Abstract

Cone-beam X-ray luminescence computed tomography (CB-XLCT) has become a promising technique for its higher utilization of X-ray and shorter scanning time compared to the narrow-beam XLCT, but it suffers from the low-spatial resolution that results in the insufficiency to resolve the adjacent multiple probes. In multispectral CB-XLCT, multiple probes show different emission behaviors in the dimension of the spectrum. In this work, a spectral-resolved CB-XLCT method combining multispectral CB-XLCT with principle component analysis (PCA) was proposed to improve the imaging resolution. Results of digital simulation and the phantom experiment illustrated that the proposed method was capable of resolving adjacent multiple probes accurately and had better performance than the common multispectral CB-XLCT with spectrum information priori.

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

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  1. G. Pratx, C. M. Carpenter, C. Sun, and L. Xing, “X-ray luminescence computed tomography via selective excitation: a feasibility study,” IEEE Trans. Med. Imaging 29(12), 1992–1999 (2010).
    [Crossref] [PubMed]
  2. C. Li, K. Di, J. Bec, and S. R. Cherry, “X-ray luminescence optical tomography imaging: experimental studies,” Opt. Lett. 38(13), 2339–2341 (2013).
    [Crossref] [PubMed]
  3. M. Ahmad, G. Pratx, M. Bazalova, and L. Xing, “X-ray luminescence and X-ray fluorescence computed tomography: new molecular imaging modalities,” IEEE Access 2(2), 1051–1061 (2014).
    [Crossref]
  4. W. Cong and G. Wang, “X-ray fan-beam luminescence tomography,” Austin J. Biomed. Eng. 1(5), 1024 (2014).
  5. D. Chen, S. Zhu, H. Yi, X. Zhang, D. Chen, J. Liang, and J. Tian, “Cone beam X-ray luminescence computed tomography: A feasibility study,” Med. Phys. 40(3), 031111 (2013).
    [Crossref] [PubMed]
  6. X. Liu, Q. Liao, and H. Wang, “In vivo X-ray luminescence tomographic imaging with single-view data,” Opt. Lett. 38(22), 4530–4533 (2013).
    [Crossref] [PubMed]
  7. X. Liu, Q. Liao, H. Wang, and Z. Yan, “Excitation-resolved cone-beam X-ray luminescence tomography,” J. Biomed. Opt. 20(7), 070501 (2015).
    [Crossref] [PubMed]
  8. P. Gao, H. Pu, J. Rong, W. Zhang, T. Liu, W. Liu, Y. Zhang, and H. Lu, “Resolving adjacent nanophosphors of different concentrations by excitation-based cone-beam X-ray luminescence tomography,” Biomed. Opt. Express 8(9), 3952–3965 (2017).
    [Crossref] [PubMed]
  9. A. D. Klose, “Hyperspectral excitation-resolved fluorescence tomography of quantum dots,” Opt. Lett. 34(16), 2477–2479 (2009).
    [Crossref] [PubMed]
  10. A. J. Chaudhari, S. Ahn, R. Levenson, R. D. Badawi, S. R. Cherry, and R. M. Leahy, “Excitation spectroscopy in multispectral optical fluorescence tomography: methodology, feasibility and computer simulation studies,” Phys. Med. Biol. 54(15), 4687–4704 (2009).
    [Crossref] [PubMed]
  11. A. D. Klose and T. Pöschinger, “Excitation-resolved fluorescence tomography with simplified spherical harmonics equations,” Phys. Med. Biol. 56(5), 1443–1469 (2011).
    [Crossref] [PubMed]
  12. H. Pu, W. He, G. Zhang, B. Zhang, F. Liu, Y. Zhang, J. Luo, and J. Bai, “Separating structures of different fluorophore concentrations by principal component analysis on multispectral excitation-resolved fluorescence tomography images,” Biomed. Opt. Express 4(10), 1829–1845 (2013).
    [Crossref] [PubMed]
  13. H. Pu, G. Zhang, W. He, F. Liu, H. Guang, Y. Zhang, J. Bai, and J. Luo, “Resolving fluorophores by unmixing multispectral fluorescence tomography with independent component analysis,” Phys. Med. Biol. 59(17), 5025–5042 (2014).
    [Crossref] [PubMed]
  14. W. Cong, H. Shen, and G. Wang, “Spectrally resolving and scattering-compensated x-ray luminescence/fluorescence computed tomography,” J. Biomed. Opt. 16(6), 066014 (2011).
    [Crossref] [PubMed]
  15. D. Chen, S. Zhu, X. Chen, T. Chao, X. Cao, F. Zhao, L. Huang, and J. Liang, “Quantitative cone beam X-ray luminescence tomography/X-ray computed tomography imaging,” Appl. Phys. Lett. 105(19), 191104 (2014).
    [Crossref]
  16. H. Abdi and L. J. Williams, “Principal component analysis,” WIREs Comp. Stat 2(4), 433–459 (2010).
  17. N. G. Anderson, A. P. Butler, N. J. A. Scott, N. J. Cook, J. S. Butzer, N. Schleich, M. Firsching, R. Grasset, N. de Ruiter, M. Campbell, and P. H. Butler, “Spectroscopic (multi-energy) CT distinguishes iodine and barium contrast material in MICE,” Eur. Radiol. 20(9), 2126–2134 (2010).
    [Crossref] [PubMed]
  18. H. Gao, J. F. Cai, Z. Shen, and H. Zhao, “Robust principal component analysis-based four-dimensional computed tomography,” Phys. Med. Biol. 56(11), 3181–3198 (2011).
    [Crossref] [PubMed]
  19. P. E. Svensson, J. Olsson, F. Engbrant, E. Bengtsson, and P. Razifar, “Characterization and reduction of noise in dynamic PET data using masked volumewise principal component analysis,” J. Nucl. Med. Technol. 39(1), 27–34 (2011).
    [Crossref] [PubMed]
  20. P. Razifar, H. Engler, G. Blomquist, A. Ringheim, S. Estrada, B. Långström, and M. Bergström, “Principal component analysis with pre-normalization improves the signal-to-noise ratio and image quality in positron emission tomography studies of amyloid deposits in Alzheimer’s disease,” Phys. Med. Biol. 54(11), 3595–3612 (2009).
    [Crossref] [PubMed]
  21. E. Eyal, B. N. Bloch, N. M. Rofsky, E. Furman-Haran, E. M. Genega, R. E. Lenkinski, and H. Degani, “Principal component analysis of dynamic contrast enhanced MRI in human prostate cancer,” Invest. Radiol. 45(4), 174–181 (2010).
    [Crossref] [PubMed]
  22. E. M. C. Hillman and A. Moore, “All-optical anatomical co-registration for molecular imaging of small animals using dynamic contrast,” Nat. Photonics 1(9), 526–530 (2007).
    [Crossref] [PubMed]
  23. X. Liu, D. Wang, F. Liu, and J. Bai, “Principal component analysis of dynamic fluorescence diffuse optical tomography images,” Opt. Express 18(6), 6300–6314 (2010).
    [Crossref] [PubMed]
  24. M. Schweiger, S. R. Arridge, M. Hiraoka, and D. T. Delpy, “The finite element method for the propagation of light in scattering media: Boundary and source conditions,” Med. Phys. 22(11), 1779–1792 (1995).
    [Crossref] [PubMed]
  25. P. C. Hansen, “Analysis of discrete ill-posed problems by means of the L-curve,” SIAM Rev. 34(4), 561–580 (1992).
    [Crossref]
  26. J. Feng, K. Jia, G. Yan, S. Zhu, C. Qin, Y. Lv, and J. Tian, “An optimal permissible source region strategy for multispectral bioluminescence tomography,” Opt. Express 16(20), 15640–15654 (2008).
    [Crossref] [PubMed]
  27. R. Lansford, G. Bearman, and S. E. Fraser, “Resolution of multiple green fluorescent protein color variants and dyes using two-photon microscopy and imaging spectroscopy,” J. Biomed. Opt. 6(3), 311–318 (2001).
    [Crossref] [PubMed]
  28. J. Yang, Z. Quan, D. Kong, X. Liu, and J. Lin, “Y2O3:Eu3+ microspheres: solvothermal synthesis and luminescence properties,” Cryst. Growth Des. 7(4), 730–735 (2007).
    [Crossref]
  29. R. Michels, F. Foschum, and A. Kienle, “Optical properties of fat emulsions,” Opt. Express 16(8), 5907–5925 (2008).
    [Crossref] [PubMed]
  30. L. R. Dice, “Measures of the amount of ecologic association between species,” Ecology 26(3), 297–302 (1945).
    [Crossref]
  31. L. Zhang, F. Gao, H. He, and H. Zhao, “Three-dimensional scheme for time-domain fluorescence molecular tomography based on Laplace transforms with noise-robust factors,” Opt. Express 16(10), 7214–7223 (2008).
    [Crossref] [PubMed]
  32. X. Liu, B. Zhang, J. Luo, and J. Bai, “Principal component analysis of dynamic fluorescence tomography in measurement space,” Phys. Med. Biol. 57(9), 2727–2742 (2012).
    [Crossref] [PubMed]
  33. P. R. Peres-Neto, D. A. Jackson, and K. M. Somers, “How many principal components? stopping rules for determining the number of non-trivial axes revisited,” Comput. Stat. Data Anal. 49(4), 974–997 (2005).
    [Crossref]
  34. C. Li, G. S. Mitchell, J. Dutta, S. Ahn, R. M. Leahy, and S. R. Cherry, “A three-dimensional multispectral fluorescence optical tomography imaging system for small animals based on a conical mirror design,” Opt. Express 17(9), 7571–7585 (2009).
    [Crossref] [PubMed]
  35. W. Zhang, Y. Shen, M. Liu, P. Gao, H. Pu, L. Fan, R. Jiang, Z. Liu, F. Shi, and H. Lu, “Sub-10 nm water-dispersible β-NaGdF4:X% Eu3+ nanoparticles with enhanced biocompatibility for in vivo X-ray luminescence computed tomography,” ACS Appl. Mater. Interfaces 9(46), 39985–39993 (2017).
    [Crossref] [PubMed]

