Abstract

Dynamic fluorescence molecular tomography (FMT) is an attractive imaging technique for three-dimensionally resolving the metabolic process of fluorescent biomarkers in small animal. When combined with compartmental modeling, dynamic FMT can be used to obtain parametric images which can provide quantitative pharmacokinetic information for drug development and metabolic research. However, the computational burden of dynamic FMT is extremely huge due to its large data sets arising from the long measurement process and the densely sampling device. In this work, we propose to accelerate the reconstruction process of dynamic FMT based on principal component analysis (PCA). Taking advantage of the compression property of PCA, the dimension of the sub weight matrix used for solving the inverse problem is reduced by retaining only a few principal components which can retain most of the effective information of the sub weight matrix. Therefore, the reconstruction process of dynamic FMT can be accelerated by solving the smaller scale inverse problem. Numerical simulation and mouse experiment are performed to validate the performance of the proposed method. Results show that the proposed method can greatly accelerate the reconstruction of parametric images in dynamic FMT almost without degradation in image quality.

© 2015 Optical Society of America

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References

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2015 (1)

G. Zhang, H. Pu, W. He, F. Liu, J. Luo, and J. Bai, “Full-direct method for imaging pharmacokinetic parameters in dynamic fluorescence molecular tomography,” Appl. Phys. Lett. 106(8), 081110 (2015).
[Crossref]

2014 (1)

G. Zhang, F. Liu, H. Pu, W. He, J. Luo, and J. Bai, “A direct method with structural priors for imaging pharmacokinetic parameters in dynamic fluorescence molecular tomography,” IEEE Trans. Biomed. Eng. 61(3), 986–990 (2014).
[Crossref] [PubMed]

2013 (4)

G. Zhang, F. Liu, B. Zhang, Y. He, J. Luo, and J. Bai, “Imaging of pharmacokinetic rates of indocyanine green in mouse liver with a hybrid fluorescence molecular tomography/x-ray computed tomography system,” J. Biomed. Opt. 18(4), 040505 (2013).
[Crossref] [PubMed]

T. Correia, T. Rudge, M. Koch, V. Ntziachristos, and S. Arridge, “Wavelet-based data and solution compression for efficient image reconstruction in fluorescence diffuse optical tomography,” J. Biomed. Opt. 18(8), 086008 (2013).
[Crossref] [PubMed]

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

X. Cao, X. Wang, B. Zhang, F. Liu, J. Luo, and J. Bai, “Accelerated image reconstruction in fluorescence molecular tomography using dimension reduction,” Biomed. Opt. Express 4(1), 1–14 (2013).
[Crossref] [PubMed]

2012 (2)

G. Zhang, X. Cao, B. Zhang, F. Liu, J. Luo, and J. Bai, “MAP estimation with structural priors for fluorescence molecular tomography,” Phys. Med. Biol. 58(2), 351–372 (2012).
[Crossref] [PubMed]

C. B. Amoozegar, T. Wang, M. B. Bouchard, A. F. H. McCaslin, W. S. Blaner, R. M. Levenson, and E. M. C. Hillman, “Dynamic contrast-enhanced optical imaging of in vivo organ function,” J. Biomed. Opt. 17(9), 096003 (2012).
[Crossref] [PubMed]

2011 (4)

L. Chen, T. H. Chan, P. L. Choyke, E. M. C. Hillman, C. Y. Chi, Z. M. Bhujwalla, G. Wang, S. S. Wang, Z. Szabo, and Y. Wang, “CAM-CM: A signal deconvolution tool for in vivo dynamic contrast-enhanced imaging of complex tissues,” Bioinformatics 27(18), 2607–2609 (2011).
[PubMed]

X. Liu, F. Liu, Y. Zhang, and J. Bai, “Unmixing dynamic fluorescence diffuse optical tomography images with independent component analysis,” IEEE Trans. Med. Imaging 30(9), 1591–1604 (2011).
[Crossref] [PubMed]

L. Chen, P. L. Choyke, T. H. Chan, C. Y. Chi, G. Wang, and Y. Wang, “Tissue-specific compartmental analysis for dynamic contrast-enhanced MR imaging of complex tumors,” IEEE Trans. Med. Imaging 30(12), 2044–2058 (2011).
[Crossref] [PubMed]

M. Choi, K. Choi, S. W. Ryu, J. Lee, and C. Choi, “Dynamic fluorescence imaging for multiparametric measurement of tumor vasculature,” J. Biomed. Opt. 16(4), 046008 (2011).
[Crossref] [PubMed]

2010 (7)

J. Tang, H. Kuwabara, D. F. Wong, and A. Rahmim, “Direct 4D reconstruction of parametric images incorporating anato-functional joint entropy,” Phys. Med. Biol. 55(15), 4261–4272 (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]

R. B. Schulz, A. Ale, A. Sarantopoulos, M. Freyer, E. Soehngen, M. Zientkowska, and V. Ntziachristos, “Hybrid system for simultaneous fluorescence and x-ray computed tomography,” IEEE Trans. Med. Imaging 29(2), 465–473 (2010).
[Crossref] [PubMed]

F. Liu, X. Liu, D. Wang, B. Zhang, and J. Bai, “A parallel excitation based fluorescence molecular tomography system for whole-body simultaneous imaging of small animals,” Ann. Biomed. Eng. 38(11), 3440–3448 (2010).
[Crossref] [PubMed]

J. Ripoll, “Hybrid Fourier-real space method for diffuse optical tomography,” Opt. Lett. 35(5), 688–690 (2010).
[Crossref] [PubMed]

T. J. Rudge, V. Y. Soloviev, and S. R. Arridge, “Fast image reconstruction in fluorescence optical tomography using data compression,” Opt. Lett. 35(5), 763–765 (2010).
[Crossref] [PubMed]

N. Ducros, C. D’andrea, G. Valentini, T. Rudge, S. Arridge, and A. Bassi, “Full-wavelet approach for fluorescence diffuse optical tomography with structured illumination,” Opt. Lett. 35(21), 3676–3678 (2010).
[Crossref] [PubMed]

2009 (3)

G. Wang and J. Qi, “Generalized algorithms for direct reconstruction of parametric images from dynamic PET data,” IEEE Trans. Med. Imaging 28(11), 1717–1726 (2009).
[Crossref] [PubMed]

