Abstract

The nonlinear normalized Born ratio (nBorn) method normalizes emission data with excitation data nonlinearly, which makes the relative distributions of the normalized measurements different from those of the emission data. When compared with the reconstruction using only emission data, what the nonlinear nBorn method does is equivalent to introducing the noisy excitation data to emission data. In our linear nBorn method, the emission data for each projection is linearly normalized with the average excitation data of all detectors. Phantom and in vivo mice studies indicate that the linear nBorn method provides better localization and quantitative performance than the nonlinear nBorn method.

© 2017 Optical Society of America

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  1. X. Guo, X. Liu, X. Wang, F. Tian, F. Liu, B. Zhang, G. Hu, and J. Bai, “A combined fluorescence and microcomputed tomography system for small animal imaging,” IEEE Trans. Biomed. Eng. 57(12), 2876–2883 (2010).
    [Crossref] [PubMed]
  2. X. Song, D. Wang, N. Chen, J. Bai, and H. Wang, “Reconstruction for free-space fluorescence tomography using a novel hybrid adaptive finite element algorithm,” Opt. Express 15(26), 18300–18317 (2007).
    [Crossref] [PubMed]
  3. J. Ye, C. Chi, Z. Xue, P. Wu, Y. An, H. Xu, S. Zhang, and J. Tian, “Fast and robust reconstruction for fluorescence molecular tomography via a sparsity adaptive subspace pursuit method,” Biomed. Opt. Express 5(2), 387–406 (2014).
    [Crossref] [PubMed]
  4. N. Deliolanis, T. Lasser, D. Hyde, A. Soubret, J. Ripoll, and V. Ntziachristos, “Free-space fluorescence molecular tomography utilizing 360 degrees geometry projections,” Opt. Lett. 32(4), 382–384 (2007).
    [Crossref] [PubMed]
  5. V. Ermolayev, P. Mohajerani, A. Ale, A. Sarantopoulos, M. Aichler, G. Kayser, A. Walch, and V. Ntziachristos, “Early recognition of lung cancer by integrin targeted imaging in K-ras mouse model,” Int. J. Cancer 137(5), 1107–1118 (2015).
    [Crossref] [PubMed]
  6. F. Gremse, B. Theek, S. Kunjachan, W. Lederle, A. Pardo, S. Barth, T. Lammers, U. Naumann, and F. Kiessling, “Absorption reconstruction improves biodistribution assessment of fluorescent nanoprobes using hybrid fluorescence-mediated tomography,” Theranostics 4(10), 960–971 (2014).
    [Crossref] [PubMed]
  7. M. Nahrendorf, P. Waterman, G. Thurber, K. Groves, M. Rajopadhye, P. Panizzi, B. Marinelli, E. Aikawa, M. J. Pittet, F. K. Swirski, and R. Weissleder, “Hybrid in vivo FMT-CT imaging of protease activity in atherosclerosis with customized nanosensors,” Arterioscler. Thromb. Vasc. Biol. 29(10), 1444–1451 (2009).
    [Crossref] [PubMed]
  8. R. Roy, A. Godavarty, and E. M. Sevick-Muraca, “Fluorescence-enhanced optical tomography using referenced measurements of heterogeneous media,” IEEE Trans. Med. Imaging 22(7), 824–836 (2003).
    [Crossref] [PubMed]
  9. J. Lee and E. Sevick-Muraca, “Fluorescence-enhanced absorption imaging: noise tolerance characteristic comparison with conventional absorption and scattering imaging,” J. Biomed. Opt. 6(1), 234–238 (2000).
  10. 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]
  11. T. Pyka, R. Schulz, A. Ale, and V. Ntziachristos, “Revisiting the normalized Born approximation: effects of scattering,” Opt. Lett. 36(22), 4329–4331 (2011).
    [Crossref] [PubMed]
  12. Y. Lin, W. C. Barber, J. S. Iwanczyk, W. Roeck, O. Nalcioglu, and G. Gulsen, “Quantitative fluorescence tomography using a combined tri-modality FT/DOT/XCT system,” Opt. Express 18(8), 7835–7850 (2010).
    [Crossref] [PubMed]
  13. F. Tian, H. Niu, S. Khadka, Z.-J. Lin, and H. Liu, “Algorithmic depth compensation improves quantification and noise suppression in functional diffuse optical tomography,” Biomed. Opt. Express 1(2), 441–452 (2010).
    [Crossref] [PubMed]
  14. J. F. P.-J. Abascal, J. Aguirre, J. Chamorro-Servent, M. Schweiger, S. Arridge, J. Ripoll, J. J. Vaquero, and M. Desco, “Influence of absorption and scattering on the quantification of fluorescence diffuse optical tomography using normalized data,” J. Biomed. Opt. 17(3), 036013 (2012).
    [Crossref] [PubMed]
  15. Y. Lin, W. C. Barber, J. S. Iwanczyk, W. W. Roeck, O. Nalcioglu, and G. Gulsen, “Quantitative fluorescence tomography using a trimodality system: in vivo validation,” J. Biomed. Opt. 15(4), 040503 (2010).
    [Crossref] [PubMed]
  16. Y. Meng, X. Yang, Y. Deng, X. Zhang, and H. Gong, “A method of extracting structural priors from images of micro-CT for fluorescence molecular tomography reconstruction,” J. XRay Sci. Technol. 22(3), 285–297 (2014).
    [PubMed]
  17. A. Li, Q. Zhang, J. P. Culver, E. L. Miller, and D. A. Boas, “Reconstructing chromosphere concentration images directly by continuous-wave diffuse optical tomography,” Opt. Lett. 29(3), 256–258 (2004).
    [Crossref] [PubMed]
  18. D. Hyde, E. Miller, D. H. Brooks, and V. Ntziachristos, “A statistical approach to inverting the born ratio,” IEEE Trans. Med. Imaging 26(7), 893–905 (2007).
    [Crossref] [PubMed]
  19. W. Xie, Y. Deng, K. Wang, X. Yang, and Q. Luo, “Reweighted L1 regularization for restraining artifacts in FMT reconstruction images with limited measurements,” Opt. Lett. 39(14), 4148–4151 (2014).
    [Crossref] [PubMed]
  20. Y. An, J. Liu, G. Zhang, J. Ye, Y. Mao, S. Jiang, W. Shang, Y. Du, C. Chi, and J. Tian, “Meshless reconstruction method for fluorescence molecular tomography based on compactly supported radial basis function,” J. Biomed. Opt. 20(10), 105003 (2015).
    [Crossref] [PubMed]
  21. M. J. Niedre, G. M. Turner, and V. Ntziachristos, “Time-resolved imaging of optical coefficients through murine chest cavities,” J. Biomed. Opt. 11(6), 064017 (2006).
    [Crossref] [PubMed]
  22. L. Lian, Y. Deng, W. Xie, G. Xu, X. Yang, Z. Zhang, and Q. Luo, “High-dynamic-range fluorescence molecular tomography for imaging of fluorescent targets with large concentration differences,” Opt. Express 24(17), 19920–19933 (2016).
    [Crossref] [PubMed]
  23. D. Vonwil, J. Christensen, S. Fischer, O. Ronneberger, and V. P. Shastri, “Validation of Fluorescence Molecular Tomography/Micro-CT Multimodal Imaging In Vivo in rats,” Mol. Imaging Biol. 16(3), 350–361 (2014).
    [Crossref] [PubMed]
  24. X. He, H. Guo, J. Yu, X. Zhang, and Y. Hou, “Effective and robust approach for fluorescence molecular tomography based on CoSaMP and SP3 model,” J. Innov. Opt. Health Sci. 9(6), 1650024 (2016).
    [Crossref]

