Abstract

Image reconstruction in the most model-based biophotonic imaging modalities essentially poses an ill-posed nonlinear inverse problem, which has been effectively tackled in the diffusion-approximation-satisfied scenarios such as diffuse optical tomography. Nevertheless, a nonlinear implementation in high-resolution laminar optical tomography (LOT) is normally computationally-costly due to its strong dependency on a dense source-detector configuration and a physically-rigorous photon-transport model. To circumvent the adversity, we herein propose a practical nonlinear LOT approach to the absorption reconstruction. The scheme takes advantage of the numerical stability of the singular value decomposition (SVD) for the ill-posed linear inversion, and is accelerated by adopting an explicitly recursive strategy for the time-consuming repeated SVD inversion, which is based on a scaled expression of the sensitivity matrix. Experiments demonstrate that the proposed methodology can perform as well as the traditional nonlinear one, while the computation time of the former is merely 26.27% of the later on average.

© 2017 Optical Society of America

Full Article  |  PDF Article
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References

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2016 (3)

M. Schwarz, A. Buehler, J. Aguirre, and V. Ntziachristos, “Three-dimensional multispectral optoacoustic mesoscopy reveals melanin and blood oxygenation in human skin in vivo,” J. Biophotonics 9(1-2), 55–60 (2016).
[Crossref] [PubMed]

M. Jia, H. Zhao, J. Li, L. Liu, L. Zhang, J. Jiang, and F. Gao, “Coupling between radiative transport and diffusion approximation for enhanced near-field photon-migration modeling based on transient photon kinetics,” J. Biomed. Opt. 21(5), 050501 (2016).
[Crossref] [PubMed]

H. Zhao, S. Wang, M. Jia, X. Chen, J. Qi, J. Tian, W. Ma, J. Li, and F. Gao, “A modified laminar optical tomography system with small dip-angle and the initial validation,” Proc. SPIE 9700, 97001B (2016).
[Crossref]

2015 (2)

2014 (4)

M. Jia, S. Cui, X. Chen, M. Liu, X. Zhou, H. Zhao, and F. Gao, “Image reconstruction method for laminar optical tomography with only a single Monte-Carlo simulation,” Chin. Opt. Lett. 12(3), 031702 (2014).
[Crossref]

X. Yi, X. Wang, W. Chen, W. Wan, H. Zhao, and F. Gao, “Full domain-decomposition scheme for diffuse optical tomography of large-sized tissues with a combined CPU and GPU parallelization,” Appl. Opt. 53(13), 2754–2765 (2014).
[Crossref] [PubMed]

Y. Yamada and S. Okawa, “Diffuse optical tomography: present status and its future,” Opt. Rev. 21(3), 185–205 (2014).
[Crossref]

H. Fujii, S. Okawa, Y. Yamada, and Y. Hoshi, “Hybrid model of light propagation in random media based on the time-dependent radiative transfer and diffusion equations,” J. Quant. Spectrosc. Radiat. Transf. 147, 145–154 (2014).
[Crossref]

2013 (1)

S. L. Jacques, “Optical properties of biological tissues: a review,” Phys. Med. Biol. 58(11), R37–R61 (2013).
[Crossref] [PubMed]

2012 (1)

2011 (1)

C. Gong, J. Liu, L. Chi, H. Huang, J. Fang, and Z. Gong, “GPU accelerated simulations of 3D deterministic particle transport using discrete ordinates method,” J. Comput. Phys. 230(15), 6010–6022 (2011).
[Crossref]

2010 (1)

H. Niu, Z. J. Lin, F. Tian, S. Dhamne, and H. Liu, “Comprehensive investigation of three-dimensional diffuse optical tomography with depth compensation algorithm,” J. Biomed. Opt. 15(4), 046005 (2010).
[Crossref] [PubMed]

2009 (5)

S. Gupta, P. K. Yalavarthy, D. Roy, D. Piao, and R. M. Vasu, “Singular value decomposition based computationally efficient algorithm for rapid dynamic near-infrared diffuse optical tomography,” Med. Phys. 36(12), 5559–5567 (2009).
[Crossref] [PubMed]

B. Yuan, S. A. Burgess, A. Iranmahboob, M. B. Bouchard, N. Lehrer, C. Bordier, and E. M. C. Hillman, “A system for high-resolution depth-resolved optical imaging of fluorescence and absorption contrast,” Rev. Sci. Instrum. 80(4), 043706 (2009).
[Crossref] [PubMed]

S. R. Arridge and J. C. Schotland, “Optical tomography: forward and inverse problems,” Inverse Probl. 25(12), 123010 (2009).
[Crossref]

L. Yao, Y. Sun, and H. Jiang, “Quantitative photoacoustic tomography based on the radiative transfer equation,” Opt. Lett. 34(12), 1765–1767 (2009).
[Crossref] [PubMed]

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).
[Crossref] [PubMed]

2008 (1)

I. Seo, C. K. Hayakawa, and V. Venugopalan, “Radiative transport in the delta-P1 approximation for semi-infinite turbid media,” Med. Phys. 35(2), 681–693 (2008).
[Crossref] [PubMed]

2007 (2)

2005 (1)

2004 (2)

2003 (1)

X. Gu, Y. Xu, and H. Jiang, “Mesh-based enhancement schemes in diffuse optical tomography,” Med. Phys. 30(5), 861–869 (2003).
[Crossref] [PubMed]

2001 (2)

