, L. E. Campbell, and A. G. Yodh, “Scattering and imaging with diffusing temporal field correlations,” Phys. Rev. Lett. 75(9), 1855–1858 (1995).
[Crossref] [PubMed]

Carp, S. A.

N. Roche-Labarbe, S. A. Carp, A. Surova, M. Patel, D. A. Boas, P. E. Grant, and M. A. Franceschini, “Noninvasive optical measures of CBV, StO(2), CBF index, and rCMRO(2) in human premature neonates’ brains in the first six weeks of life,” Hum. Brain Mapp. 31(3), 341–352 (2010).
[Crossref] [PubMed]

Carpenter, C. M.

H. Dehghani, M. E. Eames, P. K. Yalavarthy, S. C. Davis, S. Srinivasan, C. M. Carpenter, B. W. Pogue, and K. D. Paulsen, “Near infrared optical tomography using NIRFAST: Algorithm for numerical model and image reconstruction,” Commun. Numer. Methods Eng. 25(6), 711–732 (2009).
[Crossref] [PubMed]

Chaikin, P. M.

D. J. Pine, D. A. Weitz, P. M. Chaikin, and E. Herbolzheimer, “Diffusing Wave Spectroscopy,” Phys. Rev. Lett. 60(12), 1134–1137 (1988).
[Crossref] [PubMed]

Chen, L.

Y. Shang, T. Li, L. Chen, Y. Lin, M. Toborek, and G. Yu, “Extraction of diffuse correlation spectroscopy flow index by integration of Nth-order linear model with Monte Carlo simulation,” Appl. Phys. Lett. 104(19), 193703 (2014).
[Crossref] [PubMed]

Cheng, X.

D. A. Boas, T. Gaudette, G. Strangman, X. Cheng, J. J. A. Marota, and J. B. Mandeville, “The accuracy of near infrared spectroscopy and imaging during focal changes in cerebral hemodynamics,” Neuroimage 13(1), 76–90 (2001).
[Crossref] [PubMed]

Cheung, C.

J. P. Culver, T. Durduran, D. Furuya, C. Cheung, J. H. Greenberg, and A. G. Yodh, “Diffuse optical tomography of cerebral blood flow, oxygenation, and metabolism in rat during focal ischemia,” J. Cereb. Blood Flow Metab. 23(8), 911–924 (2003).
[Crossref] [PubMed]

C. Cheung, J. P. Culver, K. Takahashi, J. H. Greenberg, and A. G. Yodh, “In vivo cerebrovascular measurement combining diffuse near-infrared absorption and correlation spectroscopies,” Phys. Med. Biol. 46(8), 2053–2065 (2001).
[Crossref] [PubMed]

Choe, R.

T. Durduran, R. Choe, W. B. Baker, and A. G. Yodh, “Diffuse optics for tissue monitoring and tomography,” Rep. Prog. Phys. 73(7), 076701 (2010).
[Crossref] [PubMed]

Crofford, L. J.

Y. Shang, K. Gurley, B. Symons, D. Long, R. Srikuea, L. J. Crofford, C. A. Peterson, and G. Yu, “Noninvasive optical characterization of muscle blood flow, oxygenation, and metabolism in women with fibromyalgia,” Arthritis Res. Ther. 14(6), R236 (2012).
[Crossref] [PubMed]

Culver, J.

Culver, J. P.

A. T. Eggebrecht, S. L. Ferradal, A. Robichaux-Viehoever, M. S. Hassanpour, H. Dehghani, A. Z. Snyder, T. Hershey, and J. P. Culver, “Mapping distributed brain function and networks with diffuse optical tomography,” Nat. Photonics 8(6), 448–454 (2014).
[Crossref] [PubMed]

J. P. Culver, T. Durduran, D. Furuya, C. Cheung, J. H. Greenberg, and A. G. Yodh, “Diffuse optical tomography of cerebral blood flow, oxygenation, and metabolism in rat during focal ischemia,” J. Cereb. Blood Flow Metab. 23(8), 911–924 (2003).
[Crossref] [PubMed]

C. Cheung, J. P. Culver, K. Takahashi, J. H. Greenberg, and A. G. Yodh, “In vivo cerebrovascular measurement combining diffuse near-infrared absorption and correlation spectroscopies,” Phys. Med. Biol. 46(8), 2053–2065 (2001).
[Crossref] [PubMed]

Davis, S. C.

H. Dehghani, M. E. Eames, P. K. Yalavarthy, S. C. Davis, S. Srinivasan, C. M. Carpenter, B. W. Pogue, and K. D. Paulsen, “Near infrared optical tomography using NIRFAST: Algorithm for numerical model and image reconstruction,” Commun. Numer. Methods Eng. 25(6), 711–732 (2009).
[Crossref] [PubMed]

Dehghan, M.

M. Dehghan and R. Mohammadi-Arani, “Generalized product-type methods based on bi-conjugate gradient (GPBiCG) for solving shifted linear systems,” Comput. Appl. Math. 36(4), 1591–1606 (2017).
[Crossref]

Dehghani, H.

A. T. Eggebrecht, S. L. Ferradal, A. Robichaux-Viehoever, M. S. Hassanpour, H. Dehghani, A. Z. Snyder, T. Hershey, and J. P. Culver, “Mapping distributed brain function and networks with diffuse optical tomography,” Nat. Photonics 8(6), 448–454 (2014).
[Crossref] [PubMed]

H. Dehghani, M. E. Eames, P. K. Yalavarthy, S. C. Davis, S. Srinivasan, C. M. Carpenter, B. W. Pogue, and K. D. Paulsen, “Near infrared optical tomography using NIRFAST: Algorithm for numerical model and image reconstruction,” Commun. Numer. Methods Eng. 25(6), 711–732 (2009).
[Crossref] [PubMed]

Delpy, D. T.

J. C. Hebden, A. Gibson, T. Austin, R. M. Yusof, N. Everdell, D. T. Delpy, S. R. Arridge, J. H. Meek, and J. S. Wyatt, “Imaging changes in blood volume and oxygenation in the newborn infant brain using three-dimensional optical tomography,” Phys. Med. Biol. 49(7), 1117–1130 (2004).
[Crossref] [PubMed]

Douiri, A.

A. Douiri, M. Schweiger, J. Riley, and S. R. Arridge, “Anisotropic diffusion regularization methods for diffuse optical tomography using edge prior information,” Meas. Sci. Technol. 18(1), 87–95 (2007).
[Crossref]

Dunn, A.

Durduran, T.