2016 (2)

L. Lian, Y. Deng, W. Xie, G. Xu, X. Yang, Z. Zhang, and Q. Luo, “High-dynamic-range fluorescence molecular tomography for imaging of fluorescent targets with large concentration differences,” Opt. Express 24(17), 19920–19933 (2016).
[Crossref] [PubMed]

X. He, H. Guo, J. Yu, X. Zhang, and Y. Hou, “Effective and robust approach for fluorescence molecular tomography based on CoSaMP and SP3 model,” J. Innov. Opt. Health Sci. 9(6), 1650024 (2016).
[Crossref]

2015 (2)

Y. An, J. Liu, G. Zhang, J. Ye, Y. Mao, S. Jiang, W. Shang, Y. Du, C. Chi, and J. Tian, “Meshless reconstruction method for fluorescence molecular tomography based on compactly supported radial basis function,” J. Biomed. Opt. 20(10), 105003 (2015).
[Crossref] [PubMed]

V. Ermolayev, P. Mohajerani, A. Ale, A. Sarantopoulos, M. Aichler, G. Kayser, A. Walch, and V. Ntziachristos, “Early recognition of lung cancer by integrin targeted imaging in K-ras mouse model,” Int. J. Cancer 137(5), 1107–1118 (2015).
[Crossref] [PubMed]

2014 (5)

F. Gremse, B. Theek, S. Kunjachan, W. Lederle, A. Pardo, S. Barth, T. Lammers, U. Naumann, and F. Kiessling, “Absorption reconstruction improves biodistribution assessment of fluorescent nanoprobes using hybrid fluorescence-mediated tomography,” Theranostics 4(10), 960–971 (2014).
[Crossref] [PubMed]

J. Ye, C. Chi, Z. Xue, P. Wu, Y. An, H. Xu, S. Zhang, and J. Tian, “Fast and robust reconstruction for fluorescence molecular tomography via a sparsity adaptive subspace pursuit method,” Biomed. Opt. Express 5(2), 387–406 (2014).
[Crossref] [PubMed]

Y. Meng, X. Yang, Y. Deng, X. Zhang, and H. Gong, “A method of extracting structural priors from images of micro-CT for fluorescence molecular tomography reconstruction,” J. XRay Sci. Technol. 22(3), 285–297 (2014).
[PubMed]

D. Vonwil, J. Christensen, S. Fischer, O. Ronneberger, and V. P. Shastri, “Validation of Fluorescence Molecular Tomography/Micro-CT Multimodal Imaging In Vivo in rats,” Mol. Imaging Biol. 16(3), 350–361 (2014).
[Crossref] [PubMed]

W. Xie, Y. Deng, K. Wang, X. Yang, and Q. Luo, “Reweighted L1 regularization for restraining artifacts in FMT reconstruction images with limited measurements,” Opt. Lett. 39(14), 4148–4151 (2014).
[Crossref] [PubMed]

2012 (1)

J. F. P.-J. Abascal, J. Aguirre, J. Chamorro-Servent, M. Schweiger, S. Arridge, J. Ripoll, J. J. Vaquero, and M. Desco, “Influence of absorption and scattering on the quantification of fluorescence diffuse optical tomography using normalized data,” J. Biomed. Opt. 17(3), 036013 (2012).
[Crossref] [PubMed]

2011 (1)

2010 (4)

Y. Lin, W. C. Barber, J. S. Iwanczyk, W. Roeck, O. Nalcioglu, and G. Gulsen, “Quantitative fluorescence tomography using a combined tri-modality FT/DOT/XCT system,” Opt. Express 18(8), 7835–7850 (2010).
[Crossref] [PubMed]

F. Tian, H. Niu, S. Khadka, Z.-J. Lin, and H. Liu, “Algorithmic depth compensation improves quantification and noise suppression in functional diffuse optical tomography,” Biomed. Opt. Express 1(2), 441–452 (2010).
[Crossref] [PubMed]

Y. Lin, W. C. Barber, J. S. Iwanczyk, W. W. Roeck, O. Nalcioglu, and G. Gulsen, “Quantitative fluorescence tomography using a trimodality system: in vivo validation,” J. Biomed. Opt. 15(4), 040503 (2010).
[Crossref] [PubMed]

X. Guo, X. Liu, X. Wang, F. Tian, F. Liu, B. Zhang, G. Hu, and J. Bai, “A combined fluorescence and microcomputed tomography system for small animal imaging,” IEEE Trans. Biomed. Eng. 57(12), 2876–2883 (2010).
[Crossref] [PubMed]

2009 (1)

M. Nahrendorf, P. Waterman, G. Thurber, K. Groves, M. Rajopadhye, P. Panizzi, B. Marinelli, E. Aikawa, M. J. Pittet, F. K. Swirski, and R. Weissleder, “Hybrid in vivo FMT-CT imaging of protease activity in atherosclerosis with customized nanosensors,” Arterioscler. Thromb. Vasc. Biol. 29(10), 1444–1451 (2009).
[Crossref] [PubMed]

2007 (3)

2006 (1)

M. J. Niedre, G. M. Turner, and V. Ntziachristos, “Time-resolved imaging of optical coefficients through murine chest cavities,” J. Biomed. Opt. 11(6), 064017 (2006).
[Crossref] [PubMed]

2005 (1)

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]

2004 (1)

2003 (1)

R. Roy, A. Godavarty, and E. M. Sevick-Muraca, “Fluorescence-enhanced optical tomography using referenced measurements of heterogeneous media,” IEEE Trans. Med. Imaging 22(7), 824–836 (2003).
[Crossref] [PubMed]

2000 (1)

J. Lee and E. Sevick-Muraca, “Fluorescence-enhanced absorption imaging: noise tolerance characteristic comparison with conventional absorption and scattering imaging,” J. Biomed. Opt. 6(1), 234–238 (2000).

Abascal, J. F. P.-J.

J. F. P.-J. Abascal, J. Aguirre, J. Chamorro-Servent, M. Schweiger, S. Arridge, J. Ripoll, J. J. Vaquero, and M. Desco, “Influence of absorption and scattering on the quantification of fluorescence diffuse optical tomography using normalized data,” J. Biomed. Opt. 17(3), 036013 (2012).
[Crossref] [PubMed]

Aguirre, J.

J. F. P.-J. Abascal, J. Aguirre, J. Chamorro-Servent, M. Schweiger, S. Arridge, J. Ripoll, J. J. Vaquero, and M. Desco, “Influence of absorption and scattering on the quantification of fluorescence diffuse optical tomography using normalized data,” J. Biomed. Opt. 17(3), 036013 (2012).
[Crossref] [PubMed]

Aichler, M.

V. Ermolayev, P. Mohajerani, A. Ale, A. Sarantopoulos, M. Aichler, G. Kayser, A. Walch, and V. Ntziachristos, “Early recognition of lung cancer by integrin targeted imaging in K-ras mouse model,” Int. J. Cancer 137(5), 1107–1118 (2015).
[Crossref] [PubMed]

Aikawa, E.