2017 (2)

P. Gao, H. Pu, J. Rong, W. Zhang, T. Liu, W. Liu, Y. Zhang, and H. Lu, “Resolving adjacent nanophosphors of different concentrations by excitation-based cone-beam X-ray luminescence tomography,” Biomed. Opt. Express 8(9), 3952–3965 (2017).
[Crossref] [PubMed]

W. Zhang, Y. Shen, M. Liu, P. Gao, H. Pu, L. Fan, R. Jiang, Z. Liu, F. Shi, and H. Lu, “Sub-10 nm water-dispersible β-NaGdF4:X% Eu3+ nanoparticles with enhanced biocompatibility for in vivo X-ray luminescence computed tomography,” ACS Appl. Mater. Interfaces 9(46), 39985–39993 (2017).
[Crossref] [PubMed]

2015 (1)

X. Liu, Q. Liao, H. Wang, and Z. Yan, “Excitation-resolved cone-beam X-ray luminescence tomography,” J. Biomed. Opt. 20(7), 070501 (2015).
[Crossref] [PubMed]

2014 (4)

H. Pu, G. Zhang, W. He, F. Liu, H. Guang, Y. Zhang, J. Bai, and J. Luo, “Resolving fluorophores by unmixing multispectral fluorescence tomography with independent component analysis,” Phys. Med. Biol. 59(17), 5025–5042 (2014).
[Crossref] [PubMed]

D. Chen, S. Zhu, X. Chen, T. Chao, X. Cao, F. Zhao, L. Huang, and J. Liang, “Quantitative cone beam X-ray luminescence tomography/X-ray computed tomography imaging,” Appl. Phys. Lett. 105(19), 191104 (2014).
[Crossref]

M. Ahmad, G. Pratx, M. Bazalova, and L. Xing, “X-ray luminescence and X-ray fluorescence computed tomography: new molecular imaging modalities,” IEEE Access 2(2), 1051–1061 (2014).
[Crossref]

W. Cong and G. Wang, “X-ray fan-beam luminescence tomography,” Austin J. Biomed. Eng. 1(5), 1024 (2014).

2013 (4)

2012 (1)

X. Liu, B. Zhang, J. Luo, and J. Bai, “Principal component analysis of dynamic fluorescence tomography in measurement space,” Phys. Med. Biol. 57(9), 2727–2742 (2012).
[Crossref] [PubMed]

2011 (4)

H. Gao, J. F. Cai, Z. Shen, and H. Zhao, “Robust principal component analysis-based four-dimensional computed tomography,” Phys. Med. Biol. 56(11), 3181–3198 (2011).
[Crossref] [PubMed]

P. E. Svensson, J. Olsson, F. Engbrant, E. Bengtsson, and P. Razifar, “Characterization and reduction of noise in dynamic PET data using masked volumewise principal component analysis,” J. Nucl. Med. Technol. 39(1), 27–34 (2011).
[Crossref] [PubMed]

W. Cong, H. Shen, and G. Wang, “Spectrally resolving and scattering-compensated x-ray luminescence/fluorescence computed tomography,” J. Biomed. Opt. 16(6), 066014 (2011).
[Crossref] [PubMed]

A. D. Klose and T. Pöschinger, “Excitation-resolved fluorescence tomography with simplified spherical harmonics equations,” Phys. Med. Biol. 56(5), 1443–1469 (2011).
[Crossref] [PubMed]

2010 (5)

H. Abdi and L. J. Williams, “Principal component analysis,” WIREs Comp. Stat 2(4), 433–459 (2010).

N. G. Anderson, A. P. Butler, N. J. A. Scott, N. J. Cook, J. S. Butzer, N. Schleich, M. Firsching, R. Grasset, N. de Ruiter, M. Campbell, and P. H. Butler, “Spectroscopic (multi-energy) CT distinguishes iodine and barium contrast material in MICE,” Eur. Radiol. 20(9), 2126–2134 (2010).
[Crossref] [PubMed]

G. Pratx, C. M. Carpenter, C. Sun, and L. Xing, “X-ray luminescence computed tomography via selective excitation: a feasibility study,” IEEE Trans. Med. Imaging 29(12), 1992–1999 (2010).
[Crossref] [PubMed]

E. Eyal, B. N. Bloch, N. M. Rofsky, E. Furman-Haran, E. M. Genega, R. E. Lenkinski, and H. Degani, “Principal component analysis of dynamic contrast enhanced MRI in human prostate cancer,” Invest. Radiol. 45(4), 174–181 (2010).
[Crossref] [PubMed]

X. Liu, D. Wang, F. Liu, and J. Bai, “Principal component analysis of dynamic fluorescence diffuse optical tomography images,” Opt. Express 18(6), 6300–6314 (2010).
[Crossref] [PubMed]

2009 (4)

C. Li, G. S. Mitchell, J. Dutta, S. Ahn, R. M. Leahy, and S. R. Cherry, “A three-dimensional multispectral fluorescence optical tomography imaging system for small animals based on a conical mirror design,” Opt. Express 17(9), 7571–7585 (2009).
[Crossref] [PubMed]

A. D. Klose, “Hyperspectral excitation-resolved fluorescence tomography of quantum dots,” Opt. Lett. 34(16), 2477–2479 (2009).
[Crossref] [PubMed]

A. J. Chaudhari, S. Ahn, R. Levenson, R. D. Badawi, S. R. Cherry, and R. M. Leahy, “Excitation spectroscopy in multispectral optical fluorescence tomography: methodology, feasibility and computer simulation studies,” Phys. Med. Biol. 54(15), 4687–4704 (2009).
[Crossref] [PubMed]

P. Razifar, H. Engler, G. Blomquist, A. Ringheim, S. Estrada, B. Långström, and M. Bergström, “Principal component analysis with pre-normalization improves the signal-to-noise ratio and image quality in positron emission tomography studies of amyloid deposits in Alzheimer’s disease,” Phys. Med. Biol. 54(11), 3595–3612 (2009).
[Crossref] [PubMed]

2008 (3)

2007 (2)

J. Yang, Z. Quan, D. Kong, X. Liu, and J. Lin, “Y2O3:Eu3+ microspheres: solvothermal synthesis and luminescence properties,” Cryst. Growth Des. 7(4), 730–735 (2007).
[Crossref]

E. M. C. Hillman and A. Moore, “All-optical anatomical co-registration for molecular imaging of small animals using dynamic contrast,” Nat. Photonics 1(9), 526–530 (2007).
[Crossref] [PubMed]

2005 (1)

P. R. Peres-Neto, D. A. Jackson, and K. M. Somers, “How many principal components? stopping rules for determining the number of non-trivial axes revisited,” Comput. Stat. Data Anal. 49(4), 974–997 (2005).
[Crossref]

2001 (1)

R. Lansford, G. Bearman, and S. E. Fraser, “Resolution of multiple green fluorescent protein color variants and dyes using two-photon microscopy and imaging spectroscopy,” J. Biomed. Opt. 6(3), 311–318 (2001).
[Crossref] [PubMed]

1995 (1)

M. Schweiger, S. R. Arridge, M. Hiraoka, and D. T. Delpy, “The finite element method for the propagation of light in scattering media: Boundary and source conditions,” Med. Phys. 22(11), 1779–1792 (1995).
[Crossref] [PubMed]

1992 (1)

P. C. Hansen, “Analysis of discrete ill-posed problems by means of the L-curve,” SIAM Rev. 34(4), 561–580 (1992).
[Crossref]

1945 (1)

L. R. Dice, “Measures of the amount of ecologic association between species,” Ecology 26(3), 297–302 (1945).
[Crossref]

Abdi, H.