T. Durduran, R. Choe, W. B. Baker, and A. G. Yodh, “Diffuse optics for tissue monitoring and tomography,” Rep. Prog. Phys. 73(7), 076701 (2010).
[Crossref] [PubMed]

C. Zhou, G. Yu, D. Furuya, J. Greenberg, A. Yodh, and T. Durduran, “Diffuse optical correlation tomography of cerebral blood flow during cortical spreading depression in rat brain,” Opt. Express 14(3), 1125–1144 (2006).
[Crossref] [PubMed]

J. P. Culver, T. Durduran, D. Furuya, C. Cheung, J. H. Greenberg, and A. G. Yodh, “Diffuse optical tomography of cerebral blood flow, oxygenation, and metabolism in rat during focal ischemia,” J. Cereb. Blood Flow Metab. 23(8), 911–924 (2003).
[Crossref] [PubMed]

Eames, M. E.

H. Dehghani, M. E. Eames, P. K. Yalavarthy, S. C. Davis, S. Srinivasan, C. M. Carpenter, B. W. Pogue, and K. D. Paulsen, “Near infrared optical tomography using NIRFAST: Algorithm for numerical model and image reconstruction,” Commun. Numer. Methods Eng. 25(6), 711–732 (2009).
[Crossref] [PubMed]

Eggebrecht, A. T.

A. T. Eggebrecht, S. L. Ferradal, A. Robichaux-Viehoever, M. S. Hassanpour, H. Dehghani, A. Z. Snyder, T. Hershey, and J. P. Culver, “Mapping distributed brain function and networks with diffuse optical tomography,” Nat. Photonics 8(6), 448–454 (2014).
[Crossref] [PubMed]

Everdell, N.

J. C. Hebden, A. Gibson, T. Austin, R. M. Yusof, N. Everdell, D. T. Delpy, S. R. Arridge, J. H. Meek, and J. S. Wyatt, “Imaging changes in blood volume and oxygenation in the newborn infant brain using three-dimensional optical tomography,” Phys. Med. Biol. 49(7), 1117–1130 (2004).
[Crossref] [PubMed]

Ferradal, S. L.

A. T. Eggebrecht, S. L. Ferradal, A. Robichaux-Viehoever, M. S. Hassanpour, H. Dehghani, A. Z. Snyder, T. Hershey, and J. P. Culver, “Mapping distributed brain function and networks with diffuse optical tomography,” Nat. Photonics 8(6), 448–454 (2014).
[Crossref] [PubMed]

Ferrari, M.

M. Ferrari, M. Muthalib, and V. Quaresima, “The use of near-infrared spectroscopy in understanding skeletal muscle physiology: recent developments,” Philos Trans A Math Phys Eng Sci 369(1955), 4577–4590 (2011).
[Crossref] [PubMed]

Franceschini, M. A.

N. Roche-Labarbe, S. A. Carp, A. Surova, M. Patel, D. A. Boas, P. E. Grant, and M. A. Franceschini, “Noninvasive optical measures of CBV, StO(2), CBF index, and rCMRO(2) in human premature neonates’ brains in the first six weeks of life,” Hum. Brain Mapp. 31(3), 341–352 (2010).
[Crossref] [PubMed]

Furuya, D.

C. Zhou, G. Yu, D. Furuya, J. Greenberg, A. Yodh, and T. Durduran, “Diffuse optical correlation tomography of cerebral blood flow during cortical spreading depression in rat brain,” Opt. Express 14(3), 1125–1144 (2006).
[Crossref] [PubMed]

J. P. Culver, T. Durduran, D. Furuya, C. Cheung, J. H. Greenberg, and A. G. Yodh, “Diffuse optical tomography of cerebral blood flow, oxygenation, and metabolism in rat during focal ischemia,” J. Cereb. Blood Flow Metab. 23(8), 911–924 (2003).
[Crossref] [PubMed]

Gaudette, T.

D. A. Boas, T. Gaudette, G. Strangman, X. Cheng, J. J. A. Marota, and J. B. Mandeville, “The accuracy of near infrared spectroscopy and imaging during focal changes in cerebral hemodynamics,” Neuroimage 13(1), 76–90 (2001).
[Crossref] [PubMed]

Gibson, A.

J. C. Hebden, A. Gibson, T. Austin, R. M. Yusof, N. Everdell, D. T. Delpy, S. R. Arridge, J. H. Meek, and J. S. Wyatt, “Imaging changes in blood volume and oxygenation in the newborn infant brain using three-dimensional optical tomography,” Phys. Med. Biol. 49(7), 1117–1130 (2004).
[Crossref] [PubMed]

Gong, H.

T. Li, H. Gong, and Q. M. Luo, “Mcvm: Monte Carlo Modeling of Photon Migration in Voxelized Media,” J. Innov. Opt. Heal, Sci. 3, 91–102 (2010).

Grant, P. E.

N. Roche-Labarbe, S. A. Carp, A. Surova, M. Patel, D. A. Boas, P. E. Grant, and M. A. Franceschini, “Noninvasive optical measures of CBV, StO(2), CBF index, and rCMRO(2) in human premature neonates’ brains in the first six weeks of life,” Hum. Brain Mapp. 31(3), 341–352 (2010).
[Crossref] [PubMed]

Greenberg, J.

Greenberg, J. H.

J. P. Culver, T. Durduran, D. Furuya, C. Cheung, J. H. Greenberg, and A. G. Yodh, “Diffuse optical tomography of cerebral blood flow, oxygenation, and metabolism in rat during focal ischemia,” J. Cereb. Blood Flow Metab. 23(8), 911–924 (2003).
[Crossref] [PubMed]

C. Cheung, J. P. Culver, K. Takahashi, J. H. Greenberg, and A. G. Yodh, “In vivo cerebrovascular measurement combining diffuse near-infrared absorption and correlation spectroscopies,” Phys. Med. Biol. 46(8), 2053–2065 (2001).
[Crossref] [PubMed]

Gui, Z.

J. Guo, Z. Gui, H. Hou, and Y. Shang, “Flexible positioning of source-detector arrays in 3D visualization platform for Monte Carlo simulation of light propagation,” IEEE Access 5(12), 26673–26680 (2017).
[Crossref]

Guo, J.

J. Guo, Z. Gui, H. Hou, and Y. Shang, “Flexible positioning of source-detector arrays in 3D visualization platform for Monte Carlo simulation of light propagation,” IEEE Access 5(12), 26673–26680 (2017).
[Crossref]

Gurley, K.

Y. Shang, K. Gurley, B. Symons, D. Long, R. Srikuea, L. J. Crofford, C. A. Peterson, and G. Yu, “Noninvasive optical characterization of muscle blood flow, oxygenation, and metabolism in women with fibromyalgia,” Arthritis Res. Ther. 14(6), R236 (2012).
[Crossref] [PubMed]

Hassanpour, M. S.

