Abstract

Bioluminescence imaging (BLI) is a non-contact, optical imaging technique based on measurement of emitted light due to an internal source, which is then often directly related to cellular activity. It is widely used in pre-clinical small animal imaging studies to assess the progression of diseases such as cancer, aiding in the development of new treatments and therapies. For many applications, the quantitative assessment of accurate cellular activity and spatial distribution is desirable as it would enable direct monitoring for prognostic evaluation. This requires quantitative spatially-resolved measurements of bioluminescence source strength inside the animal to be obtained from BLI images. This is the goal of bioluminescence tomography (BLT) in which a model of light propagation through tissue is combined with an optimization algorithm to reconstruct a map of the underlying source distribution. As most models consider only the propagation of light from internal sources to the animal skin surface, an additional challenge is accounting for the light propagation from the skin to the optical detector (e.g. camera). Existing approaches typically use a model of the imaging system optics (e.g. ray-tracing, analytical optical models) or approximate corrections derived from calibration measurements. However, these approaches are typically computationally intensive or of limited accuracy. In this work, a new approach is presented in which, rather than directly using BLI images acquired at several wavelengths, the spectral derivative of that data (difference of BLI images at adjacent wavelengths) is used in BLT. As light at similar wavelengths encounters a near-identical system response (path through the optics etc.) this eliminates the need for additional corrections or system models. This approach is applied to BLT with simulated and experimental phantom data and shown that the error in reconstructed source intensity is reduced from 49% to 4%. Qualitatively, the accuracy of source localization is improved in both simulated and experimental data, as compared to reconstruction using the standard approach. The outlined algorithm can widely be adapted to all commercial systems without any further technological modifications.

Published by The Optical Society under the terms of the Creative Commons Attribution 4.0 License. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.

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References

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    [Crossref] [PubMed]

2018 (1)

2017 (1)

Y. Gao, K. Wang, S. Jiang, Y. Liu, T. Ai, and J. Tian, “Bioluminescence tomography based on gaussian weighted laplace prior regularization for in vivo morphological imaging of glioma,” IEEE Trans. Med. Imaging 36(11), 2343–2354 (2017).
[Crossref] [PubMed]

2016 (2)

B. Zhang, I. Iordachita, J. W. Wong, and K. K. H. Wang, “Multi-projection bioluminescence tomography guided system for small animal radiation research platform (SARRP),” Proc. SPIE 9701, 97010J (2016).

J. A. Guggenheim, I. Bargigia, A. Farina, A. Pifferi, and H. Dehghani, “Time resolved diffuse optical spectroscopy with geometrically accurate models for bulk parameter recovery,” Biomed. Opt. Express 7(9), 3784–3794 (2016).
[Crossref] [PubMed]

2015 (1)

S. L. Taylor, S. K. G. Mason, S. L. Glinton, M. Cobbold, and H. Dehghani, “Accounting for filter bandwidth improves the quantitative accuracy of bioluminescence tomography,” J. Biomed. Opt. 20(9), 096001 (2015).
[Crossref] [PubMed]

2014 (2)

C. Darne, Y. Lu, and E. M. Sevick-Muraca, “Small animal fluorescence and bioluminescence tomography: a review of approaches, algorithms and technology update,” Phys. Med. Biol. 59(1), R1–R64 (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]

2013 (3)

2012 (1)

2011 (1)

N. Andreu, A. Zelmer, and S. Wiles, “Noninvasive biophotonic imaging for studies of infectious disease,” FEMS Microbiol. Rev. 35(2), 360–394 (2011).
[Crossref] [PubMed]

2010 (3)

K. O’Neill, S. K. Lyons, W. M. Gallagher, K. M. Curran, and A. T. Byrne, “Bioluminescent imaging: a critical tool in pre-clinical oncology research,” J. Pathol. 220(3), 317–327 (2010).
[PubMed]