H. Abdi and L. J. Williams, “Principal component analysis,” WIREs Comp. Stat 2(4), 433–459 (2010).

Ahmad, M.

M. Ahmad, G. Pratx, M. Bazalova, and L. Xing, “X-ray luminescence and X-ray fluorescence computed tomography: new molecular imaging modalities,” IEEE Access 2(2), 1051–1061 (2014).
[Crossref]

Ahn, S.

A. J. Chaudhari, S. Ahn, R. Levenson, R. D. Badawi, S. R. Cherry, and R. M. Leahy, “Excitation spectroscopy in multispectral optical fluorescence tomography: methodology, feasibility and computer simulation studies,” Phys. Med. Biol. 54(15), 4687–4704 (2009).
[Crossref] [PubMed]

C. Li, G. S. Mitchell, J. Dutta, S. Ahn, R. M. Leahy, and S. R. Cherry, “A three-dimensional multispectral fluorescence optical tomography imaging system for small animals based on a conical mirror design,” Opt. Express 17(9), 7571–7585 (2009).
[Crossref] [PubMed]

Anderson, N. G.

N. G. Anderson, A. P. Butler, N. J. A. Scott, N. J. Cook, J. S. Butzer, N. Schleich, M. Firsching, R. Grasset, N. de Ruiter, M. Campbell, and P. H. Butler, “Spectroscopic (multi-energy) CT distinguishes iodine and barium contrast material in MICE,” Eur. Radiol. 20(9), 2126–2134 (2010).
[Crossref] [PubMed]

Arridge, S. R.

M. Schweiger, S. R. Arridge, M. Hiraoka, and D. T. Delpy, “The finite element method for the propagation of light in scattering media: Boundary and source conditions,” Med. Phys. 22(11), 1779–1792 (1995).
[Crossref] [PubMed]

Badawi, R. D.

A. J. Chaudhari, S. Ahn, R. Levenson, R. D. Badawi, S. R. Cherry, and R. M. Leahy, “Excitation spectroscopy in multispectral optical fluorescence tomography: methodology, feasibility and computer simulation studies,” Phys. Med. Biol. 54(15), 4687–4704 (2009).
[Crossref] [PubMed]

Bai, J.

H. Pu, G. Zhang, W. He, F. Liu, H. Guang, Y. Zhang, J. Bai, and J. Luo, “Resolving fluorophores by unmixing multispectral fluorescence tomography with independent component analysis,” Phys. Med. Biol. 59(17), 5025–5042 (2014).
[Crossref] [PubMed]

H. Pu, W. He, G. Zhang, B. Zhang, F. Liu, Y. Zhang, J. Luo, and J. Bai, “Separating structures of different fluorophore concentrations by principal component analysis on multispectral excitation-resolved fluorescence tomography images,” Biomed. Opt. Express 4(10), 1829–1845 (2013).
[Crossref] [PubMed]

X. Liu, B. Zhang, J. Luo, and J. Bai, “Principal component analysis of dynamic fluorescence tomography in measurement space,” Phys. Med. Biol. 57(9), 2727–2742 (2012).
[Crossref] [PubMed]

X. Liu, D. Wang, F. Liu, and J. Bai, “Principal component analysis of dynamic fluorescence diffuse optical tomography images,” Opt. Express 18(6), 6300–6314 (2010).
[Crossref] [PubMed]

Bazalova, M.

M. Ahmad, G. Pratx, M. Bazalova, and L. Xing, “X-ray luminescence and X-ray fluorescence computed tomography: new molecular imaging modalities,” IEEE Access 2(2), 1051–1061 (2014).
[Crossref]

Bearman, G.

R. Lansford, G. Bearman, and S. E. Fraser, “Resolution of multiple green fluorescent protein color variants and dyes using two-photon microscopy and imaging spectroscopy,” J. Biomed. Opt. 6(3), 311–318 (2001).
[Crossref] [PubMed]

Bec, J.

Bengtsson, E.

P. E. Svensson, J. Olsson, F. Engbrant, E. Bengtsson, and P. Razifar, “Characterization and reduction of noise in dynamic PET data using masked volumewise principal component analysis,” J. Nucl. Med. Technol. 39(1), 27–34 (2011).
[Crossref] [PubMed]

Bergström, M.

P. Razifar, H. Engler, G. Blomquist, A. Ringheim, S. Estrada, B. Långström, and M. Bergström, “Principal component analysis with pre-normalization improves the signal-to-noise ratio and image quality in positron emission tomography studies of amyloid deposits in Alzheimer’s disease,” Phys. Med. Biol. 54(11), 3595–3612 (2009).
[Crossref] [PubMed]

Bloch, B. N.

E. Eyal, B. N. Bloch, N. M. Rofsky, E. Furman-Haran, E. M. Genega, R. E. Lenkinski, and H. Degani, “Principal component analysis of dynamic contrast enhanced MRI in human prostate cancer,” Invest. Radiol. 45(4), 174–181 (2010).
[Crossref] [PubMed]

Blomquist, G.

P. Razifar, H. Engler, G. Blomquist, A. Ringheim, S. Estrada, B. Långström, and M. Bergström, “Principal component analysis with pre-normalization improves the signal-to-noise ratio and image quality in positron emission tomography studies of amyloid deposits in Alzheimer’s disease,” Phys. Med. Biol. 54(11), 3595–3612 (2009).
[Crossref] [PubMed]

Butler, A. P.

N. G. Anderson, A. P. Butler, N. J. A. Scott, N. J. Cook, J. S. Butzer, N. Schleich, M. Firsching, R. Grasset, N. de Ruiter, M. Campbell, and P. H. Butler, “Spectroscopic (multi-energy) CT distinguishes iodine and barium contrast material in MICE,” Eur. Radiol. 20(9), 2126–2134 (2010).
[Crossref] [PubMed]

Butler, P. H.

N. G. Anderson, A. P. Butler, N. J. A. Scott, N. J. Cook, J. S. Butzer, N. Schleich, M. Firsching, R. Grasset, N. de Ruiter, M. Campbell, and P. H. Butler, “Spectroscopic (multi-energy) CT distinguishes iodine and barium contrast material in MICE,” Eur. Radiol. 20(9), 2126–2134 (2010).
[Crossref] [PubMed]

Butzer, J. S.

N. G. Anderson, A. P. Butler, N. J. A. Scott, N. J. Cook, J. S. Butzer, N. Schleich, M. Firsching, R. Grasset, N. de Ruiter, M. Campbell, and P. H. Butler, “Spectroscopic (multi-energy) CT distinguishes iodine and barium contrast material in MICE,” Eur. Radiol. 20(9), 2126–2134 (2010).
[Crossref] [PubMed]

Cai, J. F.

H. Gao, J. F. Cai, Z. Shen, and H. Zhao, “Robust principal component analysis-based four-dimensional computed tomography,” Phys. Med. Biol. 56(11), 3181–3198 (2011).
[Crossref] [PubMed]

Campbell, M.

N. G. Anderson, A. P. Butler, N. J. A. Scott, N. J. Cook, J. S. Butzer, N. Schleich, M. Firsching, R. Grasset, N. de Ruiter, M. Campbell, and P. H. Butler, “Spectroscopic (multi-energy) CT distinguishes iodine and barium contrast material in MICE,” Eur. Radiol. 20(9), 2126–2134 (2010).
[Crossref] [PubMed]

Cao, X.

D. Chen, S. Zhu, X. Chen, T. Chao, X. Cao, F. Zhao, L. Huang, and J. Liang, “Quantitative cone beam X-ray luminescence tomography/X-ray computed tomography imaging,” Appl. Phys. Lett. 105(19), 191104 (2014).
[Crossref]

Carpenter, C. M.

G. Pratx, C. M. Carpenter, C. Sun, and L. Xing, “X-ray luminescence computed tomography via selective excitation: a feasibility study,” IEEE Trans. Med. Imaging 29(12), 1992–1999 (2010).
[Crossref] [PubMed]

Chao, T.

D. Chen, S. Zhu, X. Chen, T. Chao, X. Cao, F. Zhao, L. Huang, and J. Liang, “Quantitative cone beam X-ray luminescence tomography/X-ray computed tomography imaging,” Appl. Phys. Lett. 105(19), 191104 (2014).
[Crossref]

Chaudhari, A. J.

A. J. Chaudhari, S. Ahn, R. Levenson, R. D. Badawi, S. R. Cherry, and R. M. Leahy, “Excitation spectroscopy in multispectral optical fluorescence tomography: methodology, feasibility and computer simulation studies,” Phys. Med. Biol. 54(15), 4687–4704 (2009).
[Crossref] [PubMed]

Chen, D.