A. T. Eggebrecht, S. L. Ferradal, A. Robichaux-Viehoever, M. S. Hassanpour, H. Dehghani, A. Z. Snyder, T. Hershey, and J. P. Culver, “Mapping distributed brain function and networks with diffuse optical tomography,” Nat. Photonics 8(6), 448–454 (2014).
[Crossref] [PubMed]

He, L.

L. He, Y. Lin, C. Huang, D. Irwin, M. M. Szabunio, and G. Yu, “Noncontact diffuse correlation tomography of human breast tumor,” J. Biomed. Opt. 20(8), 086003 (2015).
[Crossref] [PubMed]

Y. Lin, C. Huang, D. Irwin, L. He, Y. Shang, and G. Yu, “Three-dimensional flow contrast imaging of deep tissue using noncontact diffuse correlation tomography,” Appl. Phys. Lett. 104(12), 121103 (2014).
[Crossref] [PubMed]

Hebden, J. C.

J. C. Hebden, A. Gibson, T. Austin, R. M. Yusof, N. Everdell, D. T. Delpy, S. R. Arridge, J. H. Meek, and J. S. Wyatt, “Imaging changes in blood volume and oxygenation in the newborn infant brain using three-dimensional optical tomography,” Phys. Med. Biol. 49(7), 1117–1130 (2004).
[Crossref] [PubMed]

S. R. Arridge and J. C. Hebden, “Optical imaging in medicine: II. Modelling and reconstruction,” Phys. Med. Biol. 42(5), 841–853 (1997).
[Crossref] [PubMed]

Herbolzheimer, E.

D. J. Pine, D. A. Weitz, P. M. Chaikin, and E. Herbolzheimer, “Diffusing Wave Spectroscopy,” Phys. Rev. Lett. 60(12), 1134–1137 (1988).
[Crossref] [PubMed]

Hershey, T.

A. T. Eggebrecht, S. L. Ferradal, A. Robichaux-Viehoever, M. S. Hassanpour, H. Dehghani, A. Z. Snyder, T. Hershey, and J. P. Culver, “Mapping distributed brain function and networks with diffuse optical tomography,” Nat. Photonics 8(6), 448–454 (2014).
[Crossref] [PubMed]

Hou, H.

J. Guo, Z. Gui, H. Hou, and Y. Shang, “Flexible positioning of source-detector arrays in 3D visualization platform for Monte Carlo simulation of light propagation,” IEEE Access 5(12), 26673–26680 (2017).
[Crossref]

Huang, C.

L. He, Y. Lin, C. Huang, D. Irwin, M. M. Szabunio, and G. Yu, “Noncontact diffuse correlation tomography of human breast tumor,” J. Biomed. Opt. 20(8), 086003 (2015).
[Crossref] [PubMed]

Y. Lin, C. Huang, D. Irwin, L. He, Y. Shang, and G. Yu, “Three-dimensional flow contrast imaging of deep tissue using noncontact diffuse correlation tomography,” Appl. Phys. Lett. 104(12), 121103 (2014).
[Crossref] [PubMed]

Irwin, D.

L. He, Y. Lin, C. Huang, D. Irwin, M. M. Szabunio, and G. Yu, “Noncontact diffuse correlation tomography of human breast tumor,” J. Biomed. Opt. 20(8), 086003 (2015).
[Crossref] [PubMed]

Y. Lin, C. Huang, D. Irwin, L. He, Y. Shang, and G. Yu, “Three-dimensional flow contrast imaging of deep tissue using noncontact diffuse correlation tomography,” Appl. Phys. Lett. 104(12), 121103 (2014).
[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]

Jöbsis, F. F.

F. F. Jöbsis, “Noninvasive, infrared monitoring of cerebral and myocardial oxygen sufficiency and circulatory parameters,” Science 198(4323), 1264–1267 (1977).
[Crossref] [PubMed]

Koppel, D. E.

D. E. Koppel, “Statistical Accuracy in Fluorescence Correlation Spectroscopy,” Phys. Rev. A 10(6), 1938–1945 (1974).
[Crossref]

Li, T.

Y. Shang, T. Li, L. Chen, Y. Lin, M. Toborek, and G. Yu, “Extraction of diffuse correlation spectroscopy flow index by integration of Nth-order linear model with Monte Carlo simulation,” Appl. Phys. Lett. 104(19), 193703 (2014).
[Crossref] [PubMed]

T. Li, H. Gong, and Q. M. Luo, “Mcvm: Monte Carlo Modeling of Photon Migration in Voxelized Media,” J. Innov. Opt. Heal, Sci. 3, 91–102 (2010).

Lin, Y.

L. He, Y. Lin, C. Huang, D. Irwin, M. M. Szabunio, and G. Yu, “Noncontact diffuse correlation tomography of human breast tumor,” J. Biomed. Opt. 20(8), 086003 (2015).
[Crossref] [PubMed]

Y. Lin, C. Huang, D. Irwin, L. He, Y. Shang, and G. Yu, “Three-dimensional flow contrast imaging of deep tissue using noncontact diffuse correlation tomography,” Appl. Phys. Lett. 104(12), 121103 (2014).
[Crossref] [PubMed]

Y. Shang, T. Li, L. Chen, Y. Lin, M. Toborek, and G. Yu, “Extraction of diffuse correlation spectroscopy flow index by integration of Nth-order linear model with Monte Carlo simulation,” Appl. Phys. Lett. 104(19), 193703 (2014).
[Crossref] [PubMed]

Long, D.

Y. Shang, K. Gurley, B. Symons, D. Long, R. Srikuea, L. J. Crofford, C. A. Peterson, and G. Yu, “Noninvasive optical characterization of muscle blood flow, oxygenation, and metabolism in women with fibromyalgia,” Arthritis Res. Ther. 14(6), R236 (2012).
[Crossref] [PubMed]

Luo, Q. M.

T. Li, H. Gong, and Q. M. Luo, “Mcvm: Monte Carlo Modeling of Photon Migration in Voxelized Media,” J. Innov. Opt. Heal, Sci. 3, 91–102 (2010).

Mandeville, J. B.

D. A. Boas, T. Gaudette, G. Strangman, X. Cheng, J. J. A. Marota, and J. B. Mandeville, “The accuracy of near infrared spectroscopy and imaging during focal changes in cerebral hemodynamics,” Neuroimage 13(1), 76–90 (2001).
[Crossref] [PubMed]

Maret, G.