E. M. Hillman, H. Dehghani, J. C. Hebden, S. R. Arridge, M. Schweiger, and D. T. Delpy, “Differential imaging in heterogeneous media: limitations of linearization assumptions in optical tomography,” Proc. SPIE 4250, 327–338 (2001).
[Crossref]

C. K. Hayakawa, J. Spanier, F. Bevilacqua, A. K. Dunn, J. S. You, B. J. Tromberg, and V. Venugopalan, “Perturbation Monte Carlo methods to solve inverse photon migration problems in heterogeneous tissues,” Opt. Lett. 26(17), 1335–1337 (2001).
[Crossref] [PubMed]

2000 (1)

1999 (1)

A. H. Hielscher, A. D. Klose, and K. M. Hanson, “Gradient-based iterative image reconstruction scheme for time-resolved optical tomography,” IEEE Trans. Med. Imaging 18(3), 262–271 (1999).
[Crossref] [PubMed]

1998 (1)

1991 (1)

J. Kandel, E. Bossy-Wetzel, F. Radvanyi, M. Klagsbrun, J. Folkman, and D. Hanahan, “Neovascularization is associated with a switch to the export of bFGF in the multistep development of fibrosarcoma,” Cell 66(6), 1095–1104 (1991).
[Crossref] [PubMed]

Aguirre, J.

M. Schwarz, A. Buehler, J. Aguirre, and V. Ntziachristos, “Three-dimensional multispectral optoacoustic mesoscopy reveals melanin and blood oxygenation in human skin in vivo,” J. Biophotonics 9(1-2), 55–60 (2016).
[Crossref] [PubMed]

Arridge, S.

Arridge, S. R.

S. R. Arridge and J. C. Schotland, “Optical tomography: forward and inverse problems,” Inverse Probl. 25(12), 123010 (2009).
[Crossref]

A. P. Gibson, J. C. Hebden, J. Riley, N. Everdell, M. Schweiger, S. R. Arridge, and D. T. Delpy, “Linear and nonlinear reconstruction for optical tomography of phantoms with nonscattering regions,” Appl. Opt. 44(19), 3925–3936 (2005).
[Crossref] [PubMed]

E. M. Hillman, H. Dehghani, J. C. Hebden, S. R. Arridge, M. Schweiger, and D. T. Delpy, “Differential imaging in heterogeneous media: limitations of linearization assumptions in optical tomography,” Proc. SPIE 4250, 327–338 (2001).
[Crossref]

Bangerth, W.

Bevilacqua, F.

Boas, D.

Boas, D. A.

Bordier, C.

B. Yuan, S. A. Burgess, A. Iranmahboob, M. B. Bouchard, N. Lehrer, C. Bordier, and E. M. C. Hillman, “A system for high-resolution depth-resolved optical imaging of fluorescence and absorption contrast,” Rev. Sci. Instrum. 80(4), 043706 (2009).
[Crossref] [PubMed]

Bossy-Wetzel, E.

J. Kandel, E. Bossy-Wetzel, F. Radvanyi, M. Klagsbrun, J. Folkman, and D. Hanahan, “Neovascularization is associated with a switch to the export of bFGF in the multistep development of fibrosarcoma,” Cell 66(6), 1095–1104 (1991).
[Crossref] [PubMed]

Bouchard, M. B.

B. Yuan, S. A. Burgess, A. Iranmahboob, M. B. Bouchard, N. Lehrer, C. Bordier, and E. M. C. Hillman, “A system for high-resolution depth-resolved optical imaging of fluorescence and absorption contrast,” Rev. Sci. Instrum. 80(4), 043706 (2009).
[Crossref] [PubMed]

Buehler, A.

M. Schwarz, A. Buehler, J. Aguirre, and V. Ntziachristos, “Three-dimensional multispectral optoacoustic mesoscopy reveals melanin and blood oxygenation in human skin in vivo,” J. Biophotonics 9(1-2), 55–60 (2016).
[Crossref] [PubMed]

Burgess, S. A.

T. J. Muldoon, S. A. Burgess, B. R. Chen, D. Ratner, and E. M. Hillman, “Analysis of skin lesions using laminar optical tomography,” Biomed. Opt. Express 3(7), 1701–1712 (2012).
[Crossref] [PubMed]

B. Yuan, S. A. Burgess, A. Iranmahboob, M. B. Bouchard, N. Lehrer, C. Bordier, and E. M. C. Hillman, “A system for high-resolution depth-resolved optical imaging of fluorescence and absorption contrast,” Rev. Sci. Instrum. 80(4), 043706 (2009).
[Crossref] [PubMed]

Chen, B. R.

Chen, W.

Chen, X.

H. Zhao, S. Wang, M. Jia, X. Chen, J. Qi, J. Tian, W. Ma, J. Li, and F. Gao, “A modified laminar optical tomography system with small dip-angle and the initial validation,” Proc. SPIE 9700, 97001B (2016).
[Crossref]

M. Jia, S. Cui, X. Chen, M. Liu, X. Zhou, H. Zhao, and F. Gao, “Image reconstruction method for laminar optical tomography with only a single Monte-Carlo simulation,” Chin. Opt. Lett. 12(3), 031702 (2014).
[Crossref]

Chi, L.

C. Gong, J. Liu, L. Chi, H. Huang, J. Fang, and Z. Gong, “GPU accelerated simulations of 3D deterministic particle transport using discrete ordinates method,” J. Comput. Phys. 230(15), 6010–6022 (2011).
[Crossref]

Cui, S.

Culver, J. P.

Dale, A. M.

Dehghani, H.

Delpy, D. T.