M. Nahrendorf, P. Waterman, G. Thurber, K. Groves, M. Rajopadhye, P. Panizzi, B. Marinelli, E. Aikawa, M. J. Pittet, F. K. Swirski, and R. Weissleder, “Hybrid in vivo FMT-CT imaging of protease activity in atherosclerosis with customized nanosensors,” Arterioscler. Thromb. Vasc. Biol. 29(10), 1444–1451 (2009).
[Crossref] [PubMed]

Ale, A.

V. Ermolayev, P. Mohajerani, A. Ale, A. Sarantopoulos, M. Aichler, G. Kayser, A. Walch, and V. Ntziachristos, “Early recognition of lung cancer by integrin targeted imaging in K-ras mouse model,” Int. J. Cancer 137(5), 1107–1118 (2015).
[Crossref] [PubMed]

T. Pyka, R. Schulz, A. Ale, and V. Ntziachristos, “Revisiting the normalized Born approximation: effects of scattering,” Opt. Lett. 36(22), 4329–4331 (2011).
[Crossref] [PubMed]

An, Y.

Y. An, J. Liu, G. Zhang, J. Ye, Y. Mao, S. Jiang, W. Shang, Y. Du, C. Chi, and J. Tian, “Meshless reconstruction method for fluorescence molecular tomography based on compactly supported radial basis function,” J. Biomed. Opt. 20(10), 105003 (2015).
[Crossref] [PubMed]

J. Ye, C. Chi, Z. Xue, P. Wu, Y. An, H. Xu, S. Zhang, and J. Tian, “Fast and robust reconstruction for fluorescence molecular tomography via a sparsity adaptive subspace pursuit method,” Biomed. Opt. Express 5(2), 387–406 (2014).
[Crossref] [PubMed]

Arridge, S.

J. F. P.-J. Abascal, J. Aguirre, J. Chamorro-Servent, M. Schweiger, S. Arridge, J. Ripoll, J. J. Vaquero, and M. Desco, “Influence of absorption and scattering on the quantification of fluorescence diffuse optical tomography using normalized data,” J. Biomed. Opt. 17(3), 036013 (2012).
[Crossref] [PubMed]

Bai, J.

X. Guo, X. Liu, X. Wang, F. Tian, F. Liu, B. Zhang, G. Hu, and J. Bai, “A combined fluorescence and microcomputed tomography system for small animal imaging,” IEEE Trans. Biomed. Eng. 57(12), 2876–2883 (2010).
[Crossref] [PubMed]

X. Song, D. Wang, N. Chen, J. Bai, and H. Wang, “Reconstruction for free-space fluorescence tomography using a novel hybrid adaptive finite element algorithm,” Opt. Express 15(26), 18300–18317 (2007).
[Crossref] [PubMed]

Barber, W. C.

Y. Lin, W. C. Barber, J. S. Iwanczyk, W. Roeck, O. Nalcioglu, and G. Gulsen, “Quantitative fluorescence tomography using a combined tri-modality FT/DOT/XCT system,” Opt. Express 18(8), 7835–7850 (2010).
[Crossref] [PubMed]

Y. Lin, W. C. Barber, J. S. Iwanczyk, W. W. Roeck, O. Nalcioglu, and G. Gulsen, “Quantitative fluorescence tomography using a trimodality system: in vivo validation,” J. Biomed. Opt. 15(4), 040503 (2010).
[Crossref] [PubMed]

Barth, S.

F. Gremse, B. Theek, S. Kunjachan, W. Lederle, A. Pardo, S. Barth, T. Lammers, U. Naumann, and F. Kiessling, “Absorption reconstruction improves biodistribution assessment of fluorescent nanoprobes using hybrid fluorescence-mediated tomography,” Theranostics 4(10), 960–971 (2014).
[Crossref] [PubMed]

Boas, D. A.

Brooks, D. H.

D. Hyde, E. Miller, D. H. Brooks, and V. Ntziachristos, “A statistical approach to inverting the born ratio,” IEEE Trans. Med. Imaging 26(7), 893–905 (2007).
[Crossref] [PubMed]

Chamorro-Servent, J.

J. F. P.-J. Abascal, J. Aguirre, J. Chamorro-Servent, M. Schweiger, S. Arridge, J. Ripoll, J. J. Vaquero, and M. Desco, “Influence of absorption and scattering on the quantification of fluorescence diffuse optical tomography using normalized data,” J. Biomed. Opt. 17(3), 036013 (2012).
[Crossref] [PubMed]

Chen, N.

Chi, C.

Y. An, J. Liu, G. Zhang, J. Ye, Y. Mao, S. Jiang, W. Shang, Y. Du, C. Chi, and J. Tian, “Meshless reconstruction method for fluorescence molecular tomography based on compactly supported radial basis function,” J. Biomed. Opt. 20(10), 105003 (2015).
[Crossref] [PubMed]

J. Ye, C. Chi, Z. Xue, P. Wu, Y. An, H. Xu, S. Zhang, and J. Tian, “Fast and robust reconstruction for fluorescence molecular tomography via a sparsity adaptive subspace pursuit method,” Biomed. Opt. Express 5(2), 387–406 (2014).
[Crossref] [PubMed]

Christensen, J.

D. Vonwil, J. Christensen, S. Fischer, O. Ronneberger, and V. P. Shastri, “Validation of Fluorescence Molecular Tomography/Micro-CT Multimodal Imaging In Vivo in rats,” Mol. Imaging Biol. 16(3), 350–361 (2014).
[Crossref] [PubMed]

Culver, J. P.

Deliolanis, N.

Deng, Y.

Desco, M.

J. F. P.-J. Abascal, J. Aguirre, J. Chamorro-Servent, M. Schweiger, S. Arridge, J. Ripoll, J. J. Vaquero, and M. Desco, “Influence of absorption and scattering on the quantification of fluorescence diffuse optical tomography using normalized data,” J. Biomed. Opt. 17(3), 036013 (2012).
[Crossref] [PubMed]

Du, Y.

Y. An, J. Liu, G. Zhang, J. Ye, Y. Mao, S. Jiang, W. Shang, Y. Du, C. Chi, and J. Tian, “Meshless reconstruction method for fluorescence molecular tomography based on compactly supported radial basis function,” J. Biomed. Opt. 20(10), 105003 (2015).
[Crossref] [PubMed]

Ermolayev, V.

V. Ermolayev, P. Mohajerani, A. Ale, A. Sarantopoulos, M. Aichler, G. Kayser, A. Walch, and V. Ntziachristos, “Early recognition of lung cancer by integrin targeted imaging in K-ras mouse model,” Int. J. Cancer 137(5), 1107–1118 (2015).
[Crossref] [PubMed]

Fischer, S.

D. Vonwil, J. Christensen, S. Fischer, O. Ronneberger, and V. P. Shastri, “Validation of Fluorescence Molecular Tomography/Micro-CT Multimodal Imaging In Vivo in rats,” Mol. Imaging Biol. 16(3), 350–361 (2014).
[Crossref] [PubMed]

Godavarty, A.

R. Roy, A. Godavarty, and E. M. Sevick-Muraca, “Fluorescence-enhanced optical tomography using referenced measurements of heterogeneous media,” IEEE Trans. Med. Imaging 22(7), 824–836 (2003).
[Crossref] [PubMed]

Gong, H.