G. Maret and P. E. Wolf, “Multiple Light-Scattering from Disordered Media - the Effect of Brownian-Motion of Scatterers,” Z. Phys. B Condens. Matter 65(4), 409–413 (1987).
[Crossref]

Marota, J. J. A.

D. A. Boas, T. Gaudette, G. Strangman, X. Cheng, J. J. A. Marota, and J. B. Mandeville, “The accuracy of near infrared spectroscopy and imaging during focal changes in cerebral hemodynamics,” Neuroimage 13(1), 76–90 (2001).
[Crossref] [PubMed]

Meek, J. H.

J. C. Hebden, A. Gibson, T. Austin, R. M. Yusof, N. Everdell, D. T. Delpy, S. R. Arridge, J. H. Meek, and J. S. Wyatt, “Imaging changes in blood volume and oxygenation in the newborn infant brain using three-dimensional optical tomography,” Phys. Med. Biol. 49(7), 1117–1130 (2004).
[Crossref] [PubMed]

Mohammadi-Arani, R.

M. Dehghan and R. Mohammadi-Arani, “Generalized product-type methods based on bi-conjugate gradient (GPBiCG) for solving shifted linear systems,” Comput. Appl. Math. 36(4), 1591–1606 (2017).
[Crossref]

Murkin, J. M.

4J. M. Murkin and M. Arango, “Near-infrared spectroscopy as an index of brain and tissue oxygenation,” British Journal of Anaesthesia 103, i3–i13 (2009).

Muthalib, M.

M. Ferrari, M. Muthalib, and V. Quaresima, “The use of near-infrared spectroscopy in understanding skeletal muscle physiology: recent developments,” Philos Trans A Math Phys Eng Sci 369(1955), 4577–4590 (2011).
[Crossref] [PubMed]

Nini, A.

M. Vardi and A. Nini, “Near-infrared spectroscopy for evaluation of peripheral vascular disease. A systematic review of literature,” Eur. J. Vasc. Endovasc. Surg. 35(1), 68–74 (2008).
[Crossref] [PubMed]

Pan, X.

E. Y. Sidky and X. Pan, “Image reconstruction in circular cone-beam computed tomography by constrained, total-variation minimization,” Phys. Med. Biol. 53(17), 4777–4807 (2008).
[Crossref] [PubMed]

Patel, M.

N. Roche-Labarbe, S. A. Carp, A. Surova, M. Patel, D. A. Boas, P. E. Grant, and M. A. Franceschini, “Noninvasive optical measures of CBV, StO(2), CBF index, and rCMRO(2) in human premature neonates’ brains in the first six weeks of life,” Hum. Brain Mapp. 31(3), 341–352 (2010).
[Crossref] [PubMed]

Paulsen, K. D.

H. Dehghani, M. E. Eames, P. K. Yalavarthy, S. C. Davis, S. Srinivasan, C. M. Carpenter, B. W. Pogue, and K. D. Paulsen, “Near infrared optical tomography using NIRFAST: Algorithm for numerical model and image reconstruction,” Commun. Numer. Methods Eng. 25(6), 711–732 (2009).
[Crossref] [PubMed]

Peterson, C. A.

Y. Shang, K. Gurley, B. Symons, D. Long, R. Srikuea, L. J. Crofford, C. A. Peterson, and G. Yu, “Noninvasive optical characterization of muscle blood flow, oxygenation, and metabolism in women with fibromyalgia,” Arthritis Res. Ther. 14(6), R236 (2012).
[Crossref] [PubMed]

Pine, D. J.

D. J. Pine, D. A. Weitz, P. M. Chaikin, and E. Herbolzheimer, “Diffusing Wave Spectroscopy,” Phys. Rev. Lett. 60(12), 1134–1137 (1988).
[Crossref] [PubMed]

Pogue, B. W.

H. Dehghani, M. E. Eames, P. K. Yalavarthy, S. C. Davis, S. Srinivasan, C. M. Carpenter, B. W. Pogue, and K. D. Paulsen, “Near infrared optical tomography using NIRFAST: Algorithm for numerical model and image reconstruction,” Commun. Numer. Methods Eng. 25(6), 711–732 (2009).
[Crossref] [PubMed]

Quaresima, V.

M. Ferrari, M. Muthalib, and V. Quaresima, “The use of near-infrared spectroscopy in understanding skeletal muscle physiology: recent developments,” Philos Trans A Math Phys Eng Sci 369(1955), 4577–4590 (2011).
[Crossref] [PubMed]

Riley, J.

A. Douiri, M. Schweiger, J. Riley, and S. R. Arridge, “Anisotropic diffusion regularization methods for diffuse optical tomography using edge prior information,” Meas. Sci. Technol. 18(1), 87–95 (2007).
[Crossref]

Robichaux-Viehoever, A.

A. T. Eggebrecht, S. L. Ferradal, A. Robichaux-Viehoever, M. S. Hassanpour, H. Dehghani, A. Z. Snyder, T. Hershey, and J. P. Culver, “Mapping distributed brain function and networks with diffuse optical tomography,” Nat. Photonics 8(6), 448–454 (2014).
[Crossref] [PubMed]

Roche-Labarbe, N.

N. Roche-Labarbe, S. A. Carp, A. Surova, M. Patel, D. A. Boas, P. E. Grant, and M. A. Franceschini, “Noninvasive optical measures of CBV, StO(2), CBF index, and rCMRO(2) in human premature neonates’ brains in the first six weeks of life,” Hum. Brain Mapp. 31(3), 341–352 (2010).
[Crossref] [PubMed]

Schweiger, M.

A. Douiri, M. Schweiger, J. Riley, and S. R. Arridge, “Anisotropic diffusion regularization methods for diffuse optical tomography using edge prior information,” Meas. Sci. Technol. 18(1), 87–95 (2007).
[Crossref]

Shang, Y.

J. Guo, Z. Gui, H. Hou, and Y. Shang, “Flexible positioning of source-detector arrays in 3D visualization platform for Monte Carlo simulation of light propagation,” IEEE Access 5(12), 26673–26680 (2017).
[Crossref]

Y. Shang and G. Yu, “A Nth-order linear algorithm for extracting diffuse correlation spectroscopy blood flow indices in heterogeneous tissues,” Appl. Phys. Lett. 105(13), 133702 (2014).
[Crossref] [PubMed]

Y. Lin, C. Huang, D. Irwin, L. He, Y. Shang, and G. Yu, “Three-dimensional flow contrast imaging of deep tissue using noncontact diffuse correlation tomography,” Appl. Phys. Lett. 104(12), 121103 (2014).
[Crossref] [PubMed]

Y. Shang, T. Li, L. Chen, Y. Lin, M. Toborek, and G. Yu, “Extraction of diffuse correlation spectroscopy flow index by integration of Nth-order linear model with Monte Carlo simulation,” Appl. Phys. Lett. 104(19), 193703 (2014).
[Crossref] [PubMed]

Y. Shang, K. Gurley, B. Symons, D. Long, R. Srikuea, L. J. Crofford, C. A. Peterson, and G. Yu, “Noninvasive optical characterization of muscle blood flow, oxygenation, and metabolism in women with fibromyalgia,” Arthritis Res. Ther. 14(6), R236 (2012).
[Crossref] [PubMed]

Sidky, E. Y.