D. Chen, S. Zhu, X. Chen, T. Chao, X. Cao, F. Zhao, L. Huang, and J. Liang, “Quantitative cone beam X-ray luminescence tomography/X-ray computed tomography imaging,” Appl. Phys. Lett. 105(19), 191104 (2014).
[Crossref]

D. Chen, S. Zhu, H. Yi, X. Zhang, D. Chen, J. Liang, and J. Tian, “Cone beam X-ray luminescence computed tomography: A feasibility study,” Med. Phys. 40(3), 031111 (2013).
[Crossref] [PubMed]

D. Chen, S. Zhu, H. Yi, X. Zhang, D. Chen, J. Liang, and J. Tian, “Cone beam X-ray luminescence computed tomography: A feasibility study,” Med. Phys. 40(3), 031111 (2013).
[Crossref] [PubMed]

Chen, X.

D. Chen, S. Zhu, X. Chen, T. Chao, X. Cao, F. Zhao, L. Huang, and J. Liang, “Quantitative cone beam X-ray luminescence tomography/X-ray computed tomography imaging,” Appl. Phys. Lett. 105(19), 191104 (2014).
[Crossref]

Cherry, S. R.

Cong, W.

W. Cong and G. Wang, “X-ray fan-beam luminescence tomography,” Austin J. Biomed. Eng. 1(5), 1024 (2014).

W. Cong, H. Shen, and G. Wang, “Spectrally resolving and scattering-compensated x-ray luminescence/fluorescence computed tomography,” J. Biomed. Opt. 16(6), 066014 (2011).
[Crossref] [PubMed]

Cook, N. J.

N. G. Anderson, A. P. Butler, N. J. A. Scott, N. J. Cook, J. S. Butzer, N. Schleich, M. Firsching, R. Grasset, N. de Ruiter, M. Campbell, and P. H. Butler, “Spectroscopic (multi-energy) CT distinguishes iodine and barium contrast material in MICE,” Eur. Radiol. 20(9), 2126–2134 (2010).
[Crossref] [PubMed]

de Ruiter, N.

N. G. Anderson, A. P. Butler, N. J. A. Scott, N. J. Cook, J. S. Butzer, N. Schleich, M. Firsching, R. Grasset, N. de Ruiter, M. Campbell, and P. H. Butler, “Spectroscopic (multi-energy) CT distinguishes iodine and barium contrast material in MICE,” Eur. Radiol. 20(9), 2126–2134 (2010).
[Crossref] [PubMed]

Degani, H.

E. Eyal, B. N. Bloch, N. M. Rofsky, E. Furman-Haran, E. M. Genega, R. E. Lenkinski, and H. Degani, “Principal component analysis of dynamic contrast enhanced MRI in human prostate cancer,” Invest. Radiol. 45(4), 174–181 (2010).
[Crossref] [PubMed]

Delpy, D. T.

M. Schweiger, S. R. Arridge, M. Hiraoka, and D. T. Delpy, “The finite element method for the propagation of light in scattering media: Boundary and source conditions,” Med. Phys. 22(11), 1779–1792 (1995).
[Crossref] [PubMed]

Di, K.

Dice, L. R.

L. R. Dice, “Measures of the amount of ecologic association between species,” Ecology 26(3), 297–302 (1945).
[Crossref]

Dutta, J.

Engbrant, F.

P. E. Svensson, J. Olsson, F. Engbrant, E. Bengtsson, and P. Razifar, “Characterization and reduction of noise in dynamic PET data using masked volumewise principal component analysis,” J. Nucl. Med. Technol. 39(1), 27–34 (2011).
[Crossref] [PubMed]

Engler, H.

P. Razifar, H. Engler, G. Blomquist, A. Ringheim, S. Estrada, B. Långström, and M. Bergström, “Principal component analysis with pre-normalization improves the signal-to-noise ratio and image quality in positron emission tomography studies of amyloid deposits in Alzheimer’s disease,” Phys. Med. Biol. 54(11), 3595–3612 (2009).
[Crossref] [PubMed]

Estrada, S.

P. Razifar, H. Engler, G. Blomquist, A. Ringheim, S. Estrada, B. Långström, and M. Bergström, “Principal component analysis with pre-normalization improves the signal-to-noise ratio and image quality in positron emission tomography studies of amyloid deposits in Alzheimer’s disease,” Phys. Med. Biol. 54(11), 3595–3612 (2009).
[Crossref] [PubMed]

Eyal, E.

E. Eyal, B. N. Bloch, N. M. Rofsky, E. Furman-Haran, E. M. Genega, R. E. Lenkinski, and H. Degani, “Principal component analysis of dynamic contrast enhanced MRI in human prostate cancer,” Invest. Radiol. 45(4), 174–181 (2010).
[Crossref] [PubMed]

Fan, L.

W. Zhang, Y. Shen, M. Liu, P. Gao, H. Pu, L. Fan, R. Jiang, Z. Liu, F. Shi, and H. Lu, “Sub-10 nm water-dispersible β-NaGdF4:X% Eu3+ nanoparticles with enhanced biocompatibility for in vivo X-ray luminescence computed tomography,” ACS Appl. Mater. Interfaces 9(46), 39985–39993 (2017).
[Crossref] [PubMed]

Feng, J.

Firsching, M.

N. G. Anderson, A. P. Butler, N. J. A. Scott, N. J. Cook, J. S. Butzer, N. Schleich, M. Firsching, R. Grasset, N. de Ruiter, M. Campbell, and P. H. Butler, “Spectroscopic (multi-energy) CT distinguishes iodine and barium contrast material in MICE,” Eur. Radiol. 20(9), 2126–2134 (2010).
[Crossref] [PubMed]

Foschum, F.

Fraser, S. E.

R. Lansford, G. Bearman, and S. E. Fraser, “Resolution of multiple green fluorescent protein color variants and dyes using two-photon microscopy and imaging spectroscopy,” J. Biomed. Opt. 6(3), 311–318 (2001).
[Crossref] [PubMed]

Furman-Haran, E.

E. Eyal, B. N. Bloch, N. M. Rofsky, E. Furman-Haran, E. M. Genega, R. E. Lenkinski, and H. Degani, “Principal component analysis of dynamic contrast enhanced MRI in human prostate cancer,” Invest. Radiol. 45(4), 174–181 (2010).
[Crossref] [PubMed]

Gao, F.

Gao, H.

H. Gao, J. F. Cai, Z. Shen, and H. Zhao, “Robust principal component analysis-based four-dimensional computed tomography,” Phys. Med. Biol. 56(11), 3181–3198 (2011).
[Crossref] [PubMed]

Gao, P.

P. Gao, H. Pu, J. Rong, W. Zhang, T. Liu, W. Liu, Y. Zhang, and H. Lu, “Resolving adjacent nanophosphors of different concentrations by excitation-based cone-beam X-ray luminescence tomography,” Biomed. Opt. Express 8(9), 3952–3965 (2017).
[Crossref] [PubMed]

W. Zhang, Y. Shen, M. Liu, P. Gao, H. Pu, L. Fan, R. Jiang, Z. Liu, F. Shi, and H. Lu, “Sub-10 nm water-dispersible β-NaGdF4:X% Eu3+ nanoparticles with enhanced biocompatibility for in vivo X-ray luminescence computed tomography,” ACS Appl. Mater. Interfaces 9(46), 39985–39993 (2017).
[Crossref] [PubMed]

Genega, E. M.

E. Eyal, B. N. Bloch, N. M. Rofsky, E. Furman-Haran, E. M. Genega, R. E. Lenkinski, and H. Degani, “Principal component analysis of dynamic contrast enhanced MRI in human prostate cancer,” Invest. Radiol. 45(4), 174–181 (2010).
[Crossref] [PubMed]

Grasset, R.

N. G. Anderson, A. P. Butler, N. J. A. Scott, N. J. Cook, J. S. Butzer, N. Schleich, M. Firsching, R. Grasset, N. de Ruiter, M. Campbell, and P. H. Butler, “Spectroscopic (multi-energy) CT distinguishes iodine and barium contrast material in MICE,” Eur. Radiol. 20(9), 2126–2134 (2010).
[Crossref] [PubMed]

Guang, H.

H. Pu, G. Zhang, W. He, F. Liu, H. Guang, Y. Zhang, J. Bai, and J. Luo, “Resolving fluorophores by unmixing multispectral fluorescence tomography with independent component analysis,” Phys. Med. Biol. 59(17), 5025–5042 (2014).
[Crossref] [PubMed]

Hansen, P. C.

P. C. Hansen, “Analysis of discrete ill-posed problems by means of the L-curve,” SIAM Rev. 34(4), 561–580 (1992).
[Crossref]

He, H.

He, W.

H. Pu, G. Zhang, W. He, F. Liu, H. Guang, Y. Zhang, J. Bai, and J. Luo, “Resolving fluorophores by unmixing multispectral fluorescence tomography with independent component analysis,” Phys. Med. Biol. 59(17), 5025–5042 (2014).
[Crossref] [PubMed]

H. Pu, W. He, G. Zhang, B. Zhang, F. Liu, Y. Zhang, J. Luo, and J. Bai, “Separating structures of different fluorophore concentrations by principal component analysis on multispectral excitation-resolved fluorescence tomography images,” Biomed. Opt. Express 4(10), 1829–1845 (2013).
[Crossref] [PubMed]

Hillman, E. M. C.