Y. Meng, X. Yang, Y. Deng, X. Zhang, and H. Gong, “A method of extracting structural priors from images of micro-CT for fluorescence molecular tomography reconstruction,” J. XRay Sci. Technol. 22(3), 285–297 (2014).
[PubMed]

Gremse, F.

F. Gremse, B. Theek, S. Kunjachan, W. Lederle, A. Pardo, S. Barth, T. Lammers, U. Naumann, and F. Kiessling, “Absorption reconstruction improves biodistribution assessment of fluorescent nanoprobes using hybrid fluorescence-mediated tomography,” Theranostics 4(10), 960–971 (2014).
[Crossref] [PubMed]

Groves, K.

M. Nahrendorf, P. Waterman, G. Thurber, K. Groves, M. Rajopadhye, P. Panizzi, B. Marinelli, E. Aikawa, M. J. Pittet, F. K. Swirski, and R. Weissleder, “Hybrid in vivo FMT-CT imaging of protease activity in atherosclerosis with customized nanosensors,” Arterioscler. Thromb. Vasc. Biol. 29(10), 1444–1451 (2009).
[Crossref] [PubMed]

Gulsen, G.

Y. Lin, W. C. Barber, J. S. Iwanczyk, W. Roeck, O. Nalcioglu, and G. Gulsen, “Quantitative fluorescence tomography using a combined tri-modality FT/DOT/XCT system,” Opt. Express 18(8), 7835–7850 (2010).
[Crossref] [PubMed]

Y. Lin, W. C. Barber, J. S. Iwanczyk, W. W. Roeck, O. Nalcioglu, and G. Gulsen, “Quantitative fluorescence tomography using a trimodality system: in vivo validation,” J. Biomed. Opt. 15(4), 040503 (2010).
[Crossref] [PubMed]

Guo, H.

X. He, H. Guo, J. Yu, X. Zhang, and Y. Hou, “Effective and robust approach for fluorescence molecular tomography based on CoSaMP and SP3 model,” J. Innov. Opt. Health Sci. 9(6), 1650024 (2016).
[Crossref]

Guo, X.

X. Guo, X. Liu, X. Wang, F. Tian, F. Liu, B. Zhang, G. Hu, and J. Bai, “A combined fluorescence and microcomputed tomography system for small animal imaging,” IEEE Trans. Biomed. Eng. 57(12), 2876–2883 (2010).
[Crossref] [PubMed]

He, X.

X. He, H. Guo, J. Yu, X. Zhang, and Y. Hou, “Effective and robust approach for fluorescence molecular tomography based on CoSaMP and SP3 model,” J. Innov. Opt. Health Sci. 9(6), 1650024 (2016).
[Crossref]

Hou, Y.

X. He, H. Guo, J. Yu, X. Zhang, and Y. Hou, “Effective and robust approach for fluorescence molecular tomography based on CoSaMP and SP3 model,” J. Innov. Opt. Health Sci. 9(6), 1650024 (2016).
[Crossref]

Hu, G.

X. Guo, X. Liu, X. Wang, F. Tian, F. Liu, B. Zhang, G. Hu, and J. Bai, “A combined fluorescence and microcomputed tomography system for small animal imaging,” IEEE Trans. Biomed. Eng. 57(12), 2876–2883 (2010).
[Crossref] [PubMed]

Hyde, D.

Iwanczyk, J. S.

Y. Lin, W. C. Barber, J. S. Iwanczyk, W. W. Roeck, O. Nalcioglu, and G. Gulsen, “Quantitative fluorescence tomography using a trimodality system: in vivo validation,” J. Biomed. Opt. 15(4), 040503 (2010).
[Crossref] [PubMed]

Y. Lin, W. C. Barber, J. S. Iwanczyk, W. Roeck, O. Nalcioglu, and G. Gulsen, “Quantitative fluorescence tomography using a combined tri-modality FT/DOT/XCT system,” Opt. Express 18(8), 7835–7850 (2010).
[Crossref] [PubMed]

Jiang, S.

Y. An, J. Liu, G. Zhang, J. Ye, Y. Mao, S. Jiang, W. Shang, Y. Du, C. Chi, and J. Tian, “Meshless reconstruction method for fluorescence molecular tomography based on compactly supported radial basis function,” J. Biomed. Opt. 20(10), 105003 (2015).
[Crossref] [PubMed]

Kayser, G.

V. Ermolayev, P. Mohajerani, A. Ale, A. Sarantopoulos, M. Aichler, G. Kayser, A. Walch, and V. Ntziachristos, “Early recognition of lung cancer by integrin targeted imaging in K-ras mouse model,” Int. J. Cancer 137(5), 1107–1118 (2015).
[Crossref] [PubMed]

Khadka, S.

Kiessling, F.

F. Gremse, B. Theek, S. Kunjachan, W. Lederle, A. Pardo, S. Barth, T. Lammers, U. Naumann, and F. Kiessling, “Absorption reconstruction improves biodistribution assessment of fluorescent nanoprobes using hybrid fluorescence-mediated tomography,” Theranostics 4(10), 960–971 (2014).
[Crossref] [PubMed]

Kunjachan, S.

F. Gremse, B. Theek, S. Kunjachan, W. Lederle, A. Pardo, S. Barth, T. Lammers, U. Naumann, and F. Kiessling, “Absorption reconstruction improves biodistribution assessment of fluorescent nanoprobes using hybrid fluorescence-mediated tomography,” Theranostics 4(10), 960–971 (2014).
[Crossref] [PubMed]

Lammers, T.

F. Gremse, B. Theek, S. Kunjachan, W. Lederle, A. Pardo, S. Barth, T. Lammers, U. Naumann, and F. Kiessling, “Absorption reconstruction improves biodistribution assessment of fluorescent nanoprobes using hybrid fluorescence-mediated tomography,” Theranostics 4(10), 960–971 (2014).
[Crossref] [PubMed]

Lasser, T.

Lederle, W.

F. Gremse, B. Theek, S. Kunjachan, W. Lederle, A. Pardo, S. Barth, T. Lammers, U. Naumann, and F. Kiessling, “Absorption reconstruction improves biodistribution assessment of fluorescent nanoprobes using hybrid fluorescence-mediated tomography,” Theranostics 4(10), 960–971 (2014).
[Crossref] [PubMed]

Lee, J.

J. Lee and E. Sevick-Muraca, “Fluorescence-enhanced absorption imaging: noise tolerance characteristic comparison with conventional absorption and scattering imaging,” J. Biomed. Opt. 6(1), 234–238 (2000).

Li, A.

Lian, L.

Lin, Y.

Y. Lin, W. C. Barber, J. S. Iwanczyk, W. W. Roeck, O. Nalcioglu, and G. Gulsen, “Quantitative fluorescence tomography using a trimodality system: in vivo validation,” J. Biomed. Opt. 15(4), 040503 (2010).
[Crossref] [PubMed]

Y. Lin, W. C. Barber, J. S. Iwanczyk, W. Roeck, O. Nalcioglu, and G. Gulsen, “Quantitative fluorescence tomography using a combined tri-modality FT/DOT/XCT system,” Opt. Express 18(8), 7835–7850 (2010).
[Crossref] [PubMed]

Lin, Z.-J.

Liu, F.

X. Guo, X. Liu, X. Wang, F. Tian, F. Liu, B. Zhang, G. Hu, and J. Bai, “A combined fluorescence and microcomputed tomography system for small animal imaging,” IEEE Trans. Biomed. Eng. 57(12), 2876–2883 (2010).
[Crossref] [PubMed]

Liu, H.