B. M. Kelm, B. H. Menze, O. Nix, C. M. Zechmann, and F. A. Hamprecht, “Estimating kinetic parameter maps from dynamic contrast-enhanced MRI using spatial prior knowledge,” IEEE Trans. Med. Imaging 28(10), 1534–1547 (2009).
[Crossref] [PubMed]

B. Alacam and B. Yazici, “Direct reconstruction of pharmacokinetic-rate images of optical fluorophores from NIR measurements,” IEEE Trans. Med. Imaging 28(9), 1337–1353 (2009).
[Crossref] [PubMed]

2007 (2)

B. Dogdas, D. Stout, A. F. Chatziioannou, and R. M. Leahy, “Digimouse: A 3D whole body mouse atlas from CT and cryosection data,” Phys. Med. Biol. 52(3), 577–587 (2007).
[Crossref] [PubMed]

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 (3)

2004 (1)

R. B. Schulz, J. Ripoll, and V. Ntziachristos, “Experimental fluorescence tomography of tissues with noncontact measurements,” IEEE Trans. Med. Imaging 23(4), 492–500 (2004).
[Crossref] [PubMed]

2003 (1)

2000 (1)

M. Gurfinkel, A. B. Thompson, W. Ralston, T. L. Troy, A. L. Moore, T. A. Moore, J. D. Gust, D. Tatman, J. S. Reynolds, B. Muggenburg, K. Nikula, R. Pandey, R. H. Mayer, D. J. Hawrysz, and E. M. Sevick-Muraca, “Pharmacokinetics of ICG and HPPH-car for the detection of normal and tumor tissue using fluorescence, near-infrared reflectance imaging: A case study,” Photochem. Photobiol. 72(1), 94–102 (2000).
[Crossref] [PubMed]

1997 (1)

C. C. Martin, R. F. Williams, J. H. Gao, L. D. Nickerson, J. Xiong, and P. T. Fox, “The pharmacokinetics of hyperpolarized xenon: Implications for cerebral MRI,” J. Magn. Reson. Imaging 7(5), 848–854 (1997).
[Crossref] [PubMed]

1996 (1)

H. Shinohara, A. Tanaka, T. Kitai, N. Yanabu, T. Inomoto, S. Satoh, E. Hatano, Y. Yamaoka, and K. Hirao, “Direct measurement of hepatic indocyanine green clearance with near-infrared spectroscopy: separate evaluation of uptake and removal,” Hepatology 23(1), 137–144 (1996).
[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]

Achilefu, S.

Alacam, B.

B. Alacam and B. Yazici, “Direct reconstruction of pharmacokinetic-rate images of optical fluorophores from NIR measurements,” IEEE Trans. Med. Imaging 28(9), 1337–1353 (2009).
[Crossref] [PubMed]

Ale, A.

R. B. Schulz, A. Ale, A. Sarantopoulos, M. Freyer, E. Soehngen, M. Zientkowska, and V. Ntziachristos, “Hybrid system for simultaneous fluorescence and x-ray computed tomography,” IEEE Trans. Med. Imaging 29(2), 465–473 (2010).
[Crossref] [PubMed]

Amoozegar, C. B.

C. B. Amoozegar, T. Wang, M. B. Bouchard, A. F. H. McCaslin, W. S. Blaner, R. M. Levenson, and E. M. C. Hillman, “Dynamic contrast-enhanced optical imaging of in vivo organ function,” J. Biomed. Opt. 17(9), 096003 (2012).
[Crossref] [PubMed]

Arridge, S.

T. Correia, T. Rudge, M. Koch, V. Ntziachristos, and S. Arridge, “Wavelet-based data and solution compression for efficient image reconstruction in fluorescence diffuse optical tomography,” J. Biomed. Opt. 18(8), 086008 (2013).
[Crossref] [PubMed]

N. Ducros, C. D’andrea, G. Valentini, T. Rudge, S. Arridge, and A. Bassi, “Full-wavelet approach for fluorescence diffuse optical tomography with structured illumination,” Opt. Lett. 35(21), 3676–3678 (2010).
[Crossref] [PubMed]

Arridge, S. R.

T. J. Rudge, V. Y. Soloviev, and S. R. Arridge, “Fast image reconstruction in fluorescence optical tomography using data compression,” Opt. Lett. 35(5), 763–765 (2010).
[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]

Bai, J.

G. Zhang, H. Pu, W. He, F. Liu, J. Luo, and J. Bai, “Full-direct method for imaging pharmacokinetic parameters in dynamic fluorescence molecular tomography,” Appl. Phys. Lett. 106(8), 081110 (2015).
[Crossref]

G. Zhang, F. Liu, H. Pu, W. He, J. Luo, and J. Bai, “A direct method with structural priors for imaging pharmacokinetic parameters in dynamic fluorescence molecular tomography,” IEEE Trans. Biomed. Eng. 61(3), 986–990 (2014).
[Crossref] [PubMed]

G. Zhang, F. Liu, B. Zhang, Y. He, J. Luo, and J. Bai, “Imaging of pharmacokinetic rates of indocyanine green in mouse liver with a hybrid fluorescence molecular tomography/x-ray computed tomography system,” J. Biomed. Opt. 18(4), 040505 (2013).
[Crossref] [PubMed]

X. Cao, X. Wang, B. Zhang, F. Liu, J. Luo, and J. Bai, “Accelerated image reconstruction in fluorescence molecular tomography using dimension reduction,” Biomed. Opt. Express 4(1), 1–14 (2013).
[Crossref] [PubMed]

G. Zhang, X. Cao, B. Zhang, F. Liu, J. Luo, and J. Bai, “MAP estimation with structural priors for fluorescence molecular tomography,” Phys. Med. Biol. 58(2), 351–372 (2012).
[Crossref] [PubMed]

X. Liu, F. Liu, Y. Zhang, and J. Bai, “Unmixing dynamic fluorescence diffuse optical tomography images with independent component analysis,” IEEE Trans. Med. Imaging 30(9), 1591–1604 (2011).
[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]

F. Liu, X. Liu, D. Wang, B. Zhang, and J. Bai, “A parallel excitation based fluorescence molecular tomography system for whole-body simultaneous imaging of small animals,” Ann. Biomed. Eng. 38(11), 3440–3448 (2010).
[Crossref] [PubMed]

G. Zhang, H. Pu, W. He, F. Liu, J. Luo, and J. Bai, “Bayesian framework based direct reconstruction of fluorescence parametric images,” IEEE Trans. Med. Imaging. in press.