E. M. C. Hillman and A. Moore, “All-optical anatomical co-registration for molecular imaging of small animals using dynamic contrast,” Nat. Photonics 1(9), 526–530 (2007).
[Crossref] [PubMed]

Hiraoka, M.

M. Schweiger, S. R. Arridge, M. Hiraoka, and D. T. Delpy, “The finite element method for the propagation of light in scattering media: Boundary and source conditions,” Med. Phys. 22(11), 1779–1792 (1995).
[Crossref] [PubMed]

Huang, L.

D. Chen, S. Zhu, X. Chen, T. Chao, X. Cao, F. Zhao, L. Huang, and J. Liang, “Quantitative cone beam X-ray luminescence tomography/X-ray computed tomography imaging,” Appl. Phys. Lett. 105(19), 191104 (2014).
[Crossref]

Jackson, D. A.

P. R. Peres-Neto, D. A. Jackson, and K. M. Somers, “How many principal components? stopping rules for determining the number of non-trivial axes revisited,” Comput. Stat. Data Anal. 49(4), 974–997 (2005).
[Crossref]

Jia, K.

Jiang, R.

W. Zhang, Y. Shen, M. Liu, P. Gao, H. Pu, L. Fan, R. Jiang, Z. Liu, F. Shi, and H. Lu, “Sub-10 nm water-dispersible β-NaGdF4:X% Eu3+ nanoparticles with enhanced biocompatibility for in vivo X-ray luminescence computed tomography,” ACS Appl. Mater. Interfaces 9(46), 39985–39993 (2017).
[Crossref] [PubMed]

Kienle, A.

Klose, A. D.

A. D. Klose and T. Pöschinger, “Excitation-resolved fluorescence tomography with simplified spherical harmonics equations,” Phys. Med. Biol. 56(5), 1443–1469 (2011).
[Crossref] [PubMed]

A. D. Klose, “Hyperspectral excitation-resolved fluorescence tomography of quantum dots,” Opt. Lett. 34(16), 2477–2479 (2009).
[Crossref] [PubMed]

Kong, D.

J. Yang, Z. Quan, D. Kong, X. Liu, and J. Lin, “Y2O3:Eu3+ microspheres: solvothermal synthesis and luminescence properties,” Cryst. Growth Des. 7(4), 730–735 (2007).
[Crossref]

Långström, B.

P. Razifar, H. Engler, G. Blomquist, A. Ringheim, S. Estrada, B. Långström, and M. Bergström, “Principal component analysis with pre-normalization improves the signal-to-noise ratio and image quality in positron emission tomography studies of amyloid deposits in Alzheimer’s disease,” Phys. Med. Biol. 54(11), 3595–3612 (2009).
[Crossref] [PubMed]

Lansford, R.

R. Lansford, G. Bearman, and S. E. Fraser, “Resolution of multiple green fluorescent protein color variants and dyes using two-photon microscopy and imaging spectroscopy,” J. Biomed. Opt. 6(3), 311–318 (2001).
[Crossref] [PubMed]

Leahy, R. M.

A. J. Chaudhari, S. Ahn, R. Levenson, R. D. Badawi, S. R. Cherry, and R. M. Leahy, “Excitation spectroscopy in multispectral optical fluorescence tomography: methodology, feasibility and computer simulation studies,” Phys. Med. Biol. 54(15), 4687–4704 (2009).
[Crossref] [PubMed]

C. Li, G. S. Mitchell, J. Dutta, S. Ahn, R. M. Leahy, and S. R. Cherry, “A three-dimensional multispectral fluorescence optical tomography imaging system for small animals based on a conical mirror design,” Opt. Express 17(9), 7571–7585 (2009).
[Crossref] [PubMed]

Lenkinski, R. E.

E. Eyal, B. N. Bloch, N. M. Rofsky, E. Furman-Haran, E. M. Genega, R. E. Lenkinski, and H. Degani, “Principal component analysis of dynamic contrast enhanced MRI in human prostate cancer,” Invest. Radiol. 45(4), 174–181 (2010).
[Crossref] [PubMed]

Levenson, R.

A. J. Chaudhari, S. Ahn, R. Levenson, R. D. Badawi, S. R. Cherry, and R. M. Leahy, “Excitation spectroscopy in multispectral optical fluorescence tomography: methodology, feasibility and computer simulation studies,” Phys. Med. Biol. 54(15), 4687–4704 (2009).
[Crossref] [PubMed]

Li, C.

Liang, J.

D. Chen, S. Zhu, X. Chen, T. Chao, X. Cao, F. Zhao, L. Huang, and J. Liang, “Quantitative cone beam X-ray luminescence tomography/X-ray computed tomography imaging,” Appl. Phys. Lett. 105(19), 191104 (2014).
[Crossref]

D. Chen, S. Zhu, H. Yi, X. Zhang, D. Chen, J. Liang, and J. Tian, “Cone beam X-ray luminescence computed tomography: A feasibility study,” Med. Phys. 40(3), 031111 (2013).
[Crossref] [PubMed]

Liao, Q.

X. Liu, Q. Liao, H. Wang, and Z. Yan, “Excitation-resolved cone-beam X-ray luminescence tomography,” J. Biomed. Opt. 20(7), 070501 (2015).
[Crossref] [PubMed]

X. Liu, Q. Liao, and H. Wang, “In vivo X-ray luminescence tomographic imaging with single-view data,” Opt. Lett. 38(22), 4530–4533 (2013).
[Crossref] [PubMed]

Lin, J.

J. Yang, Z. Quan, D. Kong, X. Liu, and J. Lin, “Y2O3:Eu3+ microspheres: solvothermal synthesis and luminescence properties,” Cryst. Growth Des. 7(4), 730–735 (2007).
[Crossref]

Liu, F.

Liu, M.

W. Zhang, Y. Shen, M. Liu, P. Gao, H. Pu, L. Fan, R. Jiang, Z. Liu, F. Shi, and H. Lu, “Sub-10 nm water-dispersible β-NaGdF4:X% Eu3+ nanoparticles with enhanced biocompatibility for in vivo X-ray luminescence computed tomography,” ACS Appl. Mater. Interfaces 9(46), 39985–39993 (2017).
[Crossref] [PubMed]

Liu, T.

Liu, W.

Liu, X.

X. Liu, Q. Liao, H. Wang, and Z. Yan, “Excitation-resolved cone-beam X-ray luminescence tomography,” J. Biomed. Opt. 20(7), 070501 (2015).
[Crossref] [PubMed]

X. Liu, Q. Liao, and H. Wang, “In vivo X-ray luminescence tomographic imaging with single-view data,” Opt. Lett. 38(22), 4530–4533 (2013).
[Crossref] [PubMed]

X. Liu, B. Zhang, J. Luo, and J. Bai, “Principal component analysis of dynamic fluorescence tomography in measurement space,” Phys. Med. Biol. 57(9), 2727–2742 (2012).
[Crossref] [PubMed]

X. Liu, D. Wang, F. Liu, and J. Bai, “Principal component analysis of dynamic fluorescence diffuse optical tomography images,” Opt. Express 18(6), 6300–6314 (2010).
[Crossref] [PubMed]

J. Yang, Z. Quan, D. Kong, X. Liu, and J. Lin, “Y2O3:Eu3+ microspheres: solvothermal synthesis and luminescence properties,” Cryst. Growth Des. 7(4), 730–735 (2007).
[Crossref]

Liu, Z.

W. Zhang, Y. Shen, M. Liu, P. Gao, H. Pu, L. Fan, R. Jiang, Z. Liu, F. Shi, and H. Lu, “Sub-10 nm water-dispersible β-NaGdF4:X% Eu3+ nanoparticles with enhanced biocompatibility for in vivo X-ray luminescence computed tomography,” ACS Appl. Mater. Interfaces 9(46), 39985–39993 (2017).
[Crossref] [PubMed]

Lu, H.

W. Zhang, Y. Shen, M. Liu, P. Gao, H. Pu, L. Fan, R. Jiang, Z. Liu, F. Shi, and H. Lu, “Sub-10 nm water-dispersible β-NaGdF4:X% Eu3+ nanoparticles with enhanced biocompatibility for in vivo X-ray luminescence computed tomography,” ACS Appl. Mater. Interfaces 9(46), 39985–39993 (2017).
[Crossref] [PubMed]

P. Gao, H. Pu, J. Rong, W. Zhang, T. Liu, W. Liu, Y. Zhang, and H. Lu, “Resolving adjacent nanophosphors of different concentrations by excitation-based cone-beam X-ray luminescence tomography,” Biomed. Opt. Express 8(9), 3952–3965 (2017).
[Crossref] [PubMed]

Luo, J.