Liu, J.

Y. An, J. Liu, G. Zhang, J. Ye, Y. Mao, S. Jiang, W. Shang, Y. Du, C. Chi, and J. Tian, “Meshless reconstruction method for fluorescence molecular tomography based on compactly supported radial basis function,” J. Biomed. Opt. 20(10), 105003 (2015).
[Crossref] [PubMed]

Liu, X.

X. Guo, X. Liu, X. Wang, F. Tian, F. Liu, B. Zhang, G. Hu, and J. Bai, “A combined fluorescence and microcomputed tomography system for small animal imaging,” IEEE Trans. Biomed. Eng. 57(12), 2876–2883 (2010).
[Crossref] [PubMed]

Luo, Q.

Mao, Y.

Y. An, J. Liu, G. Zhang, J. Ye, Y. Mao, S. Jiang, W. Shang, Y. Du, C. Chi, and J. Tian, “Meshless reconstruction method for fluorescence molecular tomography based on compactly supported radial basis function,” J. Biomed. Opt. 20(10), 105003 (2015).
[Crossref] [PubMed]

Marinelli, B.

M. Nahrendorf, P. Waterman, G. Thurber, K. Groves, M. Rajopadhye, P. Panizzi, B. Marinelli, E. Aikawa, M. J. Pittet, F. K. Swirski, and R. Weissleder, “Hybrid in vivo FMT-CT imaging of protease activity in atherosclerosis with customized nanosensors,” Arterioscler. Thromb. Vasc. Biol. 29(10), 1444–1451 (2009).
[Crossref] [PubMed]

Meng, Y.

Y. Meng, X. Yang, Y. Deng, X. Zhang, and H. Gong, “A method of extracting structural priors from images of micro-CT for fluorescence molecular tomography reconstruction,” J. XRay Sci. Technol. 22(3), 285–297 (2014).
[PubMed]

Miller, E.

D. Hyde, E. Miller, D. H. Brooks, and V. Ntziachristos, “A statistical approach to inverting the born ratio,” IEEE Trans. Med. Imaging 26(7), 893–905 (2007).
[Crossref] [PubMed]

Miller, E. L.

Mohajerani, P.

V. Ermolayev, P. Mohajerani, A. Ale, A. Sarantopoulos, M. Aichler, G. Kayser, A. Walch, and V. Ntziachristos, “Early recognition of lung cancer by integrin targeted imaging in K-ras mouse model,” Int. J. Cancer 137(5), 1107–1118 (2015).
[Crossref] [PubMed]

Nahrendorf, M.

M. Nahrendorf, P. Waterman, G. Thurber, K. Groves, M. Rajopadhye, P. Panizzi, B. Marinelli, E. Aikawa, M. J. Pittet, F. K. Swirski, and R. Weissleder, “Hybrid in vivo FMT-CT imaging of protease activity in atherosclerosis with customized nanosensors,” Arterioscler. Thromb. Vasc. Biol. 29(10), 1444–1451 (2009).
[Crossref] [PubMed]

Nalcioglu, O.

Y. Lin, W. C. Barber, J. S. Iwanczyk, W. Roeck, O. Nalcioglu, and G. Gulsen, “Quantitative fluorescence tomography using a combined tri-modality FT/DOT/XCT system,” Opt. Express 18(8), 7835–7850 (2010).
[Crossref] [PubMed]

Y. Lin, W. C. Barber, J. S. Iwanczyk, W. W. Roeck, O. Nalcioglu, and G. Gulsen, “Quantitative fluorescence tomography using a trimodality system: in vivo validation,” J. Biomed. Opt. 15(4), 040503 (2010).
[Crossref] [PubMed]

Naumann, U.

F. Gremse, B. Theek, S. Kunjachan, W. Lederle, A. Pardo, S. Barth, T. Lammers, U. Naumann, and F. Kiessling, “Absorption reconstruction improves biodistribution assessment of fluorescent nanoprobes using hybrid fluorescence-mediated tomography,” Theranostics 4(10), 960–971 (2014).
[Crossref] [PubMed]

Niedre, M. J.

M. J. Niedre, G. M. Turner, and V. Ntziachristos, “Time-resolved imaging of optical coefficients through murine chest cavities,” J. Biomed. Opt. 11(6), 064017 (2006).
[Crossref] [PubMed]

Niu, H.

Ntziachristos, V.

V. Ermolayev, P. Mohajerani, A. Ale, A. Sarantopoulos, M. Aichler, G. Kayser, A. Walch, and V. Ntziachristos, “Early recognition of lung cancer by integrin targeted imaging in K-ras mouse model,” Int. J. Cancer 137(5), 1107–1118 (2015).
[Crossref] [PubMed]

T. Pyka, R. Schulz, A. Ale, and V. Ntziachristos, “Revisiting the normalized Born approximation: effects of scattering,” Opt. Lett. 36(22), 4329–4331 (2011).
[Crossref] [PubMed]

N. Deliolanis, T. Lasser, D. Hyde, A. Soubret, J. Ripoll, and V. Ntziachristos, “Free-space fluorescence molecular tomography utilizing 360 degrees geometry projections,” Opt. Lett. 32(4), 382–384 (2007).
[Crossref] [PubMed]

D. Hyde, E. Miller, D. H. Brooks, and V. Ntziachristos, “A statistical approach to inverting the born ratio,” IEEE Trans. Med. Imaging 26(7), 893–905 (2007).
[Crossref] [PubMed]

M. J. Niedre, G. M. Turner, and V. Ntziachristos, “Time-resolved imaging of optical coefficients through murine chest cavities,” J. Biomed. Opt. 11(6), 064017 (2006).
[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]

Panizzi, P.

M. Nahrendorf, P. Waterman, G. Thurber, K. Groves, M. Rajopadhye, P. Panizzi, B. Marinelli, E. Aikawa, M. J. Pittet, F. K. Swirski, and R. Weissleder, “Hybrid in vivo FMT-CT imaging of protease activity in atherosclerosis with customized nanosensors,” Arterioscler. Thromb. Vasc. Biol. 29(10), 1444–1451 (2009).
[Crossref] [PubMed]

Pardo, A.

F. Gremse, B. Theek, S. Kunjachan, W. Lederle, A. Pardo, S. Barth, T. Lammers, U. Naumann, and F. Kiessling, “Absorption reconstruction improves biodistribution assessment of fluorescent nanoprobes using hybrid fluorescence-mediated tomography,” Theranostics 4(10), 960–971 (2014).
[Crossref] [PubMed]

Pittet, M. J.

M. Nahrendorf, P. Waterman, G. Thurber, K. Groves, M. Rajopadhye, P. Panizzi, B. Marinelli, E. Aikawa, M. J. Pittet, F. K. Swirski, and R. Weissleder, “Hybrid in vivo FMT-CT imaging of protease activity in atherosclerosis with customized nanosensors,” Arterioscler. Thromb. Vasc. Biol. 29(10), 1444–1451 (2009).
[Crossref] [PubMed]

Pyka, T.

Rajopadhye, M.

M. Nahrendorf, P. Waterman, G. Thurber, K. Groves, M. Rajopadhye, P. Panizzi, B. Marinelli, E. Aikawa, M. J. Pittet, F. K. Swirski, and R. Weissleder, “Hybrid in vivo FMT-CT imaging of protease activity in atherosclerosis with customized nanosensors,” Arterioscler. Thromb. Vasc. Biol. 29(10), 1444–1451 (2009).
[Crossref] [PubMed]

Ripoll, J.