Bassi, A.

Bevilacqua, F.

Bhujwalla, Z. M.

L. Chen, T. H. Chan, P. L. Choyke, E. M. C. Hillman, C. Y. Chi, Z. M. Bhujwalla, G. Wang, S. S. Wang, Z. Szabo, and Y. Wang, “CAM-CM: A signal deconvolution tool for in vivo dynamic contrast-enhanced imaging of complex tissues,” Bioinformatics 27(18), 2607–2609 (2011).
[PubMed]

Blaner, W. S.

C. B. Amoozegar, T. Wang, M. B. Bouchard, A. F. H. McCaslin, W. S. Blaner, R. M. Levenson, and E. M. C. Hillman, “Dynamic contrast-enhanced optical imaging of in vivo organ function,” J. Biomed. Opt. 17(9), 096003 (2012).
[Crossref] [PubMed]

Bloch, S.

Bouchard, M. B.

C. B. Amoozegar, T. Wang, M. B. Bouchard, A. F. H. McCaslin, W. S. Blaner, R. M. Levenson, and E. M. C. Hillman, “Dynamic contrast-enhanced optical imaging of in vivo organ function,” J. Biomed. Opt. 17(9), 096003 (2012).
[Crossref] [PubMed]

Bouman, C. A.

M. E. Kamasak, C. A. Bouman, E. D. Morris, and K. Sauer, “Direct reconstruction of kinetic parameter images from dynamic PET data,” IEEE Trans. Med. Imaging 24(5), 636–650 (2005).
[Crossref] [PubMed]

A. B. Milstein, K. J. Webb, and C. A. Bouman, “Estimation of kinetic model parameters in fluorescence optical diffusion tomography,” J. Opt. Soc. Am. A 22(7), 1357–1368 (2005).
[Crossref] [PubMed]

Cao, X.

X. Cao, X. Wang, B. Zhang, F. Liu, J. Luo, and J. Bai, “Accelerated image reconstruction in fluorescence molecular tomography using dimension reduction,” Biomed. Opt. Express 4(1), 1–14 (2013).
[Crossref] [PubMed]

G. Zhang, X. Cao, B. Zhang, F. Liu, J. Luo, and J. Bai, “MAP estimation with structural priors for fluorescence molecular tomography,” Phys. Med. Biol. 58(2), 351–372 (2012).
[Crossref] [PubMed]

Chan, T. H.

L. Chen, T. H. Chan, P. L. Choyke, E. M. C. Hillman, C. Y. Chi, Z. M. Bhujwalla, G. Wang, S. S. Wang, Z. Szabo, and Y. Wang, “CAM-CM: A signal deconvolution tool for in vivo dynamic contrast-enhanced imaging of complex tissues,” Bioinformatics 27(18), 2607–2609 (2011).
[PubMed]

L. Chen, P. L. Choyke, T. H. Chan, C. Y. Chi, G. Wang, and Y. Wang, “Tissue-specific compartmental analysis for dynamic contrast-enhanced MR imaging of complex tumors,” IEEE Trans. Med. Imaging 30(12), 2044–2058 (2011).
[Crossref] [PubMed]

Chatziioannou, A. F.

B. Dogdas, D. Stout, A. F. Chatziioannou, and R. M. Leahy, “Digimouse: A 3D whole body mouse atlas from CT and cryosection data,” Phys. Med. Biol. 52(3), 577–587 (2007).
[Crossref] [PubMed]

Chen, L.

L. Chen, T. H. Chan, P. L. Choyke, E. M. C. Hillman, C. Y. Chi, Z. M. Bhujwalla, G. Wang, S. S. Wang, Z. Szabo, and Y. Wang, “CAM-CM: A signal deconvolution tool for in vivo dynamic contrast-enhanced imaging of complex tissues,” Bioinformatics 27(18), 2607–2609 (2011).
[PubMed]

L. Chen, P. L. Choyke, T. H. Chan, C. Y. Chi, G. Wang, and Y. Wang, “Tissue-specific compartmental analysis for dynamic contrast-enhanced MR imaging of complex tumors,” IEEE Trans. Med. Imaging 30(12), 2044–2058 (2011).
[Crossref] [PubMed]

Chi, C. Y.

L. Chen, P. L. Choyke, T. H. Chan, C. Y. Chi, G. Wang, and Y. Wang, “Tissue-specific compartmental analysis for dynamic contrast-enhanced MR imaging of complex tumors,” IEEE Trans. Med. Imaging 30(12), 2044–2058 (2011).
[Crossref] [PubMed]

L. Chen, T. H. Chan, P. L. Choyke, E. M. C. Hillman, C. Y. Chi, Z. M. Bhujwalla, G. Wang, S. S. Wang, Z. Szabo, and Y. Wang, “CAM-CM: A signal deconvolution tool for in vivo dynamic contrast-enhanced imaging of complex tissues,” Bioinformatics 27(18), 2607–2609 (2011).
[PubMed]

Choi, C.

M. Choi, K. Choi, S. W. Ryu, J. Lee, and C. Choi, “Dynamic fluorescence imaging for multiparametric measurement of tumor vasculature,” J. Biomed. Opt. 16(4), 046008 (2011).
[Crossref] [PubMed]

Choi, K.

M. Choi, K. Choi, S. W. Ryu, J. Lee, and C. Choi, “Dynamic fluorescence imaging for multiparametric measurement of tumor vasculature,” J. Biomed. Opt. 16(4), 046008 (2011).
[Crossref] [PubMed]

Choi, M.

M. Choi, K. Choi, S. W. Ryu, J. Lee, and C. Choi, “Dynamic fluorescence imaging for multiparametric measurement of tumor vasculature,” J. Biomed. Opt. 16(4), 046008 (2011).
[Crossref] [PubMed]

Choyke, P. L.