H. Pu, G. Zhang, W. He, F. Liu, H. Guang, Y. Zhang, J. Bai, and J. Luo, “Resolving fluorophores by unmixing multispectral fluorescence tomography with independent component analysis,” Phys. Med. Biol. 59(17), 5025–5042 (2014).
[Crossref] [PubMed]

H. Pu, W. He, G. Zhang, B. Zhang, F. Liu, Y. Zhang, J. Luo, and J. Bai, “Separating structures of different fluorophore concentrations by principal component analysis on multispectral excitation-resolved fluorescence tomography images,” Biomed. Opt. Express 4(10), 1829–1845 (2013).
[Crossref] [PubMed]

X. Liu, B. Zhang, J. Luo, and J. Bai, “Principal component analysis of dynamic fluorescence tomography in measurement space,” Phys. Med. Biol. 57(9), 2727–2742 (2012).
[Crossref] [PubMed]

Lv, Y.

Michels, R.

Mitchell, G. S.

Moore, A.

E. M. C. Hillman and A. Moore, “All-optical anatomical co-registration for molecular imaging of small animals using dynamic contrast,” Nat. Photonics 1(9), 526–530 (2007).
[Crossref] [PubMed]

Olsson, J.

P. E. Svensson, J. Olsson, F. Engbrant, E. Bengtsson, and P. Razifar, “Characterization and reduction of noise in dynamic PET data using masked volumewise principal component analysis,” J. Nucl. Med. Technol. 39(1), 27–34 (2011).
[Crossref] [PubMed]

Peres-Neto, P. R.

P. R. Peres-Neto, D. A. Jackson, and K. M. Somers, “How many principal components? stopping rules for determining the number of non-trivial axes revisited,” Comput. Stat. Data Anal. 49(4), 974–997 (2005).
[Crossref]

Pöschinger, T.

A. D. Klose and T. Pöschinger, “Excitation-resolved fluorescence tomography with simplified spherical harmonics equations,” Phys. Med. Biol. 56(5), 1443–1469 (2011).
[Crossref] [PubMed]

Pratx, G.

M. Ahmad, G. Pratx, M. Bazalova, and L. Xing, “X-ray luminescence and X-ray fluorescence computed tomography: new molecular imaging modalities,” IEEE Access 2(2), 1051–1061 (2014).
[Crossref]

G. Pratx, C. M. Carpenter, C. Sun, and L. Xing, “X-ray luminescence computed tomography via selective excitation: a feasibility study,” IEEE Trans. Med. Imaging 29(12), 1992–1999 (2010).
[Crossref] [PubMed]

Pu, H.

P. Gao, H. Pu, J. Rong, W. Zhang, T. Liu, W. Liu, Y. Zhang, and H. Lu, “Resolving adjacent nanophosphors of different concentrations by excitation-based cone-beam X-ray luminescence tomography,” Biomed. Opt. Express 8(9), 3952–3965 (2017).
[Crossref] [PubMed]

W. Zhang, Y. Shen, M. Liu, P. Gao, H. Pu, L. Fan, R. Jiang, Z. Liu, F. Shi, and H. Lu, “Sub-10 nm water-dispersible β-NaGdF4:X% Eu3+ nanoparticles with enhanced biocompatibility for in vivo X-ray luminescence computed tomography,” ACS Appl. Mater. Interfaces 9(46), 39985–39993 (2017).
[Crossref] [PubMed]

H. Pu, G. Zhang, W. He, F. Liu, H. Guang, Y. Zhang, J. Bai, and J. Luo, “Resolving fluorophores by unmixing multispectral fluorescence tomography with independent component analysis,” Phys. Med. Biol. 59(17), 5025–5042 (2014).
[Crossref] [PubMed]

H. Pu, W. He, G. Zhang, B. Zhang, F. Liu, Y. Zhang, J. Luo, and J. Bai, “Separating structures of different fluorophore concentrations by principal component analysis on multispectral excitation-resolved fluorescence tomography images,” Biomed. Opt. Express 4(10), 1829–1845 (2013).
[Crossref] [PubMed]

Qin, C.

Quan, Z.

J. Yang, Z. Quan, D. Kong, X. Liu, and J. Lin, “Y2O3:Eu3+ microspheres: solvothermal synthesis and luminescence properties,” Cryst. Growth Des. 7(4), 730–735 (2007).
[Crossref]

Razifar, P.

P. E. Svensson, J. Olsson, F. Engbrant, E. Bengtsson, and P. Razifar, “Characterization and reduction of noise in dynamic PET data using masked volumewise principal component analysis,” J. Nucl. Med. Technol. 39(1), 27–34 (2011).
[Crossref] [PubMed]

P. Razifar, H. Engler, G. Blomquist, A. Ringheim, S. Estrada, B. Långström, and M. Bergström, “Principal component analysis with pre-normalization improves the signal-to-noise ratio and image quality in positron emission tomography studies of amyloid deposits in Alzheimer’s disease,” Phys. Med. Biol. 54(11), 3595–3612 (2009).
[Crossref] [PubMed]

Ringheim, A.

P. Razifar, H. Engler, G. Blomquist, A. Ringheim, S. Estrada, B. Långström, and M. Bergström, “Principal component analysis with pre-normalization improves the signal-to-noise ratio and image quality in positron emission tomography studies of amyloid deposits in Alzheimer’s disease,” Phys. Med. Biol. 54(11), 3595–3612 (2009).
[Crossref] [PubMed]

Rofsky, N. M.

E. Eyal, B. N. Bloch, N. M. Rofsky, E. Furman-Haran, E. M. Genega, R. E. Lenkinski, and H. Degani, “Principal component analysis of dynamic contrast enhanced MRI in human prostate cancer,” Invest. Radiol. 45(4), 174–181 (2010).
[Crossref] [PubMed]

Rong, J.

Schleich, N.

N. G. Anderson, A. P. Butler, N. J. A. Scott, N. J. Cook, J. S. Butzer, N. Schleich, M. Firsching, R. Grasset, N. de Ruiter, M. Campbell, and P. H. Butler, “Spectroscopic (multi-energy) CT distinguishes iodine and barium contrast material in MICE,” Eur. Radiol. 20(9), 2126–2134 (2010).
[Crossref] [PubMed]

Schweiger, M.

M. Schweiger, S. R. Arridge, M. Hiraoka, and D. T. Delpy, “The finite element method for the propagation of light in scattering media: Boundary and source conditions,” Med. Phys. 22(11), 1779–1792 (1995).
[Crossref] [PubMed]

Scott, N. J. A.

N. G. Anderson, A. P. Butler, N. J. A. Scott, N. J. Cook, J. S. Butzer, N. Schleich, M. Firsching, R. Grasset, N. de Ruiter, M. Campbell, and P. H. Butler, “Spectroscopic (multi-energy) CT distinguishes iodine and barium contrast material in MICE,” Eur. Radiol. 20(9), 2126–2134 (2010).
[Crossref] [PubMed]

Shen, H.

W. Cong, H. Shen, and G. Wang, “Spectrally resolving and scattering-compensated x-ray luminescence/fluorescence computed tomography,” J. Biomed. Opt. 16(6), 066014 (2011).
[Crossref] [PubMed]

Shen, Y.

W. Zhang, Y. Shen, M. Liu, P. Gao, H. Pu, L. Fan, R. Jiang, Z. Liu, F. Shi, and H. Lu, “Sub-10 nm water-dispersible β-NaGdF4:X% Eu3+ nanoparticles with enhanced biocompatibility for in vivo X-ray luminescence computed tomography,” ACS Appl. Mater. Interfaces 9(46), 39985–39993 (2017).
[Crossref] [PubMed]

Shen, Z.

H. Gao, J. F. Cai, Z. Shen, and H. Zhao, “Robust principal component analysis-based four-dimensional computed tomography,” Phys. Med. Biol. 56(11), 3181–3198 (2011).
[Crossref] [PubMed]

Shi, F.

W. Zhang, Y. Shen, M. Liu, P. Gao, H. Pu, L. Fan, R. Jiang, Z. Liu, F. Shi, and H. Lu, “Sub-10 nm water-dispersible β-NaGdF4:X% Eu3+ nanoparticles with enhanced biocompatibility for in vivo X-ray luminescence computed tomography,” ACS Appl. Mater. Interfaces 9(46), 39985–39993 (2017).
[Crossref] [PubMed]

Somers, K. M.

P. R. Peres-Neto, D. A. Jackson, and K. M. Somers, “How many principal components? stopping rules for determining the number of non-trivial axes revisited,” Comput. Stat. Data Anal. 49(4), 974–997 (2005).
[Crossref]

Sun, C.

G. Pratx, C. M. Carpenter, C. Sun, and L. Xing, “X-ray luminescence computed tomography via selective excitation: a feasibility study,” IEEE Trans. Med. Imaging 29(12), 1992–1999 (2010).
[Crossref] [PubMed]

Svensson, P. E.