H. Dehghani, F. Leblond, B. W. Pogue, and F. Chauchard, “Application of spectral derivative data in visible and near-infrared spectroscopy,” Phys. Med. Biol. 55(12), 3381–3399 (2010).
[Crossref] [PubMed]

X. Chen, X. Gao, X. Qu, D. Chen, X. Ma, J. Liang, and J. Tian, “Generalized free-space diffuse photon transport model based on the influence analysis of a camera lens diaphragm,” Appl. Opt. 49(29), 5654–5664 (2010).
[Crossref] [PubMed]

2008 (1)

H. Dehghani, S. C. Davis, and B. W. Pogue, “Spectrally resolved bioluminescence tomography using the reciprocity approach,” Med. Phys. 35(11), 4863–4871 (2008).
[Crossref] [PubMed]

2007 (1)

C. Kuo, O. Coquoz, T. L. Troy, H. Xu, and B. W. Rice, “Three-dimensional reconstruction of in vivo bioluminescent sources based on multispectral imaging,” J. Biomed. Opt. 12(2), 024007 (2007).
[Crossref] [PubMed]

2005 (3)

A. Soubret, J. Ripoll, and V. Ntziachristos, “Accuracy of fluorescent tomography in the presence of heterogeneities: study of the normalized Born ratio,” IEEE Trans. Med. Imaging 24(10), 1377–1386 (2005).
[Crossref] [PubMed]

A. P. Gibson, J. C. Hebden, and S. R. Arridge, “Recent advances in diffuse optical imaging,” Phys. Med. Biol. 50(4), R1–R43 (2005).
[Crossref] [PubMed]

H. Xu, B. W. Pogue, R. Springett, and H. Dehghani, “Spectral derivative based image reconstruction provides inherent insensitivity to coupling and geometric errors,” Opt. Lett. 30(21), 2912–2914 (2005).
[Crossref] [PubMed]

2004 (2)

2003 (1)

J. Ripoll, R. B. Schulz, and V. Ntziachristos, “Free-space propagation of diffuse light: theory and experiments,” Phys. Rev. Lett. 91(10), 103901 (2003).
[Crossref] [PubMed]

1999 (1)

S. R. Arridge, “Optical tomography in medical imaging,” Inverse Probl. 15(2), R41–R93 (1999).
[Crossref]

1995 (1)

Ai, T.

Y. Gao, K. Wang, S. Jiang, Y. Liu, T. Ai, and J. Tian, “Bioluminescence tomography based on gaussian weighted laplace prior regularization for in vivo morphological imaging of glioma,” IEEE Trans. Med. Imaging 36(11), 2343–2354 (2017).
[Crossref] [PubMed]

Andreu, N.

N. Andreu, A. Zelmer, and S. Wiles, “Noninvasive biophotonic imaging for studies of infectious disease,” FEMS Microbiol. Rev. 35(2), 360–394 (2011).
[Crossref] [PubMed]

Arridge, S. R.

A. P. Gibson, J. C. Hebden, and S. R. Arridge, “Recent advances in diffuse optical imaging,” Phys. Med. Biol. 50(4), R1–R43 (2005).
[Crossref] [PubMed]

S. R. Arridge, “Optical tomography in medical imaging,” Inverse Probl. 15(2), R41–R93 (1999).
[Crossref]

S. R. Arridge and M. Schweiger, “Photon-measurement density functions. Part 2: Finite-element-method calculations,” Appl. Opt. 34(34), 8026–8037 (1995).
[Crossref] [PubMed]

Bargigia, I.

Basevi, H. R. A.

Byrne, A. T.

K. O’Neill, S. K. Lyons, W. M. Gallagher, K. M. Curran, and A. T. Byrne, “Bioluminescent imaging: a critical tool in pre-clinical oncology research,” J. Pathol. 220(3), 317–327 (2010).
[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: algorithms for numerical model and image reconstruction algorithms,” Commun. Numer. Methods Eng. (2008).

Chauchard, F.