A. P. Gibson, J. C. Hebden, J. Riley, N. Everdell, M. Schweiger, S. R. Arridge, and D. T. Delpy, “Linear and nonlinear reconstruction for optical tomography of phantoms with nonscattering regions,” Appl. Opt. 44(19), 3925–3936 (2005).
[Crossref] [PubMed]

E. M. Hillman, H. Dehghani, J. C. Hebden, S. R. Arridge, M. Schweiger, and D. T. Delpy, “Differential imaging in heterogeneous media: limitations of linearization assumptions in optical tomography,” Proc. SPIE 4250, 327–338 (2001).
[Crossref]

Dhamne, S.

H. Niu, Z. J. Lin, F. Tian, S. Dhamne, and H. Liu, “Comprehensive investigation of three-dimensional diffuse optical tomography with depth compensation algorithm,” J. Biomed. Opt. 15(4), 046005 (2010).
[Crossref] [PubMed]

Dunn, A.

Dunn, A. K.

Eames, M. E.

Eggebrecht, A. T.

Everdell, N.

Fang, J.

C. Gong, J. Liu, L. Chi, H. Huang, J. Fang, and Z. Gong, “GPU accelerated simulations of 3D deterministic particle transport using discrete ordinates method,” J. Comput. Phys. 230(15), 6010–6022 (2011).
[Crossref]

Fang, Q.

Ferradal, S. L.

Folkman, J.

J. Kandel, E. Bossy-Wetzel, F. Radvanyi, M. Klagsbrun, J. Folkman, and D. Hanahan, “Neovascularization is associated with a switch to the export of bFGF in the multistep development of fibrosarcoma,” Cell 66(6), 1095–1104 (1991).
[Crossref] [PubMed]

Fujii, H.

H. Fujii, S. Okawa, Y. Yamada, and Y. Hoshi, “Hybrid model of light propagation in random media based on the time-dependent radiative transfer and diffusion equations,” J. Quant. Spectrosc. Radiat. Transf. 147, 145–154 (2014).
[Crossref]

Gao, F.

H. Zhao, S. Wang, M. Jia, X. Chen, J. Qi, J. Tian, W. Ma, J. Li, and F. Gao, “A modified laminar optical tomography system with small dip-angle and the initial validation,” Proc. SPIE 9700, 97001B (2016).
[Crossref]

M. Jia, H. Zhao, J. Li, L. Liu, L. Zhang, J. Jiang, and F. Gao, “Coupling between radiative transport and diffusion approximation for enhanced near-field photon-migration modeling based on transient photon kinetics,” J. Biomed. Opt. 21(5), 050501 (2016).
[Crossref] [PubMed]

X. Yi, X. Wang, W. Chen, W. Wan, H. Zhao, and F. Gao, “Full domain-decomposition scheme for diffuse optical tomography of large-sized tissues with a combined CPU and GPU parallelization,” Appl. Opt. 53(13), 2754–2765 (2014).
[Crossref] [PubMed]

M. Jia, S. Cui, X. Chen, M. Liu, X. Zhou, H. Zhao, and F. Gao, “Image reconstruction method for laminar optical tomography with only a single Monte-Carlo simulation,” Chin. Opt. Lett. 12(3), 031702 (2014).
[Crossref]

Gibson, A. P.

Gong, C.

C. Gong, J. Liu, L. Chi, H. Huang, J. Fang, and Z. Gong, “GPU accelerated simulations of 3D deterministic particle transport using discrete ordinates method,” J. Comput. Phys. 230(15), 6010–6022 (2011).
[Crossref]

Gong, Z.

C. Gong, J. Liu, L. Chi, H. Huang, J. Fang, and Z. Gong, “GPU accelerated simulations of 3D deterministic particle transport using discrete ordinates method,” J. Comput. Phys. 230(15), 6010–6022 (2011).
[Crossref]

Gu, X.

X. Gu, Y. Xu, and H. Jiang, “Mesh-based enhancement schemes in diffuse optical tomography,” Med. Phys. 30(5), 861–869 (2003).
[Crossref] [PubMed]

Gupta, S.

S. Gupta, P. K. Yalavarthy, D. Roy, D. Piao, and R. M. Vasu, “Singular value decomposition based computationally efficient algorithm for rapid dynamic near-infrared diffuse optical tomography,” Med. Phys. 36(12), 5559–5567 (2009).
[Crossref] [PubMed]

Hanahan, D.

J. Kandel, E. Bossy-Wetzel, F. Radvanyi, M. Klagsbrun, J. Folkman, and D. Hanahan, “Neovascularization is associated with a switch to the export of bFGF in the multistep development of fibrosarcoma,” Cell 66(6), 1095–1104 (1991).
[Crossref] [PubMed]

Hanson, K. M.

A. H. Hielscher, A. D. Klose, and K. M. Hanson, “Gradient-based iterative image reconstruction scheme for time-resolved optical tomography,” IEEE Trans. Med. Imaging 18(3), 262–271 (1999).
[Crossref] [PubMed]

Hayakawa, C. K.

Hebden, J. C.

A. P. Gibson, J. C. Hebden, J. Riley, N. Everdell, M. Schweiger, S. R. Arridge, and D. T. Delpy, “Linear and nonlinear reconstruction for optical tomography of phantoms with nonscattering regions,” Appl. Opt. 44(19), 3925–3936 (2005).
[Crossref] [PubMed]

E. M. Hillman, H. Dehghani, J. C. Hebden, S. R. Arridge, M. Schweiger, and D. T. Delpy, “Differential imaging in heterogeneous media: limitations of linearization assumptions in optical tomography,” Proc. SPIE 4250, 327–338 (2001).
[Crossref]

Hielscher, A. H.