L. Chen, P. L. Choyke, T. H. Chan, C. Y. Chi, G. Wang, and Y. Wang, “Tissue-specific compartmental analysis for dynamic contrast-enhanced MR imaging of complex tumors,” IEEE Trans. Med. Imaging 30(12), 2044–2058 (2011).
[Crossref] [PubMed]

L. Chen, T. H. Chan, P. L. Choyke, E. M. C. Hillman, C. Y. Chi, Z. M. Bhujwalla, G. Wang, S. S. Wang, Z. Szabo, and Y. Wang, “CAM-CM: A signal deconvolution tool for in vivo dynamic contrast-enhanced imaging of complex tissues,” Bioinformatics 27(18), 2607–2609 (2011).
[PubMed]

Correia, T.

T. Correia, T. Rudge, M. Koch, V. Ntziachristos, and S. Arridge, “Wavelet-based data and solution compression for efficient image reconstruction in fluorescence diffuse optical tomography,” J. Biomed. Opt. 18(8), 086008 (2013).
[Crossref] [PubMed]

Cuccia, D. J.

Culver, J.

D’andrea, C.

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]

Dogdas, B.

B. Dogdas, D. Stout, A. F. Chatziioannou, and R. M. Leahy, “Digimouse: A 3D whole body mouse atlas from CT and cryosection data,” Phys. Med. Biol. 52(3), 577–587 (2007).
[Crossref] [PubMed]

Ducros, N.

Durkin, A. J.

Fox, P. T.

C. C. Martin, R. F. Williams, J. H. Gao, L. D. Nickerson, J. Xiong, and P. T. Fox, “The pharmacokinetics of hyperpolarized xenon: Implications for cerebral MRI,” J. Magn. Reson. Imaging 7(5), 848–854 (1997).
[Crossref] [PubMed]

Freyer, M.

R. B. Schulz, A. Ale, A. Sarantopoulos, M. Freyer, E. Soehngen, M. Zientkowska, and V. Ntziachristos, “Hybrid system for simultaneous fluorescence and x-ray computed tomography,” IEEE Trans. Med. Imaging 29(2), 465–473 (2010).
[Crossref] [PubMed]

Gao, J. H.

C. C. Martin, R. F. Williams, J. H. Gao, L. D. Nickerson, J. Xiong, and P. T. Fox, “The pharmacokinetics of hyperpolarized xenon: Implications for cerebral MRI,” J. Magn. Reson. Imaging 7(5), 848–854 (1997).
[Crossref] [PubMed]

Gulsen, G.

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]

Gurfinkel, M.

M. Gurfinkel, A. B. Thompson, W. Ralston, T. L. Troy, A. L. Moore, T. A. Moore, J. D. Gust, D. Tatman, J. S. Reynolds, B. Muggenburg, K. Nikula, R. Pandey, R. H. Mayer, D. J. Hawrysz, and E. M. Sevick-Muraca, “Pharmacokinetics of ICG and HPPH-car for the detection of normal and tumor tissue using fluorescence, near-infrared reflectance imaging: A case study,” Photochem. Photobiol. 72(1), 94–102 (2000).
[Crossref] [PubMed]

Gust, J. D.

M. Gurfinkel, A. B. Thompson, W. Ralston, T. L. Troy, A. L. Moore, T. A. Moore, J. D. Gust, D. Tatman, J. S. Reynolds, B. Muggenburg, K. Nikula, R. Pandey, R. H. Mayer, D. J. Hawrysz, and E. M. Sevick-Muraca, “Pharmacokinetics of ICG and HPPH-car for the detection of normal and tumor tissue using fluorescence, near-infrared reflectance imaging: A case study,” Photochem. Photobiol. 72(1), 94–102 (2000).
[Crossref] [PubMed]

Hamprecht, F. A.

B. M. Kelm, B. H. Menze, O. Nix, C. M. Zechmann, and F. A. Hamprecht, “Estimating kinetic parameter maps from dynamic contrast-enhanced MRI using spatial prior knowledge,” IEEE Trans. Med. Imaging 28(10), 1534–1547 (2009).
[Crossref] [PubMed]

Hatano, E.

H. Shinohara, A. Tanaka, T. Kitai, N. Yanabu, T. Inomoto, S. Satoh, E. Hatano, Y. Yamaoka, and K. Hirao, “Direct measurement of hepatic indocyanine green clearance with near-infrared spectroscopy: separate evaluation of uptake and removal,” Hepatology 23(1), 137–144 (1996).
[Crossref] [PubMed]

Hawrysz, D. J.

M. Gurfinkel, A. B. Thompson, W. Ralston, T. L. Troy, A. L. Moore, T. A. Moore, J. D. Gust, D. Tatman, J. S. Reynolds, B. Muggenburg, K. Nikula, R. Pandey, R. H. Mayer, D. J. Hawrysz, and E. M. Sevick-Muraca, “Pharmacokinetics of ICG and HPPH-car for the detection of normal and tumor tissue using fluorescence, near-infrared reflectance imaging: A case study,” Photochem. Photobiol. 72(1), 94–102 (2000).
[Crossref] [PubMed]

He, W.

G. Zhang, H. Pu, W. He, F. Liu, J. Luo, and J. Bai, “Full-direct method for imaging pharmacokinetic parameters in dynamic fluorescence molecular tomography,” Appl. Phys. Lett. 106(8), 081110 (2015).
[Crossref]

G. Zhang, F. Liu, H. Pu, W. He, J. Luo, and J. Bai, “A direct method with structural priors for imaging pharmacokinetic parameters in dynamic fluorescence molecular tomography,” IEEE Trans. Biomed. Eng. 61(3), 986–990 (2014).
[Crossref] [PubMed]

G. Zhang, H. Pu, W. He, F. Liu, J. Luo, and J. Bai, “Bayesian framework based direct reconstruction of fluorescence parametric images,” IEEE Trans. Med. Imaging. in press.

He, Y.

G. Zhang, F. Liu, B. Zhang, Y. He, J. Luo, and J. Bai, “Imaging of pharmacokinetic rates of indocyanine green in mouse liver with a hybrid fluorescence molecular tomography/x-ray computed tomography system,” J. Biomed. Opt. 18(4), 040505 (2013).
[Crossref] [PubMed]

Hillman, E. M. C.