J. F. P.-J. Abascal, J. Aguirre, J. Chamorro-Servent, M. Schweiger, S. Arridge, J. Ripoll, J. J. Vaquero, and M. Desco, “Influence of absorption and scattering on the quantification of fluorescence diffuse optical tomography using normalized data,” J. Biomed. Opt. 17(3), 036013 (2012).
[Crossref] [PubMed]

N. Deliolanis, T. Lasser, D. Hyde, A. Soubret, J. Ripoll, and V. Ntziachristos, “Free-space fluorescence molecular tomography utilizing 360 degrees geometry projections,” Opt. Lett. 32(4), 382–384 (2007).
[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]

Roeck, W.

Roeck, W. W.

Y. Lin, W. C. Barber, J. S. Iwanczyk, W. W. Roeck, O. Nalcioglu, and G. Gulsen, “Quantitative fluorescence tomography using a trimodality system: in vivo validation,” J. Biomed. Opt. 15(4), 040503 (2010).
[Crossref] [PubMed]

Ronneberger, O.

D. Vonwil, J. Christensen, S. Fischer, O. Ronneberger, and V. P. Shastri, “Validation of Fluorescence Molecular Tomography/Micro-CT Multimodal Imaging In Vivo in rats,” Mol. Imaging Biol. 16(3), 350–361 (2014).
[Crossref] [PubMed]

Roy, R.

R. Roy, A. Godavarty, and E. M. Sevick-Muraca, “Fluorescence-enhanced optical tomography using referenced measurements of heterogeneous media,” IEEE Trans. Med. Imaging 22(7), 824–836 (2003).
[Crossref] [PubMed]

Sarantopoulos, A.

V. Ermolayev, P. Mohajerani, A. Ale, A. Sarantopoulos, M. Aichler, G. Kayser, A. Walch, and V. Ntziachristos, “Early recognition of lung cancer by integrin targeted imaging in K-ras mouse model,” Int. J. Cancer 137(5), 1107–1118 (2015).
[Crossref] [PubMed]

Schulz, R.

Schweiger, M.

J. F. P.-J. Abascal, J. Aguirre, J. Chamorro-Servent, M. Schweiger, S. Arridge, J. Ripoll, J. J. Vaquero, and M. Desco, “Influence of absorption and scattering on the quantification of fluorescence diffuse optical tomography using normalized data,” J. Biomed. Opt. 17(3), 036013 (2012).
[Crossref] [PubMed]

Sevick-Muraca, E.

J. Lee and E. Sevick-Muraca, “Fluorescence-enhanced absorption imaging: noise tolerance characteristic comparison with conventional absorption and scattering imaging,” J. Biomed. Opt. 6(1), 234–238 (2000).

Sevick-Muraca, E. M.

R. Roy, A. Godavarty, and E. M. Sevick-Muraca, “Fluorescence-enhanced optical tomography using referenced measurements of heterogeneous media,” IEEE Trans. Med. Imaging 22(7), 824–836 (2003).
[Crossref] [PubMed]

Shang, W.

Y. An, J. Liu, G. Zhang, J. Ye, Y. Mao, S. Jiang, W. Shang, Y. Du, C. Chi, and J. Tian, “Meshless reconstruction method for fluorescence molecular tomography based on compactly supported radial basis function,” J. Biomed. Opt. 20(10), 105003 (2015).
[Crossref] [PubMed]

Shastri, V. P.

D. Vonwil, J. Christensen, S. Fischer, O. Ronneberger, and V. P. Shastri, “Validation of Fluorescence Molecular Tomography/Micro-CT Multimodal Imaging In Vivo in rats,” Mol. Imaging Biol. 16(3), 350–361 (2014).
[Crossref] [PubMed]

Song, X.

Soubret, A.

N. Deliolanis, T. Lasser, D. Hyde, A. Soubret, J. Ripoll, and V. Ntziachristos, “Free-space fluorescence molecular tomography utilizing 360 degrees geometry projections,” Opt. Lett. 32(4), 382–384 (2007).
[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]

Swirski, F. K.

M. Nahrendorf, P. Waterman, G. Thurber, K. Groves, M. Rajopadhye, P. Panizzi, B. Marinelli, E. Aikawa, M. J. Pittet, F. K. Swirski, and R. Weissleder, “Hybrid in vivo FMT-CT imaging of protease activity in atherosclerosis with customized nanosensors,” Arterioscler. Thromb. Vasc. Biol. 29(10), 1444–1451 (2009).
[Crossref] [PubMed]

Theek, B.

F. Gremse, B. Theek, S. Kunjachan, W. Lederle, A. Pardo, S. Barth, T. Lammers, U. Naumann, and F. Kiessling, “Absorption reconstruction improves biodistribution assessment of fluorescent nanoprobes using hybrid fluorescence-mediated tomography,” Theranostics 4(10), 960–971 (2014).
[Crossref] [PubMed]

Thurber, G.

M. Nahrendorf, P. Waterman, G. Thurber, K. Groves, M. Rajopadhye, P. Panizzi, B. Marinelli, E. Aikawa, M. J. Pittet, F. K. Swirski, and R. Weissleder, “Hybrid in vivo FMT-CT imaging of protease activity in atherosclerosis with customized nanosensors,” Arterioscler. Thromb. Vasc. Biol. 29(10), 1444–1451 (2009).
[Crossref] [PubMed]

Tian, F.

F. Tian, H. Niu, S. Khadka, Z.-J. Lin, and H. Liu, “Algorithmic depth compensation improves quantification and noise suppression in functional diffuse optical tomography,” Biomed. Opt. Express 1(2), 441–452 (2010).
[Crossref] [PubMed]

X. Guo, X. Liu, X. Wang, F. Tian, F. Liu, B. Zhang, G. Hu, and J. Bai, “A combined fluorescence and microcomputed tomography system for small animal imaging,” IEEE Trans. Biomed. Eng. 57(12), 2876–2883 (2010).
[Crossref] [PubMed]

Tian, J.

Y. An, J. Liu, G. Zhang, J. Ye, Y. Mao, S. Jiang, W. Shang, Y. Du, C. Chi, and J. Tian, “Meshless reconstruction method for fluorescence molecular tomography based on compactly supported radial basis function,” J. Biomed. Opt. 20(10), 105003 (2015).
[Crossref] [PubMed]

J. Ye, C. Chi, Z. Xue, P. Wu, Y. An, H. Xu, S. Zhang, and J. Tian, “Fast and robust reconstruction for fluorescence molecular tomography via a sparsity adaptive subspace pursuit method,” Biomed. Opt. Express 5(2), 387–406 (2014).
[Crossref] [PubMed]

Turner, G. M.

M. J. Niedre, G. M. Turner, and V. Ntziachristos, “Time-resolved imaging of optical coefficients through murine chest cavities,” J. Biomed. Opt. 11(6), 064017 (2006).
[Crossref] [PubMed]

Vaquero, J. J.

J. F. P.-J. Abascal, J. Aguirre, J. Chamorro-Servent, M. Schweiger, S. Arridge, J. Ripoll, J. J. Vaquero, and M. Desco, “Influence of absorption and scattering on the quantification of fluorescence diffuse optical tomography using normalized data,” J. Biomed. Opt. 17(3), 036013 (2012).
[Crossref] [PubMed]

Vonwil, D.