H. Dehghani, F. Leblond, B. W. Pogue, and F. Chauchard, “Application of spectral derivative data in visible and near-infrared spectroscopy,” Phys. Med. Biol. 55(12), 3381–3399 (2010).
[Crossref] [PubMed]

Chen, D.

Chen, X.

Cobbold, M.

S. L. Taylor, S. K. G. Mason, S. L. Glinton, M. Cobbold, and H. Dehghani, “Accounting for filter bandwidth improves the quantitative accuracy of bioluminescence tomography,” J. Biomed. Opt. 20(9), 096001 (2015).
[Crossref] [PubMed]

Coquoz, O.

C. Kuo, O. Coquoz, T. L. Troy, H. Xu, and B. W. Rice, “Three-dimensional reconstruction of in vivo bioluminescent sources based on multispectral imaging,” J. Biomed. Opt. 12(2), 024007 (2007).
[Crossref] [PubMed]

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]

Curran, K. M.

K. O’Neill, S. K. Lyons, W. M. Gallagher, K. M. Curran, and A. T. Byrne, “Bioluminescent imaging: a critical tool in pre-clinical oncology research,” J. Pathol. 220(3), 317–327 (2010).
[PubMed]

Darne, C.

C. Darne, Y. Lu, and E. M. Sevick-Muraca, “Small animal fluorescence and bioluminescence tomography: a review of approaches, algorithms and technology update,” Phys. Med. Biol. 59(1), R1–R64 (2014).
[Crossref] [PubMed]

Davis, S. C.

H. Dehghani, S. C. Davis, and B. W. Pogue, “Spectrally resolved bioluminescence tomography using the reciprocity approach,” Med. Phys. 35(11), 4863–4871 (2008).
[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: algorithms for numerical model and image reconstruction algorithms,” Commun. Numer. Methods Eng. (2008).

Dehghani, H.

B. Jayet, S. P. Morgan, and H. Dehghani, “Incorporation of an ultrasound and model guided permissible region improves quantitative source recovery in bioluminescence tomography,” Biomed. Opt. Express 9(3), 1360–1374 (2018).
[Crossref] [PubMed]

J. A. Guggenheim, I. Bargigia, A. Farina, A. Pifferi, and H. Dehghani, “Time resolved diffuse optical spectroscopy with geometrically accurate models for bulk parameter recovery,” Biomed. Opt. Express 7(9), 3784–3794 (2016).
[Crossref] [PubMed]

S. L. Taylor, S. K. G. Mason, S. L. Glinton, M. Cobbold, and H. Dehghani, “Accounting for filter bandwidth improves the quantitative accuracy of bioluminescence tomography,” J. Biomed. Opt. 20(9), 096001 (2015).
[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]

J. A. Guggenheim, H. R. A. Basevi, J. Frampton, I. B. Styles, and H. Dehghani, “Multi-modal molecular diffuse optical tomography system for small animal imaging,” Meas. Sci. Technol. 24(10), 105405 (2013).
[Crossref] [PubMed]

J. A. Guggenheim, H. R. A. Basevi, I. B. Styles, J. Frampton, and H. Dehghani, “Quantitative surface radiance mapping using multiview images of light-emitting turbid media,” J. Opt. Soc. Am. A 30(12), 2572–2584 (2013).
[Crossref] [PubMed]

H. R. A. Basevi, K. M. Tichauer, F. Leblond, H. Dehghani, J. A. Guggenheim, R. W. Holt, and I. B. Styles, “Compressive sensing based reconstruction in bioluminescence tomography improves image resolution and robustness to noise,” Biomed. Opt. Express 3(9), 2131–2141 (2012).
[Crossref] [PubMed]

H. Dehghani, F. Leblond, B. W. Pogue, and F. Chauchard, “Application of spectral derivative data in visible and near-infrared spectroscopy,” Phys. Med. Biol. 55(12), 3381–3399 (2010).
[Crossref] [PubMed]

H. Dehghani, S. C. Davis, and B. W. Pogue, “Spectrally resolved bioluminescence tomography using the reciprocity approach,” Med. Phys. 35(11), 4863–4871 (2008).
[Crossref] [PubMed]

H. Xu, B. W. Pogue, R. Springett, and H. Dehghani, “Spectral derivative based image reconstruction provides inherent insensitivity to coupling and geometric errors,” Opt. Lett. 30(21), 2912–2914 (2005).
[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: algorithms for numerical model and image reconstruction algorithms,” Commun. Numer. Methods Eng. (2008).