C. B. Amoozegar, T. Wang, M. B. Bouchard, A. F. H. McCaslin, W. S. Blaner, R. M. Levenson, and E. M. C. Hillman, “Dynamic contrast-enhanced optical imaging of in vivo organ function,” J. Biomed. Opt. 17(9), 096003 (2012).
[Crossref] [PubMed]

L. Chen, T. H. Chan, P. L. Choyke, E. M. C. Hillman, C. Y. Chi, Z. M. Bhujwalla, G. Wang, S. S. Wang, Z. Szabo, and Y. Wang, “CAM-CM: A signal deconvolution tool for in vivo dynamic contrast-enhanced imaging of complex tissues,” Bioinformatics 27(18), 2607–2609 (2011).
[PubMed]

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]

Hirao, K.

H. Shinohara, A. Tanaka, T. Kitai, N. Yanabu, T. Inomoto, S. Satoh, E. Hatano, Y. Yamaoka, and K. Hirao, “Direct measurement of hepatic indocyanine green clearance with near-infrared spectroscopy: separate evaluation of uptake and removal,” Hepatology 23(1), 137–144 (1996).
[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]

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]

Inomoto, T.

H. Shinohara, A. Tanaka, T. Kitai, N. Yanabu, T. Inomoto, S. Satoh, E. Hatano, Y. Yamaoka, and K. Hirao, “Direct measurement of hepatic indocyanine green clearance with near-infrared spectroscopy: separate evaluation of uptake and removal,” Hepatology 23(1), 137–144 (1996).
[Crossref] [PubMed]

Kamasak, M. E.

M. E. Kamasak, C. A. Bouman, E. D. Morris, and K. Sauer, “Direct reconstruction of kinetic parameter images from dynamic PET data,” IEEE Trans. Med. Imaging 24(5), 636–650 (2005).
[Crossref] [PubMed]

Kelm, B. M.

B. M. Kelm, B. H. Menze, O. Nix, C. M. Zechmann, and F. A. Hamprecht, “Estimating kinetic parameter maps from dynamic contrast-enhanced MRI using spatial prior knowledge,” IEEE Trans. Med. Imaging 28(10), 1534–1547 (2009).
[Crossref] [PubMed]

Kitai, T.

H. Shinohara, A. Tanaka, T. Kitai, N. Yanabu, T. Inomoto, S. Satoh, E. Hatano, Y. Yamaoka, and K. Hirao, “Direct measurement of hepatic indocyanine green clearance with near-infrared spectroscopy: separate evaluation of uptake and removal,” Hepatology 23(1), 137–144 (1996).
[Crossref] [PubMed]

Koch, M.

T. Correia, T. Rudge, M. Koch, V. Ntziachristos, and S. Arridge, “Wavelet-based data and solution compression for efficient image reconstruction in fluorescence diffuse optical tomography,” J. Biomed. Opt. 18(8), 086008 (2013).
[Crossref] [PubMed]

Kuwabara, H.

J. Tang, H. Kuwabara, D. F. Wong, and A. Rahmim, “Direct 4D reconstruction of parametric images incorporating anato-functional joint entropy,” Phys. Med. Biol. 55(15), 4261–4272 (2010).
[Crossref] [PubMed]

Leahy, R. M.

B. Dogdas, D. Stout, A. F. Chatziioannou, and R. M. Leahy, “Digimouse: A 3D whole body mouse atlas from CT and cryosection data,” Phys. Med. Biol. 52(3), 577–587 (2007).
[Crossref] [PubMed]

Lee, J.

M. Choi, K. Choi, S. W. Ryu, J. Lee, and C. Choi, “Dynamic fluorescence imaging for multiparametric measurement of tumor vasculature,” J. Biomed. Opt. 16(4), 046008 (2011).
[Crossref] [PubMed]

Levenson, R. M.

C. B. Amoozegar, T. Wang, M. B. Bouchard, A. F. H. McCaslin, W. S. Blaner, R. M. Levenson, and E. M. C. Hillman, “Dynamic contrast-enhanced optical imaging of in vivo organ function,” J. Biomed. Opt. 17(9), 096003 (2012).
[Crossref] [PubMed]

Liu, F.

G. Zhang, H. Pu, W. He, F. Liu, J. Luo, and J. Bai, “Full-direct method for imaging pharmacokinetic parameters in dynamic fluorescence molecular tomography,” Appl. Phys. Lett. 106(8), 081110 (2015).
[Crossref]

G. Zhang, F. Liu, H. Pu, W. He, J. Luo, and J. Bai, “A direct method with structural priors for imaging pharmacokinetic parameters in dynamic fluorescence molecular tomography,” IEEE Trans. Biomed. Eng. 61(3), 986–990 (2014).
[Crossref] [PubMed]

G. Zhang, F. Liu, B. Zhang, Y. He, J. Luo, and J. Bai, “Imaging of pharmacokinetic rates of indocyanine green in mouse liver with a hybrid fluorescence molecular tomography/x-ray computed tomography system,” J. Biomed. Opt. 18(4), 040505 (2013).
[Crossref] [PubMed]

X. Cao, X. Wang, B. Zhang, F. Liu, J. Luo, and J. Bai, “Accelerated image reconstruction in fluorescence molecular tomography using dimension reduction,” Biomed. Opt. Express 4(1), 1–14 (2013).
[Crossref] [PubMed]

G. Zhang, X. Cao, B. Zhang, F. Liu, J. Luo, and J. Bai, “MAP estimation with structural priors for fluorescence molecular tomography,” Phys. Med. Biol. 58(2), 351–372 (2012).
[Crossref] [PubMed]

X. Liu, F. Liu, Y. Zhang, and J. Bai, “Unmixing dynamic fluorescence diffuse optical tomography images with independent component analysis,” IEEE Trans. Med. Imaging 30(9), 1591–1604 (2011).
[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]

F. Liu, X. Liu, D. Wang, B. Zhang, and J. Bai, “A parallel excitation based fluorescence molecular tomography system for whole-body simultaneous imaging of small animals,” Ann. Biomed. Eng. 38(11), 3440–3448 (2010).
[Crossref] [PubMed]

G. Zhang, H. Pu, W. He, F. Liu, J. Luo, and J. Bai, “Bayesian framework based direct reconstruction of fluorescence parametric images,” IEEE Trans. Med. Imaging. in press.

Liu, X.