A. H. Hielscher, A. D. Klose, and K. M. Hanson, “Gradient-based iterative image reconstruction scheme for time-resolved optical tomography,” IEEE Trans. Med. Imaging 18(3), 262–271 (1999).
[Crossref] [PubMed]

Hillman, E. M.

Hillman, E. M. C.

B. Yuan, S. A. Burgess, A. Iranmahboob, M. B. Bouchard, N. Lehrer, C. Bordier, and E. M. C. Hillman, “A system for high-resolution depth-resolved optical imaging of fluorescence and absorption contrast,” Rev. Sci. Instrum. 80(4), 043706 (2009).
[Crossref] [PubMed]

Hoshi, Y.

H. Fujii, S. Okawa, Y. Yamada, and Y. Hoshi, “Hybrid model of light propagation in random media based on the time-dependent radiative transfer and diffusion equations,” J. Quant. Spectrosc. Radiat. Transf. 147, 145–154 (2014).
[Crossref]

Huang, H.

C. Gong, J. Liu, L. Chi, H. Huang, J. Fang, and Z. Gong, “GPU accelerated simulations of 3D deterministic particle transport using discrete ordinates method,” J. Comput. Phys. 230(15), 6010–6022 (2011).
[Crossref]

Iranmahboob, A.

B. Yuan, S. A. Burgess, A. Iranmahboob, M. B. Bouchard, N. Lehrer, C. Bordier, and E. M. C. Hillman, “A system for high-resolution depth-resolved optical imaging of fluorescence and absorption contrast,” Rev. Sci. Instrum. 80(4), 043706 (2009).
[Crossref] [PubMed]

Jacques, S. L.

S. L. Jacques, “Optical properties of biological tissues: a review,” Phys. Med. Biol. 58(11), R37–R61 (2013).
[Crossref] [PubMed]

Jia, M.

H. Zhao, S. Wang, M. Jia, X. Chen, J. Qi, J. Tian, W. Ma, J. Li, and F. Gao, “A modified laminar optical tomography system with small dip-angle and the initial validation,” Proc. SPIE 9700, 97001B (2016).
[Crossref]

M. Jia, H. Zhao, J. Li, L. Liu, L. Zhang, J. Jiang, and F. Gao, “Coupling between radiative transport and diffusion approximation for enhanced near-field photon-migration modeling based on transient photon kinetics,” J. Biomed. Opt. 21(5), 050501 (2016).
[Crossref] [PubMed]

M. Jia, S. Cui, X. Chen, M. Liu, X. Zhou, H. Zhao, and F. Gao, “Image reconstruction method for laminar optical tomography with only a single Monte-Carlo simulation,” Chin. Opt. Lett. 12(3), 031702 (2014).
[Crossref]

Jiang, H.

L. Yao, Y. Sun, and H. Jiang, “Quantitative photoacoustic tomography based on the radiative transfer equation,” Opt. Lett. 34(12), 1765–1767 (2009).
[Crossref] [PubMed]

X. Gu, Y. Xu, and H. Jiang, “Mesh-based enhancement schemes in diffuse optical tomography,” Med. Phys. 30(5), 861–869 (2003).
[Crossref] [PubMed]

Jiang, J.

M. Jia, H. Zhao, J. Li, L. Liu, L. Zhang, J. Jiang, and F. Gao, “Coupling between radiative transport and diffusion approximation for enhanced near-field photon-migration modeling based on transient photon kinetics,” J. Biomed. Opt. 21(5), 050501 (2016).
[Crossref] [PubMed]

Joshi, A.

Kandel, J.

J. Kandel, E. Bossy-Wetzel, F. Radvanyi, M. Klagsbrun, J. Folkman, and D. Hanahan, “Neovascularization is associated with a switch to the export of bFGF in the multistep development of fibrosarcoma,” Cell 66(6), 1095–1104 (1991).
[Crossref] [PubMed]

Klagsbrun, M.

J. Kandel, E. Bossy-Wetzel, F. Radvanyi, M. Klagsbrun, J. Folkman, and D. Hanahan, “Neovascularization is associated with a switch to the export of bFGF in the multistep development of fibrosarcoma,” Cell 66(6), 1095–1104 (1991).
[Crossref] [PubMed]

Klose, A. D.

A. H. Hielscher, A. D. Klose, and K. M. Hanson, “Gradient-based iterative image reconstruction scheme for time-resolved optical tomography,” IEEE Trans. Med. Imaging 18(3), 262–271 (1999).
[Crossref] [PubMed]

Lehrer, N.

B. Yuan, S. A. Burgess, A. Iranmahboob, M. B. Bouchard, N. Lehrer, C. Bordier, and E. M. C. Hillman, “A system for high-resolution depth-resolved optical imaging of fluorescence and absorption contrast,” Rev. Sci. Instrum. 80(4), 043706 (2009).
[Crossref] [PubMed]

Li, J.

M. Jia, H. Zhao, J. Li, L. Liu, L. Zhang, J. Jiang, and F. Gao, “Coupling between radiative transport and diffusion approximation for enhanced near-field photon-migration modeling based on transient photon kinetics,” J. Biomed. Opt. 21(5), 050501 (2016).
[Crossref] [PubMed]

H. Zhao, S. Wang, M. Jia, X. Chen, J. Qi, J. Tian, W. Ma, J. Li, and F. Gao, “A modified laminar optical tomography system with small dip-angle and the initial validation,” Proc. SPIE 9700, 97001B (2016).
[Crossref]

Lin, Z. J.