E. Y. Sidky and X. Pan, “Image reconstruction in circular cone-beam computed tomography by constrained, total-variation minimization,” Phys. Med. Biol. 53(17), 4777–4807 (2008).
[Crossref] [PubMed]

Snyder, A. Z.

A. T. Eggebrecht, S. L. Ferradal, A. Robichaux-Viehoever, M. S. Hassanpour, H. Dehghani, A. Z. Snyder, T. Hershey, and J. P. Culver, “Mapping distributed brain function and networks with diffuse optical tomography,” Nat. Photonics 8(6), 448–454 (2014).
[Crossref] [PubMed]

Srikuea, R.

Y. Shang, K. Gurley, B. Symons, D. Long, R. Srikuea, L. J. Crofford, C. A. Peterson, and G. Yu, “Noninvasive optical characterization of muscle blood flow, oxygenation, and metabolism in women with fibromyalgia,” Arthritis Res. Ther. 14(6), R236 (2012).
[Crossref] [PubMed]

Srinivasan, S.

H. Dehghani, M. E. Eames, P. K. Yalavarthy, S. C. Davis, S. Srinivasan, C. M. Carpenter, B. W. Pogue, and K. D. Paulsen, “Near infrared optical tomography using NIRFAST: Algorithm for numerical model and image reconstruction,” Commun. Numer. Methods Eng. 25(6), 711–732 (2009).
[Crossref] [PubMed]

Stott, J.

Strangman, G.

D. A. Boas, T. Gaudette, G. Strangman, X. Cheng, J. J. A. Marota, and J. B. Mandeville, “The accuracy of near infrared spectroscopy and imaging during focal changes in cerebral hemodynamics,” Neuroimage 13(1), 76–90 (2001).
[Crossref] [PubMed]

Surova, A.

N. Roche-Labarbe, S. A. Carp, A. Surova, M. Patel, D. A. Boas, P. E. Grant, and M. A. Franceschini, “Noninvasive optical measures of CBV, StO(2), CBF index, and rCMRO(2) in human premature neonates’ brains in the first six weeks of life,” Hum. Brain Mapp. 31(3), 341–352 (2010).
[Crossref] [PubMed]

Symons, B.

Y. Shang, K. Gurley, B. Symons, D. Long, R. Srikuea, L. J. Crofford, C. A. Peterson, and G. Yu, “Noninvasive optical characterization of muscle blood flow, oxygenation, and metabolism in women with fibromyalgia,” Arthritis Res. Ther. 14(6), R236 (2012).
[Crossref] [PubMed]

Szabunio, M. M.

L. He, Y. Lin, C. Huang, D. Irwin, M. M. Szabunio, and G. Yu, “Noncontact diffuse correlation tomography of human breast tumor,” J. Biomed. Opt. 20(8), 086003 (2015).
[Crossref] [PubMed]

Takahashi, K.

C. Cheung, J. P. Culver, K. Takahashi, J. H. Greenberg, and A. G. Yodh, “In vivo cerebrovascular measurement combining diffuse near-infrared absorption and correlation spectroscopies,” Phys. Med. Biol. 46(8), 2053–2065 (2001).
[Crossref] [PubMed]

Toborek, M.

Y. Shang, T. Li, L. Chen, Y. Lin, M. Toborek, and G. Yu, “Extraction of diffuse correlation spectroscopy flow index by integration of Nth-order linear model with Monte Carlo simulation,” Appl. Phys. Lett. 104(19), 193703 (2014).
[Crossref] [PubMed]

Vardi, M.

M. Vardi and A. Nini, “Near-infrared spectroscopy for evaluation of peripheral vascular disease. A systematic review of literature,” Eur. J. Vasc. Endovasc. Surg. 35(1), 68–74 (2008).
[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]

Weitz, D. A.

D. J. Pine, D. A. Weitz, P. M. Chaikin, and E. Herbolzheimer, “Diffusing Wave Spectroscopy,” Phys. Rev. Lett. 60(12), 1134–1137 (1988).
[Crossref] [PubMed]

Wolf, P. E.

G. Maret and P. E. Wolf, “Multiple Light-Scattering from Disordered Media - the Effect of Brownian-Motion of Scatterers,” Z. Phys. B Condens. Matter 65(4), 409–413 (1987).
[Crossref]

Wyatt, J. S.

J. C. Hebden, A. Gibson, T. Austin, R. M. Yusof, N. Everdell, D. T. Delpy, S. R. Arridge, J. H. Meek, and J. S. Wyatt, “Imaging changes in blood volume and oxygenation in the newborn infant brain using three-dimensional optical tomography,” Phys. Med. Biol. 49(7), 1117–1130 (2004).
[Crossref] [PubMed]

Yalavarthy, P. K.

H. Dehghani, M. E. Eames, P. K. Yalavarthy, S. C. Davis, S. Srinivasan, C. M. Carpenter, B. W. Pogue, and K. D. Paulsen, “Near infrared optical tomography using NIRFAST: Algorithm for numerical model and image reconstruction,” Commun. Numer. Methods Eng. 25(6), 711–732 (2009).
[Crossref] [PubMed]

Yodh, A.

Yodh, A. G.

T. Durduran, R. Choe, W. B. Baker, and A. G. Yodh, “Diffuse optics for tissue monitoring and tomography,” Rep. Prog. Phys. 73(7), 076701 (2010).
[Crossref] [PubMed]

J. P. Culver, T. Durduran, D. Furuya, C. Cheung, J. H. Greenberg, and A. G. Yodh, “Diffuse optical tomography of cerebral blood flow, oxygenation, and metabolism in rat during focal ischemia,” J. Cereb. Blood Flow Metab. 23(8), 911–924 (2003).
[Crossref] [PubMed]

C. Cheung, J. P. Culver, K. Takahashi, J. H. Greenberg, and A. G. Yodh, “In vivo cerebrovascular measurement combining diffuse near-infrared absorption and correlation spectroscopies,” Phys. Med. Biol. 46(8), 2053–2065 (2001).
[Crossref] [PubMed]

D. A. Boas, L. E. Campbell, and A. G. Yodh, “Scattering and imaging with diffusing temporal field correlations,” Phys. Rev. Lett. 75(9), 1855–1858 (1995).
[Crossref] [PubMed]

Yu, G.