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: algorithms for numerical model and image reconstruction algorithms,” Commun. Numer. Methods Eng. (2008).

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]

Farina, A.

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]

Frampton, J.

J. A. Guggenheim, H. R. A. Basevi, I. B. Styles, J. Frampton, and H. Dehghani, “Quantitative surface radiance mapping using multiview images of light-emitting turbid media,” J. Opt. Soc. Am. A 30(12), 2572–2584 (2013).
[Crossref] [PubMed]

J. A. Guggenheim, H. R. A. Basevi, J. Frampton, I. B. Styles, and H. Dehghani, “Multi-modal molecular diffuse optical tomography system for small animal imaging,” Meas. Sci. Technol. 24(10), 105405 (2013).
[Crossref] [PubMed]

Gallagher, W. M.

K. O’Neill, S. K. Lyons, W. M. Gallagher, K. M. Curran, and A. T. Byrne, “Bioluminescent imaging: a critical tool in pre-clinical oncology research,” J. Pathol. 220(3), 317–327 (2010).
[PubMed]

Gao, X.

Gao, Y.

Y. Gao, K. Wang, S. Jiang, Y. Liu, T. Ai, and J. Tian, “Bioluminescence tomography based on gaussian weighted laplace prior regularization for in vivo morphological imaging of glioma,” IEEE Trans. Med. Imaging 36(11), 2343–2354 (2017).
[Crossref] [PubMed]

Gibson, A. P.

A. P. Gibson, J. C. Hebden, and S. R. Arridge, “Recent advances in diffuse optical imaging,” Phys. Med. Biol. 50(4), R1–R43 (2005).
[Crossref] [PubMed]

Glinton, S. L.

S. L. Taylor, S. K. G. Mason, S. L. Glinton, M. Cobbold, and H. Dehghani, “Accounting for filter bandwidth improves the quantitative accuracy of bioluminescence tomography,” J. Biomed. Opt. 20(9), 096001 (2015).
[Crossref] [PubMed]

Gu, X.

Guggenheim, J. A.

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]

Hebden, J. C.

A. P. Gibson, J. C. Hebden, and S. R. Arridge, “Recent advances in diffuse optical imaging,” Phys. Med. Biol. 50(4), R1–R43 (2005).
[Crossref] [PubMed]

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]

Holt, R. W.

Iordachita, I.

B. Zhang, I. Iordachita, J. W. Wong, and K. K. H. Wang, “Multi-projection bioluminescence tomography guided system for small animal radiation research platform (SARRP),” Proc. SPIE 9701, 97010J (2016).

Jayet, B.

Jiang, H.

Jiang, M.

G. Wang, Y. Li, and M. Jiang, “Uniqueness theorems in bioluminescence tomography,” Med. Phys. 31(8), 2289–2299 (2004).
[Crossref] [PubMed]

Jiang, S.

Y. Gao, K. Wang, S. Jiang, Y. Liu, T. Ai, and J. Tian, “Bioluminescence tomography based on gaussian weighted laplace prior regularization for in vivo morphological imaging of glioma,” IEEE Trans. Med. Imaging 36(11), 2343–2354 (2017).
[Crossref] [PubMed]

Kuo, C.

C. Kuo, O. Coquoz, T. L. Troy, H. Xu, and B. W. Rice, “Three-dimensional reconstruction of in vivo bioluminescent sources based on multispectral imaging,” J. Biomed. Opt. 12(2), 024007 (2007).
[Crossref] [PubMed]

Larcom, L.