X. Liu, F. Liu, Y. Zhang, and J. Bai, “Unmixing dynamic fluorescence diffuse optical tomography images with independent component analysis,” IEEE Trans. Med. Imaging 30(9), 1591–1604 (2011).
[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]

F. Liu, X. Liu, D. Wang, B. Zhang, and J. Bai, “A parallel excitation based fluorescence molecular tomography system for whole-body simultaneous imaging of small animals,” Ann. Biomed. Eng. 38(11), 3440–3448 (2010).
[Crossref] [PubMed]

Luo, J.

G. Zhang, H. Pu, W. He, F. Liu, J. Luo, and J. Bai, “Full-direct method for imaging pharmacokinetic parameters in dynamic fluorescence molecular tomography,” Appl. Phys. Lett. 106(8), 081110 (2015).
[Crossref]

G. Zhang, F. Liu, H. Pu, W. He, J. Luo, and J. Bai, “A direct method with structural priors for imaging pharmacokinetic parameters in dynamic fluorescence molecular tomography,” IEEE Trans. Biomed. Eng. 61(3), 986–990 (2014).
[Crossref] [PubMed]

G. Zhang, F. Liu, B. Zhang, Y. He, J. Luo, and J. Bai, “Imaging of pharmacokinetic rates of indocyanine green in mouse liver with a hybrid fluorescence molecular tomography/x-ray computed tomography system,” J. Biomed. Opt. 18(4), 040505 (2013).
[Crossref] [PubMed]

X. Cao, X. Wang, B. Zhang, F. Liu, J. Luo, and J. Bai, “Accelerated image reconstruction in fluorescence molecular tomography using dimension reduction,” Biomed. Opt. Express 4(1), 1–14 (2013).
[Crossref] [PubMed]

G. Zhang, X. Cao, B. Zhang, F. Liu, J. Luo, and J. Bai, “MAP estimation with structural priors for fluorescence molecular tomography,” Phys. Med. Biol. 58(2), 351–372 (2012).
[Crossref] [PubMed]

G. Zhang, H. Pu, W. He, F. Liu, J. Luo, and J. Bai, “Bayesian framework based direct reconstruction of fluorescence parametric images,” IEEE Trans. Med. Imaging. in press.

Martin, C. C.

C. C. Martin, R. F. Williams, J. H. Gao, L. D. Nickerson, J. Xiong, and P. T. Fox, “The pharmacokinetics of hyperpolarized xenon: Implications for cerebral MRI,” J. Magn. Reson. Imaging 7(5), 848–854 (1997).
[Crossref] [PubMed]

Mayer, R. H.

M. Gurfinkel, A. B. Thompson, W. Ralston, T. L. Troy, A. L. Moore, T. A. Moore, J. D. Gust, D. Tatman, J. S. Reynolds, B. Muggenburg, K. Nikula, R. Pandey, R. H. Mayer, D. J. Hawrysz, and E. M. Sevick-Muraca, “Pharmacokinetics of ICG and HPPH-car for the detection of normal and tumor tissue using fluorescence, near-infrared reflectance imaging: A case study,” Photochem. Photobiol. 72(1), 94–102 (2000).
[Crossref] [PubMed]

McCaslin, A. F. H.

C. B. Amoozegar, T. Wang, M. B. Bouchard, A. F. H. McCaslin, W. S. Blaner, R. M. Levenson, and E. M. C. Hillman, “Dynamic contrast-enhanced optical imaging of in vivo organ function,” J. Biomed. Opt. 17(9), 096003 (2012).
[Crossref] [PubMed]

Menze, B. H.

B. M. Kelm, B. H. Menze, O. Nix, C. M. Zechmann, and F. A. Hamprecht, “Estimating kinetic parameter maps from dynamic contrast-enhanced MRI using spatial prior knowledge,” IEEE Trans. Med. Imaging 28(10), 1534–1547 (2009).
[Crossref] [PubMed]

Merritt, S.

Milstein, A. B.

Mohajerani, P.

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]

Moore, A. L.

M. Gurfinkel, A. B. Thompson, W. Ralston, T. L. Troy, A. L. Moore, T. A. Moore, J. D. Gust, D. Tatman, J. S. Reynolds, B. Muggenburg, K. Nikula, R. Pandey, R. H. Mayer, D. J. Hawrysz, and E. M. Sevick-Muraca, “Pharmacokinetics of ICG and HPPH-car for the detection of normal and tumor tissue using fluorescence, near-infrared reflectance imaging: A case study,” Photochem. Photobiol. 72(1), 94–102 (2000).
[Crossref] [PubMed]

Moore, T. A.

M. Gurfinkel, A. B. Thompson, W. Ralston, T. L. Troy, A. L. Moore, T. A. Moore, J. D. Gust, D. Tatman, J. S. Reynolds, B. Muggenburg, K. Nikula, R. Pandey, R. H. Mayer, D. J. Hawrysz, and E. M. Sevick-Muraca, “Pharmacokinetics of ICG and HPPH-car for the detection of normal and tumor tissue using fluorescence, near-infrared reflectance imaging: A case study,” Photochem. Photobiol. 72(1), 94–102 (2000).
[Crossref] [PubMed]

Morris, E. D.

M. E. Kamasak, C. A. Bouman, E. D. Morris, and K. Sauer, “Direct reconstruction of kinetic parameter images from dynamic PET data,” IEEE Trans. Med. Imaging 24(5), 636–650 (2005).
[Crossref] [PubMed]

Muggenburg, B.

M. Gurfinkel, A. B. Thompson, W. Ralston, T. L. Troy, A. L. Moore, T. A. Moore, J. D. Gust, D. Tatman, J. S. Reynolds, B. Muggenburg, K. Nikula, R. Pandey, R. H. Mayer, D. J. Hawrysz, and E. M. Sevick-Muraca, “Pharmacokinetics of ICG and HPPH-car for the detection of normal and tumor tissue using fluorescence, near-infrared reflectance imaging: A case study,” Photochem. Photobiol. 72(1), 94–102 (2000).
[Crossref] [PubMed]

Nalcioglu, O.

Nickerson, L. D.

C. C. Martin, R. F. Williams, J. H. Gao, L. D. Nickerson, J. Xiong, and P. T. Fox, “The pharmacokinetics of hyperpolarized xenon: Implications for cerebral MRI,” J. Magn. Reson. Imaging 7(5), 848–854 (1997).
[Crossref] [PubMed]

Nikula, K.