L. He, Y. Lin, C. Huang, D. Irwin, M. M. Szabunio, and G. Yu, “Noncontact diffuse correlation tomography of human breast tumor,” J. Biomed. Opt. 20(8), 086003 (2015).
[Crossref] [PubMed]

Y. Lin, C. Huang, D. Irwin, L. He, Y. Shang, and G. Yu, “Three-dimensional flow contrast imaging of deep tissue using noncontact diffuse correlation tomography,” Appl. Phys. Lett. 104(12), 121103 (2014).
[Crossref] [PubMed]

Y. Shang, T. Li, L. Chen, Y. Lin, M. Toborek, and G. Yu, “Extraction of diffuse correlation spectroscopy flow index by integration of Nth-order linear model with Monte Carlo simulation,” Appl. Phys. Lett. 104(19), 193703 (2014).
[Crossref] [PubMed]

Y. Shang and G. Yu, “A Nth-order linear algorithm for extracting diffuse correlation spectroscopy blood flow indices in heterogeneous tissues,” Appl. Phys. Lett. 105(13), 133702 (2014).
[Crossref] [PubMed]

Y. Shang, K. Gurley, B. Symons, D. Long, R. Srikuea, L. J. Crofford, C. A. Peterson, and G. Yu, “Noninvasive optical characterization of muscle blood flow, oxygenation, and metabolism in women with fibromyalgia,” Arthritis Res. Ther. 14(6), R236 (2012).
[Crossref] [PubMed]

G. Yu, “Near-infrared diffuse correlation spectroscopy in cancer diagnosis and therapy monitoring,” J. Biomed. Opt. 17(1), 010901 (2012).
[Crossref] [PubMed]

C. Zhou, G. Yu, D. Furuya, J. Greenberg, A. Yodh, and T. Durduran, “Diffuse optical correlation tomography of cerebral blood flow during cortical spreading depression in rat brain,” Opt. Express 14(3), 1125–1144 (2006).
[Crossref] [PubMed]

Yusof, R. M.

J. C. Hebden, A. Gibson, T. Austin, R. M. Yusof, N. Everdell, D. T. Delpy, S. R. Arridge, J. H. Meek, and J. S. Wyatt, “Imaging changes in blood volume and oxygenation in the newborn infant brain using three-dimensional optical tomography,” Phys. Med. Biol. 49(7), 1117–1130 (2004).
[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]

Zhou, C.

Appl. Phys. Lett. (3)

Y. Lin, C. Huang, D. Irwin, L. He, Y. Shang, and G. Yu, “Three-dimensional flow contrast imaging of deep tissue using noncontact diffuse correlation tomography,” Appl. Phys. Lett. 104(12), 121103 (2014).
[Crossref] [PubMed]

Y. Shang, T. Li, L. Chen, Y. Lin, M. Toborek, and G. Yu, “Extraction of diffuse correlation spectroscopy flow index by integration of Nth-order linear model with Monte Carlo simulation,” Appl. Phys. Lett. 104(19), 193703 (2014).
[Crossref] [PubMed]

Y. Shang and G. Yu, “A Nth-order linear algorithm for extracting diffuse correlation spectroscopy blood flow indices in heterogeneous tissues,” Appl. Phys. Lett. 105(13), 133702 (2014).
[Crossref] [PubMed]

Arthritis Res. Ther. (1)

Y. Shang, K. Gurley, B. Symons, D. Long, R. Srikuea, L. J. Crofford, C. A. Peterson, and G. Yu, “Noninvasive optical characterization of muscle blood flow, oxygenation, and metabolism in women with fibromyalgia,” Arthritis Res. Ther. 14(6), R236 (2012).
[Crossref] [PubMed]

British Journal of Anaesthesia (1)

4J. M. Murkin and M. Arango, “Near-infrared spectroscopy as an index of brain and tissue oxygenation,” British Journal of Anaesthesia 103, i3–i13 (2009).

Commun. Numer. Methods Eng. (1)

H. Dehghani, M. E. Eames, P. K. Yalavarthy, S. C. Davis, S. Srinivasan, C. M. Carpenter, B. W. Pogue, and K. D. Paulsen, “Near infrared optical tomography using NIRFAST: Algorithm for numerical model and image reconstruction,” Commun. Numer. Methods Eng. 25(6), 711–732 (2009).
[Crossref] [PubMed]

Comput. Appl. Math. (1)

M. Dehghan and R. Mohammadi-Arani, “Generalized product-type methods based on bi-conjugate gradient (GPBiCG) for solving shifted linear systems,” Comput. Appl. Math. 36(4), 1591–1606 (2017).
[Crossref]

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]

Eur. J. Vasc. Endovasc. Surg. (1)

M. Vardi and A. Nini, “Near-infrared spectroscopy for evaluation of peripheral vascular disease. A systematic review of literature,” Eur. J. Vasc. Endovasc. Surg. 35(1), 68–74 (2008).
[Crossref] [PubMed]

Hum. Brain Mapp. (1)

N. Roche-Labarbe, S. A. Carp, A. Surova, M. Patel, D. A. Boas, P. E. Grant, and M. A. Franceschini, “Noninvasive optical measures of CBV, StO(2), CBF index, and rCMRO(2) in human premature neonates’ brains in the first six weeks of life,” Hum. Brain Mapp. 31(3), 341–352 (2010).
[Crossref] [PubMed]

IEEE Access (1)

J. Guo, Z. Gui, H. Hou, and Y. Shang, “Flexible positioning of source-detector arrays in 3D visualization platform for Monte Carlo simulation of light propagation,” IEEE Access 5(12), 26673–26680 (2017).
[Crossref]

J. Biomed. Opt. (2)

L. He, Y. Lin, C. Huang, D. Irwin, M. M. Szabunio, and G. Yu, “Noncontact diffuse correlation tomography of human breast tumor,” J. Biomed. Opt. 20(8), 086003 (2015).
[Crossref] [PubMed]

G. Yu, “Near-infrared diffuse correlation spectroscopy in cancer diagnosis and therapy monitoring,” J. Biomed. Opt. 17(1), 010901 (2012).
[Crossref] [PubMed]

J. Cereb. Blood Flow Metab. (1)

J. P. Culver, T. Durduran, D. Furuya, C. Cheung, J. H. Greenberg, and A. G. Yodh, “Diffuse optical tomography of cerebral blood flow, oxygenation, and metabolism in rat during focal ischemia,” J. Cereb. Blood Flow Metab. 23(8), 911–924 (2003).
[Crossref] [PubMed]

J. Innov. Opt. Heal, Sci. (1)

T. Li, H. Gong, and Q. M. Luo, “Mcvm: Monte Carlo Modeling of Photon Migration in Voxelized Media,” J. Innov. Opt. Heal, Sci. 3, 91–102 (2010).