H. Niu, Z. J. Lin, F. Tian, S. Dhamne, and H. Liu, “Comprehensive investigation of three-dimensional diffuse optical tomography with depth compensation algorithm,” J. Biomed. Opt. 15(4), 046005 (2010).
[Crossref] [PubMed]

Liu, H.

H. Niu, Z. J. Lin, F. Tian, S. Dhamne, and H. Liu, “Comprehensive investigation of three-dimensional diffuse optical tomography with depth compensation algorithm,” J. Biomed. Opt. 15(4), 046005 (2010).
[Crossref] [PubMed]

Liu, J.

C. Gong, J. Liu, L. Chi, H. Huang, J. Fang, and Z. Gong, “GPU accelerated simulations of 3D deterministic particle transport using discrete ordinates method,” J. Comput. Phys. 230(15), 6010–6022 (2011).
[Crossref]

Liu, L.

M. Jia, H. Zhao, J. Li, L. Liu, L. Zhang, J. Jiang, and F. Gao, “Coupling between radiative transport and diffusion approximation for enhanced near-field photon-migration modeling based on transient photon kinetics,” J. Biomed. Opt. 21(5), 050501 (2016).
[Crossref] [PubMed]

Liu, M.

Liu, Q.

Ma, W.

H. Zhao, S. Wang, M. Jia, X. Chen, J. Qi, J. Tian, W. Ma, J. Li, and F. Gao, “A modified laminar optical tomography system with small dip-angle and the initial validation,” Proc. SPIE 9700, 97001B (2016).
[Crossref]

Muldoon, T. J.

Niu, H.

H. Niu, Z. J. Lin, F. Tian, S. Dhamne, and H. Liu, “Comprehensive investigation of three-dimensional diffuse optical tomography with depth compensation algorithm,” J. Biomed. Opt. 15(4), 046005 (2010).
[Crossref] [PubMed]

Ntziachristos, V.

M. Schwarz, A. Buehler, J. Aguirre, and V. Ntziachristos, “Three-dimensional multispectral optoacoustic mesoscopy reveals melanin and blood oxygenation in human skin in vivo,” J. Biophotonics 9(1-2), 55–60 (2016).
[Crossref] [PubMed]

A. Taruttis and V. Ntziachristos, “Advances in real-time multispectral optoacoustic imaging and its applications,” Nat. Photonics 9(4), 219–227 (2015).
[Crossref]

Okawa, S.

Y. Yamada and S. Okawa, “Diffuse optical tomography: present status and its future,” Opt. Rev. 21(3), 185–205 (2014).
[Crossref]

H. Fujii, S. Okawa, Y. Yamada, and Y. Hoshi, “Hybrid model of light propagation in random media based on the time-dependent radiative transfer and diffusion equations,” J. Quant. Spectrosc. Radiat. Transf. 147, 145–154 (2014).
[Crossref]

Piao, D.

S. Gupta, P. K. Yalavarthy, D. Roy, D. Piao, and R. M. Vasu, “Singular value decomposition based computationally efficient algorithm for rapid dynamic near-infrared diffuse optical tomography,” Med. Phys. 36(12), 5559–5567 (2009).
[Crossref] [PubMed]

Pogue, B. W.

Qi, J.

H. Zhao, S. Wang, M. Jia, X. Chen, J. Qi, J. Tian, W. Ma, J. Li, and F. Gao, “A modified laminar optical tomography system with small dip-angle and the initial validation,” Proc. SPIE 9700, 97001B (2016).
[Crossref]

Radvanyi, F.

J. Kandel, E. Bossy-Wetzel, F. Radvanyi, M. Klagsbrun, J. Folkman, and D. Hanahan, “Neovascularization is associated with a switch to the export of bFGF in the multistep development of fibrosarcoma,” Cell 66(6), 1095–1104 (1991).
[Crossref] [PubMed]

Ramanujam, N.

Ratner, D.

Riley, J.

Roy, D.

S. Gupta, P. K. Yalavarthy, D. Roy, D. Piao, and R. M. Vasu, “Singular value decomposition based computationally efficient algorithm for rapid dynamic near-infrared diffuse optical tomography,” Med. Phys. 36(12), 5559–5567 (2009).
[Crossref] [PubMed]

Schotland, J. C.

S. R. Arridge and J. C. Schotland, “Optical tomography: forward and inverse problems,” Inverse Probl. 25(12), 123010 (2009).
[Crossref]

Schwarz, M.

M. Schwarz, A. Buehler, J. Aguirre, and V. Ntziachristos, “Three-dimensional multispectral optoacoustic mesoscopy reveals melanin and blood oxygenation in human skin in vivo,” J. Biophotonics 9(1-2), 55–60 (2016).
[Crossref] [PubMed]

Schweiger, M.

Seo, I.

I. Seo, C. K. Hayakawa, and V. Venugopalan, “Radiative transport in the delta-P1 approximation for semi-infinite turbid media,” Med. Phys. 35(2), 681–693 (2008).
[Crossref] [PubMed]

Sevick-Muraca, E.

Spanier, J.

Sun, Y.

Taruttis, A.

A. Taruttis and V. Ntziachristos, “Advances in real-time multispectral optoacoustic imaging and its applications,” Nat. Photonics 9(4), 219–227 (2015).
[Crossref]

Tian, F.

H. Niu, Z. J. Lin, F. Tian, S. Dhamne, and H. Liu, “Comprehensive investigation of three-dimensional diffuse optical tomography with depth compensation algorithm,” J. Biomed. Opt. 15(4), 046005 (2010).
[Crossref] [PubMed]

Tian, J.