Leblond, F.

Li, Y.

G. Wang, Y. Li, and M. Jiang, “Uniqueness theorems in bioluminescence tomography,” Med. Phys. 31(8), 2289–2299 (2004).
[Crossref] [PubMed]

Liang, J.

Liu, Y.

Y. Gao, K. Wang, S. Jiang, Y. Liu, T. Ai, and J. Tian, “Bioluminescence tomography based on gaussian weighted laplace prior regularization for in vivo morphological imaging of glioma,” IEEE Trans. Med. Imaging 36(11), 2343–2354 (2017).
[Crossref] [PubMed]

Lu, Y.

C. Darne, Y. Lu, and E. M. Sevick-Muraca, “Small animal fluorescence and bioluminescence tomography: a review of approaches, algorithms and technology update,” Phys. Med. Biol. 59(1), R1–R64 (2014).
[Crossref] [PubMed]

Lyons, S. K.

K. O’Neill, S. K. Lyons, W. M. Gallagher, K. M. Curran, and A. T. Byrne, “Bioluminescent imaging: a critical tool in pre-clinical oncology research,” J. Pathol. 220(3), 317–327 (2010).
[PubMed]

Ma, X.

Mason, S. K. G.

S. L. Taylor, S. K. G. Mason, S. L. Glinton, M. Cobbold, and H. Dehghani, “Accounting for filter bandwidth improves the quantitative accuracy of bioluminescence tomography,” J. Biomed. Opt. 20(9), 096001 (2015).
[Crossref] [PubMed]

Mohajerani, P.

Morgan, S. P.

Ntziachristos, V.

P. Mohajerani and V. Ntziachristos, “Compression of Born ratio for fluorescence molecular tomography/X-ray computed tomography hybrid imaging: methodology and in vivo validation,” Opt. Lett. 38(13), 2324–2326 (2013).
[Crossref] [PubMed]

A. Soubret, J. Ripoll, and V. Ntziachristos, “Accuracy of fluorescent tomography in the presence of heterogeneities: study of the normalized Born ratio,” IEEE Trans. Med. Imaging 24(10), 1377–1386 (2005).
[Crossref] [PubMed]

J. Ripoll, R. B. Schulz, and V. Ntziachristos, “Free-space propagation of diffuse light: theory and experiments,” Phys. Rev. Lett. 91(10), 103901 (2003).
[Crossref] [PubMed]

O’Neill, K.

K. O’Neill, S. K. Lyons, W. M. Gallagher, K. M. Curran, and A. T. Byrne, “Bioluminescent imaging: a critical tool in pre-clinical oncology research,” J. Pathol. 220(3), 317–327 (2010).
[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: algorithms for numerical model and image reconstruction algorithms,” Commun. Numer. Methods Eng. (2008).

Pifferi, A.

Pogue, B. W.

H. Dehghani, F. Leblond, B. W. Pogue, and F. Chauchard, “Application of spectral derivative data in visible and near-infrared spectroscopy,” Phys. Med. Biol. 55(12), 3381–3399 (2010).
[Crossref] [PubMed]

H. Dehghani, S. C. Davis, and B. W. Pogue, “Spectrally resolved bioluminescence tomography using the reciprocity approach,” Med. Phys. 35(11), 4863–4871 (2008).
[Crossref] [PubMed]

H. Xu, B. W. Pogue, R. Springett, and H. Dehghani, “Spectral derivative based image reconstruction provides inherent insensitivity to coupling and geometric errors,” Opt. Lett. 30(21), 2912–2914 (2005).
[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: algorithms for numerical model and image reconstruction algorithms,” Commun. Numer. Methods Eng. (2008).

Qu, X.

Rice, B. W.

C. Kuo, O. Coquoz, T. L. Troy, H. Xu, and B. W. Rice, “Three-dimensional reconstruction of in vivo bioluminescent sources based on multispectral imaging,” J. Biomed. Opt. 12(2), 024007 (2007).
[Crossref] [PubMed]

Ripoll, J.