Meas. Sci. Technol. (1)

A. Douiri, M. Schweiger, J. Riley, and S. R. Arridge, “Anisotropic diffusion regularization methods for diffuse optical tomography using edge prior information,” Meas. Sci. Technol. 18(1), 87–95 (2007).
[Crossref]

Nat. Photonics (1)

A. T. Eggebrecht, S. L. Ferradal, A. Robichaux-Viehoever, M. S. Hassanpour, H. Dehghani, A. Z. Snyder, T. Hershey, and J. P. Culver, “Mapping distributed brain function and networks with diffuse optical tomography,” Nat. Photonics 8(6), 448–454 (2014).
[Crossref] [PubMed]

Neuroimage (1)

D. A. Boas, T. Gaudette, G. Strangman, X. Cheng, J. J. A. Marota, and J. B. Mandeville, “The accuracy of near infrared spectroscopy and imaging during focal changes in cerebral hemodynamics,” Neuroimage 13(1), 76–90 (2001).
[Crossref] [PubMed]

Opt. Express (2)

Philos Trans A Math Phys Eng Sci (1)

M. Ferrari, M. Muthalib, and V. Quaresima, “The use of near-infrared spectroscopy in understanding skeletal muscle physiology: recent developments,” Philos Trans A Math Phys Eng Sci 369(1955), 4577–4590 (2011).
[Crossref] [PubMed]

Phys. Med. Biol. (4)

J. C. Hebden, A. Gibson, T. Austin, R. M. Yusof, N. Everdell, D. T. Delpy, S. R. Arridge, J. H. Meek, and J. S. Wyatt, “Imaging changes in blood volume and oxygenation in the newborn infant brain using three-dimensional optical tomography,” Phys. Med. Biol. 49(7), 1117–1130 (2004).
[Crossref] [PubMed]

S. R. Arridge and J. C. Hebden, “Optical imaging in medicine: II. Modelling and reconstruction,” Phys. Med. Biol. 42(5), 841–853 (1997).
[Crossref] [PubMed]

C. Cheung, J. P. Culver, K. Takahashi, J. H. Greenberg, and A. G. Yodh, “In vivo cerebrovascular measurement combining diffuse near-infrared absorption and correlation spectroscopies,” Phys. Med. Biol. 46(8), 2053–2065 (2001).
[Crossref] [PubMed]

E. Y. Sidky and X. Pan, “Image reconstruction in circular cone-beam computed tomography by constrained, total-variation minimization,” Phys. Med. Biol. 53(17), 4777–4807 (2008).
[Crossref] [PubMed]

Phys. Rev. A (1)

D. E. Koppel, “Statistical Accuracy in Fluorescence Correlation Spectroscopy,” Phys. Rev. A 10(6), 1938–1945 (1974).
[Crossref]

Phys. Rev. Lett. (2)

D. J. Pine, D. A. Weitz, P. M. Chaikin, and E. Herbolzheimer, “Diffusing Wave Spectroscopy,” Phys. Rev. Lett. 60(12), 1134–1137 (1988).
[Crossref] [PubMed]

D. A. Boas, L. E. Campbell, and A. G. Yodh, “Scattering and imaging with diffusing temporal field correlations,” Phys. Rev. Lett. 75(9), 1855–1858 (1995).
[Crossref] [PubMed]

Rep. Prog. Phys. (1)

T. Durduran, R. Choe, W. B. Baker, and A. G. Yodh, “Diffuse optics for tissue monitoring and tomography,” Rep. Prog. Phys. 73(7), 076701 (2010).
[Crossref] [PubMed]

Science (1)

F. F. Jöbsis, “Noninvasive, infrared monitoring of cerebral and myocardial oxygen sufficiency and circulatory parameters,” Science 198(4323), 1264–1267 (1977).
[Crossref] [PubMed]

Z. Phys. B Condens. Matter (1)

G. Maret and P. E. Wolf, “Multiple Light-Scattering from Disordered Media - the Effect of Brownian-Motion of Scatterers,” Z. Phys. B Condens. Matter 65(4), 409–413 (1987).
[Crossref]

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Figures (8)

Fig. 1
Fig. 1 the placement of S-D array on the surface of human forehead.
Fig. 2
Fig. 2 Setup of a cross-shape anomaly (a) and dual cube-shape anomalies (c) in 3D human head (9 mm beneath the forehead surface). (b) and (d) show the two anomaly setup in 2D transverse plane respectively.
Fig. 3
Fig. 3 (a) is the curve of autocorrelation g1(τ, i, j) with and without noise, collected at the S-D separation of 6.3 mm, 12 mm, and 17 mm, respectively.(b) A zoom-in segment of g1(τ, i, j) curve at the 6.3 mm S-D separation, marked with three representative of single delay time (τ = 1.7 × 10−6, 3.2 × 10−6, 5.7 × 10−6 second [22, 23])
Fig. 4
Fig. 4 BFI images reconstructed from g1(τ) data without noise, and shown in 3D volume (a and c) and 2D transverse plane (b and d), respectively . The anomaly is either a cross-shape (a and b) or dual cube-shape (c and d).
Fig. 5
Fig. 5 BFI images reconstructed from g1(τ) data with noise, and shown in 3D volume (a and c) and 2D transverse plane (b and d), respectively . The anomaly is either a cross-shape (a and b) or dual cube-shape (c and d).
Fig. 6
Fig. 6 Time-course RMSE (a and b) and CORR (c and d) values calculated from the reconstructed images. The outcomes were derived from the g1(τ) data without noise (a and c) and with noise (b and d). In all sub-figures, the red solid curve denotes the outcomes of cross-shaped anomaly, and blue dotted curve denotes those of dual cube-shape anomalies.
Fig. 7
Fig. 7 RMSE and CORR values of reconstructed images as the depth of the anomalies increased. (a) RMSE without noise. (b) RMSE with noise. (c) CORR without noise. (d) CORR with noise. Red is cross-shaped anomaly and blue is two cube-shaped anomalies.
Fig. 8
Fig. 8 Reconstruction of cross-shape anomaly with varied flow contrast; (a)-(e): the reconstructed images with flow contrast varied from 1.5-fold to 7-fold; (f): the misjudgment ratio of anomaly at different flow contrast.