H. Zhao, S. Wang, M. Jia, X. Chen, J. Qi, J. Tian, W. Ma, J. Li, and F. Gao, “A modified laminar optical tomography system with small dip-angle and the initial validation,” Proc. SPIE 9700, 97001B (2016).
[Crossref]

Tromberg, B. J.

Vasu, R. M.

S. Gupta, P. K. Yalavarthy, D. Roy, D. Piao, and R. M. Vasu, “Singular value decomposition based computationally efficient algorithm for rapid dynamic near-infrared diffuse optical tomography,” Med. Phys. 36(12), 5559–5567 (2009).
[Crossref] [PubMed]

Venugopalan, V.

Wan, W.

Wang, S.

H. Zhao, S. Wang, M. Jia, X. Chen, J. Qi, J. Tian, W. Ma, J. Li, and F. Gao, “A modified laminar optical tomography system with small dip-angle and the initial validation,” Proc. SPIE 9700, 97001B (2016).
[Crossref]

Wang, X.

Wu, X.

Xu, Y.

X. Gu, Y. Xu, and H. Jiang, “Mesh-based enhancement schemes in diffuse optical tomography,” Med. Phys. 30(5), 861–869 (2003).
[Crossref] [PubMed]

Yalavarthy, P. K.

S. Gupta, P. K. Yalavarthy, D. Roy, D. Piao, and R. M. Vasu, “Singular value decomposition based computationally efficient algorithm for rapid dynamic near-infrared diffuse optical tomography,” Med. Phys. 36(12), 5559–5567 (2009).
[Crossref] [PubMed]

M. E. Eames, B. W. Pogue, P. K. Yalavarthy, and H. Dehghani, “An efficient Jacobian reduction method for diffuse optical image reconstruction,” Opt. Express 15(24), 15908–15919 (2007).
[Crossref] [PubMed]

Yamada, Y.

H. Fujii, S. Okawa, Y. Yamada, and Y. Hoshi, “Hybrid model of light propagation in random media based on the time-dependent radiative transfer and diffusion equations,” J. Quant. Spectrosc. Radiat. Transf. 147, 145–154 (2014).
[Crossref]

Y. Yamada and S. Okawa, “Diffuse optical tomography: present status and its future,” Opt. Rev. 21(3), 185–205 (2014).
[Crossref]

Yao, L.

Yi, X.

You, J. S.

Yuan, B.

B. Yuan, S. A. Burgess, A. Iranmahboob, M. B. Bouchard, N. Lehrer, C. Bordier, and E. M. C. Hillman, “A system for high-resolution depth-resolved optical imaging of fluorescence and absorption contrast,” Rev. Sci. Instrum. 80(4), 043706 (2009).
[Crossref] [PubMed]

Zhang, L.

M. Jia, H. Zhao, J. Li, L. Liu, L. Zhang, J. Jiang, and F. Gao, “Coupling between radiative transport and diffusion approximation for enhanced near-field photon-migration modeling based on transient photon kinetics,” J. Biomed. Opt. 21(5), 050501 (2016).
[Crossref] [PubMed]

Zhao, H.

M. Jia, H. Zhao, J. Li, L. Liu, L. Zhang, J. Jiang, and F. Gao, “Coupling between radiative transport and diffusion approximation for enhanced near-field photon-migration modeling based on transient photon kinetics,” J. Biomed. Opt. 21(5), 050501 (2016).
[Crossref] [PubMed]

H. Zhao, S. Wang, M. Jia, X. Chen, J. Qi, J. Tian, W. Ma, J. Li, and F. Gao, “A modified laminar optical tomography system with small dip-angle and the initial validation,” Proc. SPIE 9700, 97001B (2016).
[Crossref]

M. Jia, S. Cui, X. Chen, M. Liu, X. Zhou, H. Zhao, and F. Gao, “Image reconstruction method for laminar optical tomography with only a single Monte-Carlo simulation,” Chin. Opt. Lett. 12(3), 031702 (2014).
[Crossref]

X. Yi, X. Wang, W. Chen, W. Wan, H. Zhao, and F. Gao, “Full domain-decomposition scheme for diffuse optical tomography of large-sized tissues with a combined CPU and GPU parallelization,” Appl. Opt. 53(13), 2754–2765 (2014).
[Crossref] [PubMed]

Zhou, X.

Appl. Opt. (2)

Biomed. Opt. Express (2)

Cell (1)

J. Kandel, E. Bossy-Wetzel, F. Radvanyi, M. Klagsbrun, J. Folkman, and D. Hanahan, “Neovascularization is associated with a switch to the export of bFGF in the multistep development of fibrosarcoma,” Cell 66(6), 1095–1104 (1991).
[Crossref] [PubMed]

Chin. Opt. Lett. (1)

IEEE Trans. Med. Imaging (1)

A. H. Hielscher, A. D. Klose, and K. M. Hanson, “Gradient-based iterative image reconstruction scheme for time-resolved optical tomography,” IEEE Trans. Med. Imaging 18(3), 262–271 (1999).
[Crossref] [PubMed]

Inverse Probl. (1)

S. R. Arridge and J. C. Schotland, “Optical tomography: forward and inverse problems,” Inverse Probl. 25(12), 123010 (2009).
[Crossref]

J. Biomed. Opt. (2)

M. Jia, H. Zhao, J. Li, L. Liu, L. Zhang, J. Jiang, and F. Gao, “Coupling between radiative transport and diffusion approximation for enhanced near-field photon-migration modeling based on transient photon kinetics,” J. Biomed. Opt. 21(5), 050501 (2016).
[Crossref] [PubMed]