A. Soubret, J. Ripoll, and V. Ntziachristos, “Accuracy of fluorescent tomography in the presence of heterogeneities: study of the normalized Born ratio,” IEEE Trans. Med. Imaging 24(10), 1377–1386 (2005).
[Crossref] [PubMed]

J. Ripoll, R. B. Schulz, and V. Ntziachristos, “Free-space propagation of diffuse light: theory and experiments,” Phys. Rev. Lett. 91(10), 103901 (2003).
[Crossref] [PubMed]

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]

Schulz, R. B.

J. Ripoll, R. B. Schulz, and V. Ntziachristos, “Free-space propagation of diffuse light: theory and experiments,” Phys. Rev. Lett. 91(10), 103901 (2003).
[Crossref] [PubMed]

Schweiger, M.

Sevick-Muraca, E. M.

C. Darne, Y. Lu, and E. M. Sevick-Muraca, “Small animal fluorescence and bioluminescence tomography: a review of approaches, algorithms and technology update,” Phys. Med. Biol. 59(1), R1–R64 (2014).
[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]

Soubret, A.

A. Soubret, J. Ripoll, and V. Ntziachristos, “Accuracy of fluorescent tomography in the presence of heterogeneities: study of the normalized Born ratio,” IEEE Trans. Med. Imaging 24(10), 1377–1386 (2005).
[Crossref] [PubMed]

Springett, R.

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: algorithms for numerical model and image reconstruction algorithms,” Commun. Numer. Methods Eng. (2008).

Styles, I. B.

Taylor, S. L.

S. L. Taylor, S. K. G. Mason, S. L. Glinton, M. Cobbold, and H. Dehghani, “Accounting for filter bandwidth improves the quantitative accuracy of bioluminescence tomography,” J. Biomed. Opt. 20(9), 096001 (2015).
[Crossref] [PubMed]

Tian, J.

Y. Gao, K. Wang, S. Jiang, Y. Liu, T. Ai, and J. Tian, “Bioluminescence tomography based on gaussian weighted laplace prior regularization for in vivo morphological imaging of glioma,” IEEE Trans. Med. Imaging 36(11), 2343–2354 (2017).
[Crossref] [PubMed]

X. Chen, X. Gao, X. Qu, D. Chen, X. Ma, J. Liang, and J. Tian, “Generalized free-space diffuse photon transport model based on the influence analysis of a camera lens diaphragm,” Appl. Opt. 49(29), 5654–5664 (2010).
[Crossref] [PubMed]

Tichauer, K. M.

Troy, T. L.

C. Kuo, O. Coquoz, T. L. Troy, H. Xu, and B. W. Rice, “Three-dimensional reconstruction of in vivo bioluminescent sources based on multispectral imaging,” J. Biomed. Opt. 12(2), 024007 (2007).
[Crossref] [PubMed]

Wang, G.

G. Wang, Y. Li, and M. Jiang, “Uniqueness theorems in bioluminescence tomography,” Med. Phys. 31(8), 2289–2299 (2004).
[Crossref] [PubMed]

Wang, K.

Y. Gao, K. Wang, S. Jiang, Y. Liu, T. Ai, and J. Tian, “Bioluminescence tomography based on gaussian weighted laplace prior regularization for in vivo morphological imaging of glioma,” IEEE Trans. Med. Imaging 36(11), 2343–2354 (2017).
[Crossref] [PubMed]

Wang, K. K. H.

B. Zhang, I. Iordachita, J. W. Wong, and K. K. H. Wang, “Multi-projection bioluminescence tomography guided system for small animal radiation research platform (SARRP),” Proc. SPIE 9701, 97010J (2016).

Wiles, S.

N. Andreu, A. Zelmer, and S. Wiles, “Noninvasive biophotonic imaging for studies of infectious disease,” FEMS Microbiol. Rev. 35(2), 360–394 (2011).
[Crossref] [PubMed]

Wong, J. W.