D. Vonwil, J. Christensen, S. Fischer, O. Ronneberger, and V. P. Shastri, “Validation of Fluorescence Molecular Tomography/Micro-CT Multimodal Imaging In Vivo in rats,” Mol. Imaging Biol. 16(3), 350–361 (2014).
[Crossref] [PubMed]

Walch, A.

V. Ermolayev, P. Mohajerani, A. Ale, A. Sarantopoulos, M. Aichler, G. Kayser, A. Walch, and V. Ntziachristos, “Early recognition of lung cancer by integrin targeted imaging in K-ras mouse model,” Int. J. Cancer 137(5), 1107–1118 (2015).
[Crossref] [PubMed]

Wang, D.

Wang, H.

Wang, K.

Wang, X.

X. Guo, X. Liu, X. Wang, F. Tian, F. Liu, B. Zhang, G. Hu, and J. Bai, “A combined fluorescence and microcomputed tomography system for small animal imaging,” IEEE Trans. Biomed. Eng. 57(12), 2876–2883 (2010).
[Crossref] [PubMed]

Waterman, P.

M. Nahrendorf, P. Waterman, G. Thurber, K. Groves, M. Rajopadhye, P. Panizzi, B. Marinelli, E. Aikawa, M. J. Pittet, F. K. Swirski, and R. Weissleder, “Hybrid in vivo FMT-CT imaging of protease activity in atherosclerosis with customized nanosensors,” Arterioscler. Thromb. Vasc. Biol. 29(10), 1444–1451 (2009).
[Crossref] [PubMed]

Weissleder, R.

M. Nahrendorf, P. Waterman, G. Thurber, K. Groves, M. Rajopadhye, P. Panizzi, B. Marinelli, E. Aikawa, M. J. Pittet, F. K. Swirski, and R. Weissleder, “Hybrid in vivo FMT-CT imaging of protease activity in atherosclerosis with customized nanosensors,” Arterioscler. Thromb. Vasc. Biol. 29(10), 1444–1451 (2009).
[Crossref] [PubMed]

Wu, P.

Xie, W.

Xu, G.

Xu, H.

Xue, Z.

Yang, X.

Ye, J.

Y. An, J. Liu, G. Zhang, J. Ye, Y. Mao, S. Jiang, W. Shang, Y. Du, C. Chi, and J. Tian, “Meshless reconstruction method for fluorescence molecular tomography based on compactly supported radial basis function,” J. Biomed. Opt. 20(10), 105003 (2015).
[Crossref] [PubMed]

J. Ye, C. Chi, Z. Xue, P. Wu, Y. An, H. Xu, S. Zhang, and J. Tian, “Fast and robust reconstruction for fluorescence molecular tomography via a sparsity adaptive subspace pursuit method,” Biomed. Opt. Express 5(2), 387–406 (2014).
[Crossref] [PubMed]

Yu, J.

X. He, H. Guo, J. Yu, X. Zhang, and Y. Hou, “Effective and robust approach for fluorescence molecular tomography based on CoSaMP and SP3 model,” J. Innov. Opt. Health Sci. 9(6), 1650024 (2016).
[Crossref]

Zhang, B.

X. Guo, X. Liu, X. Wang, F. Tian, F. Liu, B. Zhang, G. Hu, and J. Bai, “A combined fluorescence and microcomputed tomography system for small animal imaging,” IEEE Trans. Biomed. Eng. 57(12), 2876–2883 (2010).
[Crossref] [PubMed]

Zhang, G.

Y. An, J. Liu, G. Zhang, J. Ye, Y. Mao, S. Jiang, W. Shang, Y. Du, C. Chi, and J. Tian, “Meshless reconstruction method for fluorescence molecular tomography based on compactly supported radial basis function,” J. Biomed. Opt. 20(10), 105003 (2015).
[Crossref] [PubMed]

Zhang, Q.

Zhang, S.

Zhang, X.

X. He, H. Guo, J. Yu, X. Zhang, and Y. Hou, “Effective and robust approach for fluorescence molecular tomography based on CoSaMP and SP3 model,” J. Innov. Opt. Health Sci. 9(6), 1650024 (2016).
[Crossref]

Y. Meng, X. Yang, Y. Deng, X. Zhang, and H. Gong, “A method of extracting structural priors from images of micro-CT for fluorescence molecular tomography reconstruction,” J. XRay Sci. Technol. 22(3), 285–297 (2014).
[PubMed]

Zhang, Z.

Arterioscler. Thromb. Vasc. Biol. (1)

M. Nahrendorf, P. Waterman, G. Thurber, K. Groves, M. Rajopadhye, P. Panizzi, B. Marinelli, E. Aikawa, M. J. Pittet, F. K. Swirski, and R. Weissleder, “Hybrid in vivo FMT-CT imaging of protease activity in atherosclerosis with customized nanosensors,” Arterioscler. Thromb. Vasc. Biol. 29(10), 1444–1451 (2009).
[Crossref] [PubMed]

Biomed. Opt. Express (2)

IEEE Trans. Biomed. Eng. (1)

X. Guo, X. Liu, X. Wang, F. Tian, F. Liu, B. Zhang, G. Hu, and J. Bai, “A combined fluorescence and microcomputed tomography system for small animal imaging,” IEEE Trans. Biomed. Eng. 57(12), 2876–2883 (2010).
[Crossref] [PubMed]

IEEE Trans. Med. Imaging (3)

R. Roy, A. Godavarty, and E. M. Sevick-Muraca, “Fluorescence-enhanced optical tomography using referenced measurements of heterogeneous media,” IEEE Trans. Med. Imaging 22(7), 824–836 (2003).
[Crossref] [PubMed]

D. Hyde, E. Miller, D. H. Brooks, and V. Ntziachristos, “A statistical approach to inverting the born ratio,” IEEE Trans. Med. Imaging 26(7), 893–905 (2007).
[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]

Int. J. Cancer (1)

V. Ermolayev, P. Mohajerani, A. Ale, A. Sarantopoulos, M. Aichler, G. Kayser, A. Walch, and V. Ntziachristos, “Early recognition of lung cancer by integrin targeted imaging in K-ras mouse model,” Int. J. Cancer 137(5), 1107–1118 (2015).
[Crossref] [PubMed]

J. Biomed. Opt. (5)

J. Lee and E. Sevick-Muraca, “Fluorescence-enhanced absorption imaging: noise tolerance characteristic comparison with conventional absorption and scattering imaging,” J. Biomed. Opt. 6(1), 234–238 (2000).