P. E. Svensson, J. Olsson, F. Engbrant, E. Bengtsson, and P. Razifar, “Characterization and reduction of noise in dynamic PET data using masked volumewise principal component analysis,” J. Nucl. Med. Technol. 39(1), 27–34 (2011).
[Crossref] [PubMed]

Tian, J.

D. Chen, S. Zhu, H. Yi, X. Zhang, D. Chen, J. Liang, and J. Tian, “Cone beam X-ray luminescence computed tomography: A feasibility study,” Med. Phys. 40(3), 031111 (2013).
[Crossref] [PubMed]

J. Feng, K. Jia, G. Yan, S. Zhu, C. Qin, Y. Lv, and J. Tian, “An optimal permissible source region strategy for multispectral bioluminescence tomography,” Opt. Express 16(20), 15640–15654 (2008).
[Crossref] [PubMed]

Wang, D.

Wang, G.

W. Cong and G. Wang, “X-ray fan-beam luminescence tomography,” Austin J. Biomed. Eng. 1(5), 1024 (2014).

W. Cong, H. Shen, and G. Wang, “Spectrally resolving and scattering-compensated x-ray luminescence/fluorescence computed tomography,” J. Biomed. Opt. 16(6), 066014 (2011).
[Crossref] [PubMed]

Wang, H.

X. Liu, Q. Liao, H. Wang, and Z. Yan, “Excitation-resolved cone-beam X-ray luminescence tomography,” J. Biomed. Opt. 20(7), 070501 (2015).
[Crossref] [PubMed]

X. Liu, Q. Liao, and H. Wang, “In vivo X-ray luminescence tomographic imaging with single-view data,” Opt. Lett. 38(22), 4530–4533 (2013).
[Crossref] [PubMed]

Williams, L. J.

H. Abdi and L. J. Williams, “Principal component analysis,” WIREs Comp. Stat 2(4), 433–459 (2010).

Xing, L.

M. Ahmad, G. Pratx, M. Bazalova, and L. Xing, “X-ray luminescence and X-ray fluorescence computed tomography: new molecular imaging modalities,” IEEE Access 2(2), 1051–1061 (2014).
[Crossref]

G. Pratx, C. M. Carpenter, C. Sun, and L. Xing, “X-ray luminescence computed tomography via selective excitation: a feasibility study,” IEEE Trans. Med. Imaging 29(12), 1992–1999 (2010).
[Crossref] [PubMed]

Yan, G.

Yan, Z.

X. Liu, Q. Liao, H. Wang, and Z. Yan, “Excitation-resolved cone-beam X-ray luminescence tomography,” J. Biomed. Opt. 20(7), 070501 (2015).
[Crossref] [PubMed]

Yang, J.

J. Yang, Z. Quan, D. Kong, X. Liu, and J. Lin, “Y2O3:Eu3+ microspheres: solvothermal synthesis and luminescence properties,” Cryst. Growth Des. 7(4), 730–735 (2007).
[Crossref]

Yi, H.

D. Chen, S. Zhu, H. Yi, X. Zhang, D. Chen, J. Liang, and J. Tian, “Cone beam X-ray luminescence computed tomography: A feasibility study,” Med. Phys. 40(3), 031111 (2013).
[Crossref] [PubMed]

Zhang, B.

Zhang, G.

H. Pu, G. Zhang, W. He, F. Liu, H. Guang, Y. Zhang, J. Bai, and J. Luo, “Resolving fluorophores by unmixing multispectral fluorescence tomography with independent component analysis,” Phys. Med. Biol. 59(17), 5025–5042 (2014).
[Crossref] [PubMed]

H. Pu, W. He, G. Zhang, B. Zhang, F. Liu, Y. Zhang, J. Luo, and J. Bai, “Separating structures of different fluorophore concentrations by principal component analysis on multispectral excitation-resolved fluorescence tomography images,” Biomed. Opt. Express 4(10), 1829–1845 (2013).
[Crossref] [PubMed]

Zhang, L.

Zhang, W.

P. Gao, H. Pu, J. Rong, W. Zhang, T. Liu, W. Liu, Y. Zhang, and H. Lu, “Resolving adjacent nanophosphors of different concentrations by excitation-based cone-beam X-ray luminescence tomography,” Biomed. Opt. Express 8(9), 3952–3965 (2017).
[Crossref] [PubMed]

W. Zhang, Y. Shen, M. Liu, P. Gao, H. Pu, L. Fan, R. Jiang, Z. Liu, F. Shi, and H. Lu, “Sub-10 nm water-dispersible β-NaGdF4:X% Eu3+ nanoparticles with enhanced biocompatibility for in vivo X-ray luminescence computed tomography,” ACS Appl. Mater. Interfaces 9(46), 39985–39993 (2017).
[Crossref] [PubMed]

Zhang, X.

D. Chen, S. Zhu, H. Yi, X. Zhang, D. Chen, J. Liang, and J. Tian, “Cone beam X-ray luminescence computed tomography: A feasibility study,” Med. Phys. 40(3), 031111 (2013).
[Crossref] [PubMed]

Zhang, Y.

Zhao, F.

D. Chen, S. Zhu, X. Chen, T. Chao, X. Cao, F. Zhao, L. Huang, and J. Liang, “Quantitative cone beam X-ray luminescence tomography/X-ray computed tomography imaging,” Appl. Phys. Lett. 105(19), 191104 (2014).
[Crossref]

Zhao, H.

H. Gao, J. F. Cai, Z. Shen, and H. Zhao, “Robust principal component analysis-based four-dimensional computed tomography,” Phys. Med. Biol. 56(11), 3181–3198 (2011).
[Crossref] [PubMed]

L. Zhang, F. Gao, H. He, and H. Zhao, “Three-dimensional scheme for time-domain fluorescence molecular tomography based on Laplace transforms with noise-robust factors,” Opt. Express 16(10), 7214–7223 (2008).
[Crossref] [PubMed]

Zhu, S.

D. Chen, S. Zhu, X. Chen, T. Chao, X. Cao, F. Zhao, L. Huang, and J. Liang, “Quantitative cone beam X-ray luminescence tomography/X-ray computed tomography imaging,” Appl. Phys. Lett. 105(19), 191104 (2014).
[Crossref]

D. Chen, S. Zhu, H. Yi, X. Zhang, D. Chen, J. Liang, and J. Tian, “Cone beam X-ray luminescence computed tomography: A feasibility study,” Med. Phys. 40(3), 031111 (2013).
[Crossref] [PubMed]

J. Feng, K. Jia, G. Yan, S. Zhu, C. Qin, Y. Lv, and J. Tian, “An optimal permissible source region strategy for multispectral bioluminescence tomography,” Opt. Express 16(20), 15640–15654 (2008).
[Crossref] [PubMed]

ACS Appl. Mater. Interfaces (1)

W. Zhang, Y. Shen, M. Liu, P. Gao, H. Pu, L. Fan, R. Jiang, Z. Liu, F. Shi, and H. Lu, “Sub-10 nm water-dispersible β-NaGdF4:X% Eu3+ nanoparticles with enhanced biocompatibility for in vivo X-ray luminescence computed tomography,” ACS Appl. Mater. Interfaces 9(46), 39985–39993 (2017).
[Crossref] [PubMed]

Appl. Phys. Lett. (1)

D. Chen, S. Zhu, X. Chen, T. Chao, X. Cao, F. Zhao, L. Huang, and J. Liang, “Quantitative cone beam X-ray luminescence tomography/X-ray computed tomography imaging,” Appl. Phys. Lett. 105(19), 191104 (2014).
[Crossref]

Austin J. Biomed. Eng. (1)

W. Cong and G. Wang, “X-ray fan-beam luminescence tomography,” Austin J. Biomed. Eng. 1(5), 1024 (2014).

Biomed. Opt. Express (2)

Comput. Stat. Data Anal. (1)

P. R. Peres-Neto, D. A. Jackson, and K. M. Somers, “How many principal components? stopping rules for determining the number of non-trivial axes revisited,” Comput. Stat. Data Anal. 49(4), 974–997 (2005).
[Crossref]

Cryst. Growth Des. (1)

J. Yang, Z. Quan, D. Kong, X. Liu, and J. Lin, “Y2O3:Eu3+ microspheres: solvothermal synthesis and luminescence properties,” Cryst. Growth Des. 7(4), 730–735 (2007).
[Crossref]

Ecology (1)

L. R. Dice, “Measures of the amount of ecologic association between species,” Ecology 26(3), 297–302 (1945).
[Crossref]

Eur. Radiol. (1)

N. G. Anderson, A. P. Butler, N. J. A. Scott, N. J. Cook, J. S. Butzer, N. Schleich, M. Firsching, R. Grasset, N. de Ruiter, M. Campbell, and P. H. Butler, “Spectroscopic (multi-energy) CT distinguishes iodine and barium contrast material in MICE,” Eur. Radiol. 20(9), 2126–2134 (2010).
[Crossref] [PubMed]