M. Gurfinkel, A. B. Thompson, W. Ralston, T. L. Troy, A. L. Moore, T. A. Moore, J. D. Gust, D. Tatman, J. S. Reynolds, B. Muggenburg, K. Nikula, R. Pandey, R. H. Mayer, D. J. Hawrysz, and E. M. Sevick-Muraca, “Pharmacokinetics of ICG and HPPH-car for the detection of normal and tumor tissue using fluorescence, near-infrared reflectance imaging: A case study,” Photochem. Photobiol. 72(1), 94–102 (2000).
[Crossref] [PubMed]

Nix, O.

B. M. Kelm, B. H. Menze, O. Nix, C. M. Zechmann, and F. A. Hamprecht, “Estimating kinetic parameter maps from dynamic contrast-enhanced MRI using spatial prior knowledge,” IEEE Trans. Med. Imaging 28(10), 1534–1547 (2009).
[Crossref] [PubMed]

Ntziachristos, V.

T. Correia, T. Rudge, M. Koch, V. Ntziachristos, and S. Arridge, “Wavelet-based data and solution compression for efficient image reconstruction in fluorescence diffuse optical tomography,” J. Biomed. Opt. 18(8), 086008 (2013).
[Crossref] [PubMed]

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

R. B. Schulz, A. Ale, A. Sarantopoulos, M. Freyer, E. Soehngen, M. Zientkowska, and V. Ntziachristos, “Hybrid system for simultaneous fluorescence and x-ray computed tomography,” IEEE Trans. Med. Imaging 29(2), 465–473 (2010).
[Crossref] [PubMed]

R. B. Schulz, J. Ripoll, and V. Ntziachristos, “Experimental fluorescence tomography of tissues with noncontact measurements,” IEEE Trans. Med. Imaging 23(4), 492–500 (2004).
[Crossref] [PubMed]

Pandey, R.

M. Gurfinkel, A. B. Thompson, W. Ralston, T. L. Troy, A. L. Moore, T. A. Moore, J. D. Gust, D. Tatman, J. S. Reynolds, B. Muggenburg, K. Nikula, R. Pandey, R. H. Mayer, D. J. Hawrysz, and E. M. Sevick-Muraca, “Pharmacokinetics of ICG and HPPH-car for the detection of normal and tumor tissue using fluorescence, near-infrared reflectance imaging: A case study,” Photochem. Photobiol. 72(1), 94–102 (2000).
[Crossref] [PubMed]

Patwardhan, S.

Pu, H.

G. Zhang, H. Pu, W. He, F. Liu, J. Luo, and J. Bai, “Full-direct method for imaging pharmacokinetic parameters in dynamic fluorescence molecular tomography,” Appl. Phys. Lett. 106(8), 081110 (2015).
[Crossref]

G. Zhang, F. Liu, H. Pu, W. He, J. Luo, and J. Bai, “A direct method with structural priors for imaging pharmacokinetic parameters in dynamic fluorescence molecular tomography,” IEEE Trans. Biomed. Eng. 61(3), 986–990 (2014).
[Crossref] [PubMed]

G. Zhang, H. Pu, W. He, F. Liu, J. Luo, and J. Bai, “Bayesian framework based direct reconstruction of fluorescence parametric images,” IEEE Trans. Med. Imaging. in press.

Qi, J.

G. Wang and J. Qi, “Generalized algorithms for direct reconstruction of parametric images from dynamic PET data,” IEEE Trans. Med. Imaging 28(11), 1717–1726 (2009).
[Crossref] [PubMed]

Rahmim, A.

J. Tang, H. Kuwabara, D. F. Wong, and A. Rahmim, “Direct 4D reconstruction of parametric images incorporating anato-functional joint entropy,” Phys. Med. Biol. 55(15), 4261–4272 (2010).
[Crossref] [PubMed]

Ralston, W.

M. Gurfinkel, A. B. Thompson, W. Ralston, T. L. Troy, A. L. Moore, T. A. Moore, J. D. Gust, D. Tatman, J. S. Reynolds, B. Muggenburg, K. Nikula, R. Pandey, R. H. Mayer, D. J. Hawrysz, and E. M. Sevick-Muraca, “Pharmacokinetics of ICG and HPPH-car for the detection of normal and tumor tissue using fluorescence, near-infrared reflectance imaging: A case study,” Photochem. Photobiol. 72(1), 94–102 (2000).
[Crossref] [PubMed]

Reynolds, J. S.

M. Gurfinkel, A. B. Thompson, W. Ralston, T. L. Troy, A. L. Moore, T. A. Moore, J. D. Gust, D. Tatman, J. S. Reynolds, B. Muggenburg, K. Nikula, R. Pandey, R. H. Mayer, D. J. Hawrysz, and E. M. Sevick-Muraca, “Pharmacokinetics of ICG and HPPH-car for the detection of normal and tumor tissue using fluorescence, near-infrared reflectance imaging: A case study,” Photochem. Photobiol. 72(1), 94–102 (2000).
[Crossref] [PubMed]

Ripoll, J.

J. Ripoll, “Hybrid Fourier-real space method for diffuse optical tomography,” Opt. Lett. 35(5), 688–690 (2010).
[Crossref] [PubMed]

R. B. Schulz, J. Ripoll, and V. Ntziachristos, “Experimental fluorescence tomography of tissues with noncontact measurements,” IEEE Trans. Med. Imaging 23(4), 492–500 (2004).
[Crossref] [PubMed]

Rudge, T.

T. Correia, T. Rudge, M. Koch, V. Ntziachristos, and S. Arridge, “Wavelet-based data and solution compression for efficient image reconstruction in fluorescence diffuse optical tomography,” J. Biomed. Opt. 18(8), 086008 (2013).
[Crossref] [PubMed]

N. Ducros, C. D’andrea, G. Valentini, T. Rudge, S. Arridge, and A. Bassi, “Full-wavelet approach for fluorescence diffuse optical tomography with structured illumination,” Opt. Lett. 35(21), 3676–3678 (2010).
[Crossref] [PubMed]

Rudge, T. J.

Ryu, S. W.

M. Choi, K. Choi, S. W. Ryu, J. Lee, and C. Choi, “Dynamic fluorescence imaging for multiparametric measurement of tumor vasculature,” J. Biomed. Opt. 16(4), 046008 (2011).
[Crossref] [PubMed]

Sarantopoulos, A.