B. Zhang, I. Iordachita, J. W. Wong, and K. K. H. Wang, “Multi-projection bioluminescence tomography guided system for small animal radiation research platform (SARRP),” Proc. SPIE 9701, 97010J (2016).

Xu, H.

C. Kuo, O. Coquoz, T. L. Troy, H. Xu, and B. W. Rice, “Three-dimensional reconstruction of in vivo bioluminescent sources based on multispectral imaging,” J. Biomed. Opt. 12(2), 024007 (2007).
[Crossref] [PubMed]

H. Xu, B. W. Pogue, R. Springett, and H. Dehghani, “Spectral derivative based image reconstruction provides inherent insensitivity to coupling and geometric errors,” Opt. Lett. 30(21), 2912–2914 (2005).
[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: algorithms for numerical model and image reconstruction algorithms,” Commun. Numer. Methods Eng. (2008).

Zelmer, A.

N. Andreu, A. Zelmer, and S. Wiles, “Noninvasive biophotonic imaging for studies of infectious disease,” FEMS Microbiol. Rev. 35(2), 360–394 (2011).
[Crossref] [PubMed]

Zhang, B.

B. Zhang, I. Iordachita, J. W. Wong, and K. K. H. Wang, “Multi-projection bioluminescence tomography guided system for small animal radiation research platform (SARRP),” Proc. SPIE 9701, 97010J (2016).

Zhang, Q.

Appl. Opt. (2)

Biomed. Opt. Express (3)

FEMS Microbiol. Rev. (1)

N. Andreu, A. Zelmer, and S. Wiles, “Noninvasive biophotonic imaging for studies of infectious disease,” FEMS Microbiol. Rev. 35(2), 360–394 (2011).
[Crossref] [PubMed]

IEEE Trans. Med. Imaging (2)

Y. Gao, K. Wang, S. Jiang, Y. Liu, T. Ai, and J. Tian, “Bioluminescence tomography based on gaussian weighted laplace prior regularization for in vivo morphological imaging of glioma,” IEEE Trans. Med. Imaging 36(11), 2343–2354 (2017).
[Crossref] [PubMed]

A. Soubret, J. Ripoll, and V. Ntziachristos, “Accuracy of fluorescent tomography in the presence of heterogeneities: study of the normalized Born ratio,” IEEE Trans. Med. Imaging 24(10), 1377–1386 (2005).
[Crossref] [PubMed]

Inverse Probl. (1)

S. R. Arridge, “Optical tomography in medical imaging,” Inverse Probl. 15(2), R41–R93 (1999).
[Crossref]

J. Biomed. Opt. (2)

S. L. Taylor, S. K. G. Mason, S. L. Glinton, M. Cobbold, and H. Dehghani, “Accounting for filter bandwidth improves the quantitative accuracy of bioluminescence tomography,” J. Biomed. Opt. 20(9), 096001 (2015).
[Crossref] [PubMed]

C. Kuo, O. Coquoz, T. L. Troy, H. Xu, and B. W. Rice, “Three-dimensional reconstruction of in vivo bioluminescent sources based on multispectral imaging,” J. Biomed. Opt. 12(2), 024007 (2007).
[Crossref] [PubMed]

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

J. Pathol. (1)

K. O’Neill, S. K. Lyons, W. M. Gallagher, K. M. Curran, and A. T. Byrne, “Bioluminescent imaging: a critical tool in pre-clinical oncology research,” J. Pathol. 220(3), 317–327 (2010).
[PubMed]

Meas. Sci. Technol. (1)

J. A. Guggenheim, H. R. A. Basevi, J. Frampton, I. B. Styles, and H. Dehghani, “Multi-modal molecular diffuse optical tomography system for small animal imaging,” Meas. Sci. Technol. 24(10), 105405 (2013).
[Crossref] [PubMed]

Med. Phys. (2)