IEEE Access (1)

M. Ahmad, G. Pratx, M. Bazalova, and L. Xing, “X-ray luminescence and X-ray fluorescence computed tomography: new molecular imaging modalities,” IEEE Access 2(2), 1051–1061 (2014).
[Crossref]

IEEE Trans. Med. Imaging (1)

G. Pratx, C. M. Carpenter, C. Sun, and L. Xing, “X-ray luminescence computed tomography via selective excitation: a feasibility study,” IEEE Trans. Med. Imaging 29(12), 1992–1999 (2010).
[Crossref] [PubMed]

Invest. Radiol. (1)

E. Eyal, B. N. Bloch, N. M. Rofsky, E. Furman-Haran, E. M. Genega, R. E. Lenkinski, and H. Degani, “Principal component analysis of dynamic contrast enhanced MRI in human prostate cancer,” Invest. Radiol. 45(4), 174–181 (2010).
[Crossref] [PubMed]

J. Biomed. Opt. (3)

X. Liu, Q. Liao, H. Wang, and Z. Yan, “Excitation-resolved cone-beam X-ray luminescence tomography,” J. Biomed. Opt. 20(7), 070501 (2015).
[Crossref] [PubMed]

W. Cong, H. Shen, and G. Wang, “Spectrally resolving and scattering-compensated x-ray luminescence/fluorescence computed tomography,” J. Biomed. Opt. 16(6), 066014 (2011).
[Crossref] [PubMed]

R. Lansford, G. Bearman, and S. E. Fraser, “Resolution of multiple green fluorescent protein color variants and dyes using two-photon microscopy and imaging spectroscopy,” J. Biomed. Opt. 6(3), 311–318 (2001).
[Crossref] [PubMed]

J. Nucl. Med. Technol. (1)

P. E. Svensson, J. Olsson, F. Engbrant, E. Bengtsson, and P. Razifar, “Characterization and reduction of noise in dynamic PET data using masked volumewise principal component analysis,” J. Nucl. Med. Technol. 39(1), 27–34 (2011).
[Crossref] [PubMed]

Med. Phys. (2)

D. Chen, S. Zhu, H. Yi, X. Zhang, D. Chen, J. Liang, and J. Tian, “Cone beam X-ray luminescence computed tomography: A feasibility study,” Med. Phys. 40(3), 031111 (2013).
[Crossref] [PubMed]

M. Schweiger, S. R. Arridge, M. Hiraoka, and D. T. Delpy, “The finite element method for the propagation of light in scattering media: Boundary and source conditions,” Med. Phys. 22(11), 1779–1792 (1995).
[Crossref] [PubMed]

Nat. Photonics (1)

E. M. C. Hillman and A. Moore, “All-optical anatomical co-registration for molecular imaging of small animals using dynamic contrast,” Nat. Photonics 1(9), 526–530 (2007).
[Crossref] [PubMed]

Opt. Express (5)

Opt. Lett. (3)

Phys. Med. Biol. (6)

X. Liu, B. Zhang, J. Luo, and J. Bai, “Principal component analysis of dynamic fluorescence tomography in measurement space,” Phys. Med. Biol. 57(9), 2727–2742 (2012).
[Crossref] [PubMed]

A. J. Chaudhari, S. Ahn, R. Levenson, R. D. Badawi, S. R. Cherry, and R. M. Leahy, “Excitation spectroscopy in multispectral optical fluorescence tomography: methodology, feasibility and computer simulation studies,” Phys. Med. Biol. 54(15), 4687–4704 (2009).
[Crossref] [PubMed]

A. D. Klose and T. Pöschinger, “Excitation-resolved fluorescence tomography with simplified spherical harmonics equations,” Phys. Med. Biol. 56(5), 1443–1469 (2011).
[Crossref] [PubMed]

P. Razifar, H. Engler, G. Blomquist, A. Ringheim, S. Estrada, B. Långström, and M. Bergström, “Principal component analysis with pre-normalization improves the signal-to-noise ratio and image quality in positron emission tomography studies of amyloid deposits in Alzheimer’s disease,” Phys. Med. Biol. 54(11), 3595–3612 (2009).
[Crossref] [PubMed]

H. Gao, J. F. Cai, Z. Shen, and H. Zhao, “Robust principal component analysis-based four-dimensional computed tomography,” Phys. Med. Biol. 56(11), 3181–3198 (2011).
[Crossref] [PubMed]

H. Pu, G. Zhang, W. He, F. Liu, H. Guang, Y. Zhang, J. Bai, and J. Luo, “Resolving fluorophores by unmixing multispectral fluorescence tomography with independent component analysis,” Phys. Med. Biol. 59(17), 5025–5042 (2014).
[Crossref] [PubMed]

SIAM Rev. (1)

P. C. Hansen, “Analysis of discrete ill-posed problems by means of the L-curve,” SIAM Rev. 34(4), 561–580 (1992).
[Crossref]

WIREs Comp. Stat (1)

H. Abdi and L. J. Williams, “Principal component analysis,” WIREs Comp. Stat 2(4), 433–459 (2010).

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Figures (10)

Fig. 1
Fig. 1 Illustration of cylinder model. (a) The coronal view. (b) The transverse view.
Fig. 2
Fig. 2 Illustrations of imaging system and phantom. (a) Multispectral CB-XLCT system. (b) X-ray projection of the phantom and the reconstruction region is between two red solid lines. (c) XCT slice of the phantom, corresponding to Z = 1.5 cm in (b).
Fig. 3
Fig. 3 Reconstruction results at different spectral bands with center wavelengths of (a) 580 nm, (b) 620 nm, (c) 660 nm and (d) 700 nm.
Fig. 4
Fig. 4 Results of M-SI method in digital simulation. Distributions of (a) probe A and (b) probe B recovered by M-SI method.
Fig. 5
Fig. 5 The obtained PCs by M-PCA method in (a) case 1, (b) case 2 and (c) case 3. For each case, the images in the first row are the positive PCs, and the images in the second row are the negative PCs.
Fig. 6
Fig. 6 Merged images of probes obtained by (a) M-SI method and (b) M-PCA method in case 3. (c) Intensity profiles along the red dash lines in (a) and (b).
Fig. 7
Fig. 7 Reconstruction results of C-NF with (a) 6 projections, (b) 12 projections and (c) 24 projections. The height of the reconstruction slices is 1.5 cm.
Fig. 8
Fig. 8 Results of reconstruction and M-SI method in phantom experiment. (a) and (b) Reconstruction results at 580 nm and 620 nm. (c) and (d) Distributions of nanoparticles Y2O3:Eu3+ and Gd2O2S:Tb3+ obtained by M-SI method.
Fig. 9
Fig. 9 Results of M-PCA method in phantom experiment. (a) and (b) The positive elements in the first and second PCs. (c) and (d) The negative elements in the first and second PCs.
Fig. 10
Fig. 10 Qualitative comparisons of C–NF, M-SI and M-PCA methods. (a), (d) and (g) Fusion images of C–NF, M-SI and M-PCA with the corresponding XCT slice respectively. (b) and (c) Different views of 3D rendering of C–NF. (e) and (f) Different views of 3D rendering of M-SI. (h) and (i) Different views of 3D rendering of M-PCA.

Tables (6)

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Table 1 The relative fraction ω ( λ k ) in digital simulation

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Table 2 Different combinations of multiple spectral bands

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Table 3 The percentage and cumulated percentages of variances in PCs (%)

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Table 4 The quantitative evaluation of M-PCA and M-SI in digital simulation

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Table 5 The relative fraction ω ( λ k ) in phantom experiment

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Table 6 The quantitative evaluation of M-SI and M-PCA in phantom experiment

Equations (13)

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

χ ( r ) = χ ( r 0 ) exp { r 0 r μ x ( τ ) d τ }
S ( r s ) = χ ( r s ) η ρ ( r s )
[ D ( r ) Φ ( r ) ] μ a ( r ) Φ ( r ) = S ( r s )
W x = Φ m
W ( λ k ) x ( λ k ) = Φ m ( λ k )
[ W ( λ 1 ) η ( λ 1 ) W ( λ 2 ) η ( λ 2 ) W ( λ k ) η ( λ k ) ] ρ = [ Φ m ( λ 1 ) Φ m ( λ 2 ) Φ m ( λ k ) ]
x ( λ k ) = ρ 1 η 1 ( λ k ) + ρ 2 η 2 ( λ k ) + ρ P η P ( λ k )
[ ρ 1 ρ 2 ρ P ] A = [ x ( λ 1 ) x ( λ 2 ) x ( λ M ) ]
P = X 0 E
p j = X 0 e j
D i c e = 2 | X Y | | X | + | Y |
L E = p a - p c 2
R = u max u v a l l e y u max u min

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