Equations (35)

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( ( D ( r ) v ) G 1 ( r , τ ) ) ( μ a ( r ) + 1 3 μ s ' ( r ) k 0 2 α Δ r 2 ( τ ) ) G 1 ( r , τ ) = S ( r ) e i 2 π τ c λ
φ s ( r s i , r d i , τ ) = ln g 1 ( r s i , r d i , τ ) g 1 , 0 ( r s i , r d i , τ ) = j = 1 N W i j ( r s i , r d i , r j , τ ) Δ ( α D B ( r j ) )
g 1 ( m , j , τ ) = < E ( m , j , 0 ) E * ( m , j , τ ) > < | E ( m , j , 0 ) | 2 > = 0 P ( m , j , s 1 , ... , s n ) exp ( - 1 3 i = 1 n k 0 2 ( i ) < Δ r i 2 ( τ ) > s i l i * ) d ( s 1 , ... , s n ) = 0 P ( m , j , s 1 , ... , s n ) exp ( 2 i = 1 n k 0 2 ( i ) α D B ( i ) s i μ s ' ( i ) τ ) d ( s 1 , ... , s n )
g 1 ( m , j , τ ) = g 1 ( m , j , 0 ) + g 1 ( 1 ) ( m , j , 0 ) τ + k = 2 N g 1 ( k ) ( m , j , 0 ) k ! τ k + g 1 ( N + 1 ) ( m , j , ξ ) τ N + 1 ( N + 1 ) ! , (0 < ξ < τ )
g 1 ( m , j , τ ) 1 = τ 0 P ( m , j , s 1 , ... , s n ) [ 2 i = 1 n k 0 2 ( i ) α D B ( i ) s i μ s ' ( i )] d ( s 1 , ... , s n )
g 1 ( m , j , τ ) 1- k = 2 N 0 P ( m , j , s 1 , ... , s n ) [ 2 i = 1 n k 0 2 ( i ) α D B ( i ) s i μ s ' ( i ) ] k d ( s 1 , ... , s n ) k ! τ k = τ 0 P ( m , j , s 1 , ... , s n ) [ 2 i = 1 n k 0 2 ( i ) α D B ( i ) s i μ s ' ( i ) ] d ( s 1 , ... , s n )
g 1 ( m , j , τ ) 1 = τ i = 1 n B ( m , j , i ) α D B ( i )
g 1 ( m , j , τ ) 1 k = 2 N q = 1 Q w ( q , m , j ) ( 2 i = 1 n k 0 2 ( i ) α D B ( i ) s ( i , q , m , j ) μ s ' ( i ) ) k k ! τ k = τ i = 1 n B ( m , j , i ) α D B ( i )
B ( m , j , i ) = q = 1 Q 2 w ( q , m , j ) k 0 2 ( i ) s ( i , q , m , j ) μ s ' ( i )
A ( h , i ) = B ( m , j , i )
α D B = [ α D B ( 1 ) , α D B ( 2 ) , α D B ( n ) ] T
g 1 ( h , τ ) 1 = τ i = 1 n B ( m , j , i ) α D B ( 1 ) ( i ) = τ i = 1 n A ( h , i ) α D B ( 1 ) ( i ) = τ ( A α D B ( 1 ) )
A α D B ( 1 ) = S l
g 1 ( h , τ ) 1 k = 2 N q = 1 Q w ( q , h ) ( 2 i = 1 n k 0 2 ( i ) α D B ( N 1 ) ( i ) s ( i , q , h ) μ s ' ( i ) ) k k ! τ k = τ i = 1 n A ( h , i ) α D B ( N ) ( i ) = τ ( A α D B ( N ) )
A α D B ( N ) = S l ( N )
v * = arg min v T V + μ 2 A v b 2 2 s .t . v i 0 ( i = 1 , 2 , ... , n )
v T V = ν ( x , y , z ) 1 = x ν 1 + y ν 1 + z ν 1
( x v ) i , j , k = v i + 1 , j , k v i , j , k ( y v ) i , j , k = v i , j + 1 , k v i , j , k ( z v ) i , j , k = v i , j , k + 1 v i , j , k
min v , d x , d y , d z d x 1 + d y 1 + d z 1 + μ 2 A v b 2 2 s . t . d x = x v , d y = y v , d z = z v
min v , d x , d y , d z d x 1 + d y 1 + d z 1 + μ 2 A v b 2 2 + λ 2 d x - x v - b x k 2 2 + λ 2 d y - y v - b y k 2 2 + λ 2 d z - z v - b z k 2 2
b x k + 1 = b x k + ( x v k + 1 d x k + 1 )
b y k + 1 = b y k + ( y v k + 1 d y k + 1 )
b z k + 1 = b z k + ( z v k + 1 d z k + 1 )
v k + 1 = arg min v μ 2 A v - b 2 2 + λ 2 d x k - x v - b x k 2 2 + λ 2 d y k - y v - b y k 2 2 + λ 2 d z k - z v - b z k 2 2
v k + 1 = { v k + 1 v k + 1 0 0 v k + 1 < 0
( d x k + 1 , d y k + 1 , d z k + ! ) = arg min d x , d y , d z d x 1 + d y 1 + d z 1 + λ 2 d x - x v k + 1 - b x k 2 2 + λ 2 d y - y v k + 1 - b y k 2 2 + λ 2 d z - z v k + 1 - b z k 2 2
v k + 1 v k 2 < ε
d x k + 1 = shrink ( | x v k + 1 + b x k | , 1 λ )
d y k + 1 = shrink ( | y v k + 1 + b y k | , 1 λ )
d z k + 1 = shrink ( | z v k + 1 + b z k | , 1 λ )
shrink ( t , γ ) = t | t | * max ( | t | γ , 0 )
g 1 ( m , j , τ ) = q = 1 Q w ( q , m , j ) exp ( 2 i = 1 n k 0 2 ( i ) α D B ( i ) s ( i , q , m , j ) μ s ' ( i ) )
σ ( τ ) = T t [ β 2 ( 1 + e 2 Γ T ) ( 1 + e 2 Γ τ ) + 2 m ( 1 e 2 Γ T ) e 2 Γ T ( 1 e 2 Γ T ) + 2 n 1 β ( 1 + e 2 Γ τ ) + n 2 β ( 1 + e 2 Γ τ ) ] 1 2
RMSE = 1 n i n ( α D B i α D B , 0 i α D B , 0 i ) 2
CORR = i = 1 n α D B i α D B , 0 i i = 1 n ( α D B i ) 2 i = 1 n ( α D B , 0 i ) 2

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