H. Niu, Z. J. Lin, F. Tian, S. Dhamne, and H. Liu, “Comprehensive investigation of three-dimensional diffuse optical tomography with depth compensation algorithm,” J. Biomed. Opt. 15(4), 046005 (2010).
[Crossref] [PubMed]

J. Biophotonics (1)

M. Schwarz, A. Buehler, J. Aguirre, and V. Ntziachristos, “Three-dimensional multispectral optoacoustic mesoscopy reveals melanin and blood oxygenation in human skin in vivo,” J. Biophotonics 9(1-2), 55–60 (2016).
[Crossref] [PubMed]

J. Comput. Phys. (1)

C. Gong, J. Liu, L. Chi, H. Huang, J. Fang, and Z. Gong, “GPU accelerated simulations of 3D deterministic particle transport using discrete ordinates method,” J. Comput. Phys. 230(15), 6010–6022 (2011).
[Crossref]

J. Opt. Soc. Am. A (1)

J. Quant. Spectrosc. Radiat. Transf. (1)

H. Fujii, S. Okawa, Y. Yamada, and Y. Hoshi, “Hybrid model of light propagation in random media based on the time-dependent radiative transfer and diffusion equations,” J. Quant. Spectrosc. Radiat. Transf. 147, 145–154 (2014).
[Crossref]

Med. Phys. (3)

X. Gu, Y. Xu, and H. Jiang, “Mesh-based enhancement schemes in diffuse optical tomography,” Med. Phys. 30(5), 861–869 (2003).
[Crossref] [PubMed]

S. Gupta, P. K. Yalavarthy, D. Roy, D. Piao, and R. M. Vasu, “Singular value decomposition based computationally efficient algorithm for rapid dynamic near-infrared diffuse optical tomography,” Med. Phys. 36(12), 5559–5567 (2009).
[Crossref] [PubMed]

I. Seo, C. K. Hayakawa, and V. Venugopalan, “Radiative transport in the delta-P1 approximation for semi-infinite turbid media,” Med. Phys. 35(2), 681–693 (2008).
[Crossref] [PubMed]

Nat. Photonics (1)

A. Taruttis and V. Ntziachristos, “Advances in real-time multispectral optoacoustic imaging and its applications,” Nat. Photonics 9(4), 219–227 (2015).
[Crossref]

Opt. Express (4)

Opt. Lett. (4)

Opt. Rev. (1)

Y. Yamada and S. Okawa, “Diffuse optical tomography: present status and its future,” Opt. Rev. 21(3), 185–205 (2014).
[Crossref]

Phys. Med. Biol. (1)

S. L. Jacques, “Optical properties of biological tissues: a review,” Phys. Med. Biol. 58(11), R37–R61 (2013).
[Crossref] [PubMed]

Proc. SPIE (2)

H. Zhao, S. Wang, M. Jia, X. Chen, J. Qi, J. Tian, W. Ma, J. Li, and F. Gao, “A modified laminar optical tomography system with small dip-angle and the initial validation,” Proc. SPIE 9700, 97001B (2016).
[Crossref]

E. M. Hillman, H. Dehghani, J. C. Hebden, S. R. Arridge, M. Schweiger, and D. T. Delpy, “Differential imaging in heterogeneous media: limitations of linearization assumptions in optical tomography,” Proc. SPIE 4250, 327–338 (2001).
[Crossref]

Rev. Sci. Instrum. (1)

B. Yuan, S. A. Burgess, A. Iranmahboob, M. B. Bouchard, N. Lehrer, C. Bordier, and E. M. C. Hillman, “A system for high-resolution depth-resolved optical imaging of fluorescence and absorption contrast,” Rev. Sci. Instrum. 80(4), 043706 (2009).
[Crossref] [PubMed]

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T. Papadopoulo and M.I. A. Lourakis, “Estimating the Jacobian of the Singular Value Decomposition: Theory and Applications,” Research Report 3961, INRIA Sophia-Antipolis, June 2000.

G. W. Stewart and J.-G. Sun, Matrix Perturbation Theory (Academic, 1990).

M. E. Wall, A. Rechtsteinner, and L. M. Rocha, “Singular value decomposition and principal component analysis,” in A Practical Approach to Microarray Data Analysis, D. P. Berrar, W. Dubitzky, and M. Granzow ed. (Kluwer, Norwell, 2003).

C. Musco and C. Musco, “Randomized block krylov methods for stronger and faster approximate singular value decomposition,” in Proceedings of Neural Information Processing Systems 28 (NIPS, 2015), pp. 1396–1404.

A. Liutkus, “Randomized SVD,” MATLAB Central File Exchange, 2014.

V. Vijayan, “Fast SVD and PCA,” MATLAB Central File Exchange.

D. A. Boas, C. Pitris, and N. Ramanujam, Handbook of Biomedical Optics (Taylor and Francis, 2010).

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Figures (10)