J. F. P.-J. Abascal, J. Aguirre, J. Chamorro-Servent, M. Schweiger, S. Arridge, J. Ripoll, J. J. Vaquero, and M. Desco, “Influence of absorption and scattering on the quantification of fluorescence diffuse optical tomography using normalized data,” J. Biomed. Opt. 17(3), 036013 (2012).
[Crossref] [PubMed]

Y. Lin, W. C. Barber, J. S. Iwanczyk, W. W. Roeck, O. Nalcioglu, and G. Gulsen, “Quantitative fluorescence tomography using a trimodality system: in vivo validation,” J. Biomed. Opt. 15(4), 040503 (2010).
[Crossref] [PubMed]

Y. An, J. Liu, G. Zhang, J. Ye, Y. Mao, S. Jiang, W. Shang, Y. Du, C. Chi, and J. Tian, “Meshless reconstruction method for fluorescence molecular tomography based on compactly supported radial basis function,” J. Biomed. Opt. 20(10), 105003 (2015).
[Crossref] [PubMed]

M. J. Niedre, G. M. Turner, and V. Ntziachristos, “Time-resolved imaging of optical coefficients through murine chest cavities,” J. Biomed. Opt. 11(6), 064017 (2006).
[Crossref] [PubMed]

J. Innov. Opt. Health Sci. (1)

X. He, H. Guo, J. Yu, X. Zhang, and Y. Hou, “Effective and robust approach for fluorescence molecular tomography based on CoSaMP and SP3 model,” J. Innov. Opt. Health Sci. 9(6), 1650024 (2016).
[Crossref]

J. XRay Sci. Technol. (1)

Y. Meng, X. Yang, Y. Deng, X. Zhang, and H. Gong, “A method of extracting structural priors from images of micro-CT for fluorescence molecular tomography reconstruction,” J. XRay Sci. Technol. 22(3), 285–297 (2014).
[PubMed]

Mol. Imaging Biol. (1)

D. Vonwil, J. Christensen, S. Fischer, O. Ronneberger, and V. P. Shastri, “Validation of Fluorescence Molecular Tomography/Micro-CT Multimodal Imaging In Vivo in rats,” Mol. Imaging Biol. 16(3), 350–361 (2014).
[Crossref] [PubMed]

Opt. Express (3)

Opt. Lett. (4)

Theranostics (1)

F. Gremse, B. Theek, S. Kunjachan, W. Lederle, A. Pardo, S. Barth, T. Lammers, U. Naumann, and F. Kiessling, “Absorption reconstruction improves biodistribution assessment of fluorescent nanoprobes using hybrid fluorescence-mediated tomography,” Theranostics 4(10), 960–971 (2014).
[Crossref] [PubMed]

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Figures (11)

Fig. 1
Fig. 1 (a) Schematic of the experimental system. (b) The model of the phantom used in the phantom study.
Fig. 2
Fig. 2 The reconstruction results of nonlinear and linear nBorn methods in experimental conditions (I)–(III) when homogeneous optical coefficients were used in the presence of absorption heterogeneities. [3D renderings were implemented using AMIRA software, FEI Company, Hillsboro, OR, USA.].
Fig. 3
Fig. 3 Average reconstructed FMT intensity as a function of the true DiR concentration when homogeneous optical coefficients were used in the presence of absorption heterogeneities. (a), (b), and (c) are the quantitative results in experimental conditions (I)–(III), respectively. The reconstructed values were normalized to the maximum value.
Fig. 4
Fig. 4 The reconstruction results of nonlinear and linear nBorn methods in experimental conditions (I)–(III) when the matched heterogeneous optical coefficients were used in the presence of absorption heterogeneities. [3D renderings were implemented using AMIRA software.]
Fig. 5
Fig. 5 Average reconstructed FMT intensity as a function of the true DiR concentration when the matched heterogeneous optical coefficients were used in the presence of absorption heterogeneities. (a), (b), and (c) are the quantitative results in experimental conditions (I)–(III), respectively. The reconstructed values were normalized to the maximum value.
Fig. 6
Fig. 6 The reconstruction results of nonlinear and linear nBorn methods in experimental conditions (I), (IV), and (V) when homogeneous optical coefficients were used in the presence of scattering heterogeneities. [3D renderings were implemented using AMIRA software.]
Fig. 7
Fig. 7 Average reconstructed FMT intensity as a function of the true DiR concentration when homogeneous optical coefficients were used in the presence of scattering heterogeneities. (a), (b), and (c) are the quantitative results in experimental conditions (I), (IV), and (V), respectively. The reconstructed values were normalized to the maximum value.
Fig. 8
Fig. 8 The reconstruction results of nonlinear and linear nBorn methods in experimental conditions (I), (IV), and (V) when the matched heterogeneous optical coefficients were used in the presence of scattering heterogeneities. [3D renderings were implemented using AMIRA software.]
Fig. 9
Fig. 9 Average reconstructed FMT intensity as a function of the true DiR concentration when homogeneous optical coefficients were used in the presence of scattering heterogeneities. (a), (b), and (c) are the quantitative results in experimental conditions (I), (IV), and (V), respectively. The reconstructed values were normalized to the maximum value.
Fig. 10
Fig. 10 The localization and quantitative results of in vivo experiments. (a) The relative positions of the fluorescent targets T1, T2,and T3 in the lower abdominal cavity of the mouse. (b) The 3D reconstruction result of the fluorescent targets with the nonlinear nBorn method. (c) The 3D reconstruction result of the fluorescent targets with the linear nBorn method. [Coordinate system was defined by D (dorsal), V (ventral), Cr (cranial), Cd (caudal), L (left), and R (right). 3D renderings in (b)–(c) were implemented using AMIRA software.]
Fig. 11
Fig. 11 Average reconstructed FMT intensity as a function of the true DiR concentration when the homogeneous optical coefficients were used in the in vivo experiment.

Tables (6)

Tables Icon

Table 1 Five sets of experiments and their configurations and the true optical coefficients of the heterogeneous-solution

Tables Icon

Table 2 The PE and R2 of the nonlinear and the linear nBorn methods in experimental conditions (I)–(III) when homogeneous optical coefficients were used in the presence of absorption heterogeneities.

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Table 3 The PE and R2 of the nonlinear and the linear nBorn methods in experimental conditions (I)–(III) when the matched heterogeneous optical coefficients were used in the presence of absorption heterogeneities.

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Table 4 The PE and R2 of the nonlinear and the linear nBorn methods in experimental conditions (I), (IV), and (V) when homogeneous optical coefficients were used in the presence of scattering heterogeneities.

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Table 5 The PE and R2 of the nonlinear and the linear nBorn methods in experimental conditions (I), (IV), and (V) when the matched heterogeneous optical coefficients were used in the presence of scattering heterogeneities.

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Table 6 The PE and R2 of the nonlinear and the linear nBorn methods in the in vivo experiment.

Equations (10)

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U f ( r d , r s ) = Q E λ fluo Θ f fluo d 3 r Θ det ( r d ) g 0 λ fluo ( r d , r ) v D λ fluo n ( r ) g 0 λ exc ( r , r s ) Θ src ( r s ) T λ fluo ,
U e ( r d , r s ) = Q E λ exc Θ f exc Θ det ( r d ) g 0 λ exc ( r d , r s ) Θ src ( r s ) T λ exc ,
U LnB ( r d , r s k ) = U f ( r d , r s k ) U LnB e ( r d , r s k ) = α 0 d 3 r g 0 λ fluo ( r d , r ) n ( r ) g 0 λ exc ( r , r s k ) j=1 j=n g 0 λ exc ( r d j , r s k ) / n ,
U m e a L n B = W x ,
x k + 1 = arg x 0 min 1 2 W x U m e a L n B 2 2 + λ M k x 1 ,
( m i i ) k + 1 = 1 | ( x i ) k | + α ,
x k + 1 = min x 1 2 W x U m e a L n B 2 2 + μ 2 d k M k x b k 2 2 ,
d k + 1 = min d λ d 1 + μ 2 d M k x b k 2 2 ,
b k + 1 = b k + ( M x k + 1 d k + 1 ) ,
PE= P r P 0 2 ,

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