H. Dehghani, S. C. Davis, and B. W. Pogue, “Spectrally resolved bioluminescence tomography using the reciprocity approach,” Med. Phys. 35(11), 4863–4871 (2008).
[Crossref] [PubMed]

G. Wang, Y. Li, and M. Jiang, “Uniqueness theorems in bioluminescence tomography,” Med. Phys. 31(8), 2289–2299 (2004).
[Crossref] [PubMed]

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]

Opt. Express (1)

Opt. Lett. (2)

Phys. Med. Biol. (3)

A. P. Gibson, J. C. Hebden, and S. R. Arridge, “Recent advances in diffuse optical imaging,” Phys. Med. Biol. 50(4), R1–R43 (2005).
[Crossref] [PubMed]

H. Dehghani, F. Leblond, B. W. Pogue, and F. Chauchard, “Application of spectral derivative data in visible and near-infrared spectroscopy,” Phys. Med. Biol. 55(12), 3381–3399 (2010).
[Crossref] [PubMed]

C. Darne, Y. Lu, and E. M. Sevick-Muraca, “Small animal fluorescence and bioluminescence tomography: a review of approaches, algorithms and technology update,” Phys. Med. Biol. 59(1), R1–R64 (2014).
[Crossref] [PubMed]

Phys. Rev. Lett. (1)

J. Ripoll, R. B. Schulz, and V. Ntziachristos, “Free-space propagation of diffuse light: theory and experiments,” Phys. Rev. Lett. 91(10), 103901 (2003).
[Crossref] [PubMed]

Proc. SPIE (1)

B. Zhang, I. Iordachita, J. W. Wong, and K. K. H. Wang, “Multi-projection bioluminescence tomography guided system for small animal radiation research platform (SARRP),” Proc. SPIE 9701, 97010J (2016).

Other (2)

A. D. Klose, K. Li, and N. Paragas, “Automated data analysis for preclinical imaging of bioluminescent reporter systems,” in Biophotonics Congress: Biomedical Optics Congress 2018 (Microscopy/Translational/Brain/OTS), OSA Technical Digest (Optical Society of America, 2018), JTu3A.24.
[Crossref]

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: algorithms for numerical model and image reconstruction algorithms,” Commun. Numer. Methods Eng. (2008).

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Figures (4)

Fig. 1
Fig. 1 Schematic of the imaging protocol and phantom setup and the total photon count images from the source at 5 mm depth with varying rotational angles.
Fig. 2
Fig. 2 Measured intensity data from the cylindrical phantom as function of (a) angle and (b) the cosine of turning angle.
Fig. 3
Fig. 3 (a) Schematic of 2D circular model with a single bioluminescence source and 17 detectors placed equidistance at +/− 10 degrees from central axis with the camera being placed directly above and (b) Reconstructed images of simulated radial offset added data from 2D circle using ‘raw’ intensity data and ‘logarithm of intensity’ data for different levels of noise.
Fig. 4
Fig. 4 (left top): Photo of the mouse phantom used in the experiment; (left bottom): 3D surface image of the mapped boundary data at 630 nm; (top row): The coronal and (bottom row): transverse slices of the CBCT image, with overlaid recovered maps using the raw as well as spectral derivative data. The red circles shown mark the light source.

Tables (1)

Tables Icon

Table 1 The total expected and recovered bioluminescence intensity (AU) using different reconstruction algorithms

Equations (8)

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

A λ x= b λ
[ A λ1 A λ2 A λ3 A λ4 ]x=[ b λ1 b λ2 b λ3 b λ4 ]
A λ x= b λ n
logb= logb b b
log( b λ n) b λ n A λ x=log( b λ n)
log( b λi n) b λi n A λi x=log( b λi n)
log( b λi+1 n) b λi+1 n A λi+1 x=log( b λi+1 n)
[ log( b λi n) b λi n A λi log( b λi+1 n) b λi+1 n A λi+1 ]x=log( b λi b λi+1 )

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