Fig. 1
Fig. 1 Tissue model for generating simulated data.
Fig. 2
Fig. 2 Reconstructed images and the corresponding Z-profiles along the white dashed lines with the four schemes, for (a) TAC = 2, (b) TAC = 3, and (c) TAC = 5, respectively, with a fixed target depth of 0.9mm. The black dotted boxes indicate the original targets.
Fig. 3
Fig. 3 Reconstructed images and the corresponding Z-profiles along the white dashed lines with the four schemes, for the target depths of (a) 0.4mm, (b) 0.9mm, and (c) 1.2mm, respectively. The black dotted boxes indicate the original targets.
Fig. 4
Fig. 4 Reconstructed slices along y = 4.165 mm and the corresponding Z-profiles along the white dashed lines, with the four schemes for a fixed target depth of 0.9 mm, when SNRs of the simulated data are (a) 10 dB, (b) 20 dB, and (c) 30 dB, respectively. The black dotted lines indicate the edges of original targets.
Fig. 5
Fig. 5 Schematic of the cdaLOT system.
Fig. 6
Fig. 6 Phantom experimental results. (a) Reconstructed μ a images for target depths of 0.4mm (upper row) and 1mm (lower row), with the four schemes from left to right columns, respectively. (b)-(c) Corresponding profiles of the reconstructed μ a images along the white dashed lines marked in the above images for target depths of 0.4mm and 1mm, respectively.
Fig. 7
Fig. 7 Imagings of the murine cancerous region: (a) photograph and (b) cdaLOT raw images.
Fig. 8
Fig. 8 In-vivo experimental results. (a) Reconstructed images sliced at z = 0.2mm, z = 0.5mm, z = 0.71mm, z = 0.9mm, and x = 4.1mm, from left to right columns, respectively, with the four reconstruction schemes. (b) Corresponding Z-profiles along the white dashed lines marked in the above Y-Z slices. The red dashed line indicates z-position of the tumor centroid.
Fig. 9
Fig. 9 Computation time per iteration VS. size of (J).
Fig. 10
Fig. 10 (a) Reconstructed μ a images along y = 4.165mm with the proposed, traditional, and improved approaches using the rSVD and fSVD, respectively, for TAC = 2, SNR = 10dB, and a fixed target depth of 0.9 mm. (b) Corresponding Z-profiles along the white dashed lines marked in the above X-Z slices.

Tables (5)

Tables Icon

Table 1 Comparisons among the reconstructions for three TACs

Tables Icon

Table 2 Comparisons among the reconstructions for different target depths

Tables Icon

Table 3 Comparisons among the reconstructions for noise robustness

Tables Icon

Table 4 Comparisons among the reconstructions for different target depths

Tables Icon

Table 5 Comparisons among the reconstructions for different target depths. The numbers bracketed in Table 5 are the corresponding 1-iteration results.

Equations (17)

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

δ μ a ( k ) = [ ( J ( k ) ) T J ( k ) + α ( k ) I ] 1 ( J ( k ) ) T b ( k ) ,
δ μ a ( k ) = V ( k ) Λ ( k ) ( Λ ( k ) ) 2 + α ( k ) I ( U ( k ) ) T b ( k ) ,
Θ ( k+1 ) =δ Θ ( k ) + Θ ( k ) ,
δ Θ i,j ( k ) n=1 M m=1 N l=1 N Θ i,j ( k ) J m,l ( k ) J m,l ( k ) μ a,n ( k ) δ μ a,n ( k ) .
F m ( k+1 ) = F m ( k ) n=1 N e s m,n ( k ) δ μ a,n ( k ) ,
J m,n ( k+1 ) = J m,n ( k ) e s m,n ( k ) δ μ a,n ( k ) .
δ Θ i,j ( k ) m=1 M n=1 N Θ i,j ( k ) J m,n ( k ) δ J m,n ( k ) ,
{ Λ i ( k ) J m,n ( k ) = u m,i ( k ) v n,i ( k ) U ( k ) J m,n ( k ) = U ( k ) ϕ ( k ) ( m,n ) V ( k ) J m,n ( k ) = V ( k ) φ ( k ) ( m,n ) ,
[ Λ j ( k ) Λ i ( k ) Λ i ( k ) Λ j ( k ) ][ ϕ i,j ( k ) ( m,n ) φ i,j ( k ) ( m,n ) ]=[ u m,i ( k ) v n,j ( k ) u m,j ( k ) v n,i ( k ) ].
{ Λ ( k+1 ) =diag( Ω ( k ) )+ Λ ( k ) U ( k+1 ) = U ( k ) [ ξ ( k ) Ω ( k ) η ( k ) ( Ω ( k ) ) T +I ] V ( k+1 ) = V ( k ) [ ξ ( k ) ( Ω ( k ) ) T η ( k ) Ω ( k ) +I ] ,
Ω ( k ) = ( U ( k ) ) T δ J ( k ) V ( k ) ,
[ ξ i,j ( k ) η i,j ( k ) ]= [ ( Λ i (k) ) 2 + ( Λ j (k) ) 2 + α (k) -2 Λ i (k) Λ j (k) ] [ ( Λ i (k) ) 2 + ( Λ j (k) ) 2 + α (k) ] 2 -4 ( Λ i (k) Λ j (k) ) 2 [ Λ i (k) Λ j (k) Λ j (k) Λ i (k) ]( 1 Δ ij ),
J m,n ( k ) = lim δ μ a,n ( k ) 0 F m ( k+1 ) F m ( k ) δ μ a,n ( k ) ,
J m,n ( k ) = lim δ μ a,n ( k ) 0 F m ( k ) e s m,n ( k ) δ μ a,n ( k ) F m ( k ) δ μ a,n ( k ) = F m ( k ) s m,n ( k ) .
J m,n ( k+1 ) = F m ( k+1 ) μ a,n | μ a,n ( k ) ,
J m,n ( k+1 ) = s m,n ( k ) F m ( k ) e s m,n δ μ a,n ( k )
J m,n ( k+1 ) = J m,n ( k ) e s m,n ( k ) δ μ a,n ( k ) .

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