R. B. Schulz, A. Ale, A. Sarantopoulos, M. Freyer, E. Soehngen, M. Zientkowska, and V. Ntziachristos, “Hybrid system for simultaneous fluorescence and x-ray computed tomography,” IEEE Trans. Med. Imaging 29(2), 465–473 (2010).
[Crossref] [PubMed]

Satoh, S.

H. Shinohara, A. Tanaka, T. Kitai, N. Yanabu, T. Inomoto, S. Satoh, E. Hatano, Y. Yamaoka, and K. Hirao, “Direct measurement of hepatic indocyanine green clearance with near-infrared spectroscopy: separate evaluation of uptake and removal,” Hepatology 23(1), 137–144 (1996).
[Crossref] [PubMed]

Sauer, K.

M. E. Kamasak, C. A. Bouman, E. D. Morris, and K. Sauer, “Direct reconstruction of kinetic parameter images from dynamic PET data,” IEEE Trans. Med. Imaging 24(5), 636–650 (2005).
[Crossref] [PubMed]

Schulz, R. B.

R. B. Schulz, A. Ale, A. Sarantopoulos, M. Freyer, E. Soehngen, M. Zientkowska, and V. Ntziachristos, “Hybrid system for simultaneous fluorescence and x-ray computed tomography,” IEEE Trans. Med. Imaging 29(2), 465–473 (2010).
[Crossref] [PubMed]

R. B. Schulz, J. Ripoll, and V. Ntziachristos, “Experimental fluorescence tomography of tissues with noncontact measurements,” IEEE Trans. Med. Imaging 23(4), 492–500 (2004).
[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]

Sevick-Muraca, E. M.

M. Gurfinkel, A. B. Thompson, W. Ralston, T. L. Troy, A. L. Moore, T. A. Moore, J. D. Gust, D. Tatman, J. S. Reynolds, B. Muggenburg, K. Nikula, R. Pandey, R. H. Mayer, D. J. Hawrysz, and E. M. Sevick-Muraca, “Pharmacokinetics of ICG and HPPH-car for the detection of normal and tumor tissue using fluorescence, near-infrared reflectance imaging: A case study,” Photochem. Photobiol. 72(1), 94–102 (2000).
[Crossref] [PubMed]

Shinohara, H.

H. Shinohara, A. Tanaka, T. Kitai, N. Yanabu, T. Inomoto, S. Satoh, E. Hatano, Y. Yamaoka, and K. Hirao, “Direct measurement of hepatic indocyanine green clearance with near-infrared spectroscopy: separate evaluation of uptake and removal,” Hepatology 23(1), 137–144 (1996).
[Crossref] [PubMed]

Soehngen, E.

R. B. Schulz, A. Ale, A. Sarantopoulos, M. Freyer, E. Soehngen, M. Zientkowska, and V. Ntziachristos, “Hybrid system for simultaneous fluorescence and x-ray computed tomography,” IEEE Trans. Med. Imaging 29(2), 465–473 (2010).
[Crossref] [PubMed]

Soloviev, V. Y.

Stout, D.

B. Dogdas, D. Stout, A. F. Chatziioannou, and R. M. Leahy, “Digimouse: A 3D whole body mouse atlas from CT and cryosection data,” Phys. Med. Biol. 52(3), 577–587 (2007).
[Crossref] [PubMed]

Szabo, Z.

L. Chen, T. H. Chan, P. L. Choyke, E. M. C. Hillman, C. Y. Chi, Z. M. Bhujwalla, G. Wang, S. S. Wang, Z. Szabo, and Y. Wang, “CAM-CM: A signal deconvolution tool for in vivo dynamic contrast-enhanced imaging of complex tissues,” Bioinformatics 27(18), 2607–2609 (2011).
[PubMed]

Tanaka, A.

H. Shinohara, A. Tanaka, T. Kitai, N. Yanabu, T. Inomoto, S. Satoh, E. Hatano, Y. Yamaoka, and K. Hirao, “Direct measurement of hepatic indocyanine green clearance with near-infrared spectroscopy: separate evaluation of uptake and removal,” Hepatology 23(1), 137–144 (1996).
[Crossref] [PubMed]

Tang, J.

J. Tang, H. Kuwabara, D. F. Wong, and A. Rahmim, “Direct 4D reconstruction of parametric images incorporating anato-functional joint entropy,” Phys. Med. Biol. 55(15), 4261–4272 (2010).
[Crossref] [PubMed]

Tatman, D.

M. Gurfinkel, A. B. Thompson, W. Ralston, T. L. Troy, A. L. Moore, T. A. Moore, J. D. Gust, D. Tatman, J. S. Reynolds, B. Muggenburg, K. Nikula, R. Pandey, R. H. Mayer, D. J. Hawrysz, and E. M. Sevick-Muraca, “Pharmacokinetics of ICG and HPPH-car for the detection of normal and tumor tissue using fluorescence, near-infrared reflectance imaging: A case study,” Photochem. Photobiol. 72(1), 94–102 (2000).
[Crossref] [PubMed]

Thompson, A. B.

M. Gurfinkel, A. B. Thompson, W. Ralston, T. L. Troy, A. L. Moore, T. A. Moore, J. D. Gust, D. Tatman, J. S. Reynolds, B. Muggenburg, K. Nikula, R. Pandey, R. H. Mayer, D. J. Hawrysz, and E. M. Sevick-Muraca, “Pharmacokinetics of ICG and HPPH-car for the detection of normal and tumor tissue using fluorescence, near-infrared reflectance imaging: A case study,” Photochem. Photobiol. 72(1), 94–102 (2000).
[Crossref] [PubMed]

Tian, 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]

Tromberg, B. J.

Troy, T. L.

M. Gurfinkel, A. B. Thompson, W. Ralston, T. L. Troy, A. L. Moore, T. A. Moore, J. D. Gust, D. Tatman, J. S. Reynolds, B. Muggenburg, K. Nikula, R. Pandey, R. H. Mayer, D. J. Hawrysz, and E. M. Sevick-Muraca, “Pharmacokinetics of ICG and HPPH-car for the detection of normal and tumor tissue using fluorescence, near-infrared reflectance imaging: A case study,” Photochem. Photobiol. 72(1), 94–102 (2000).
[Crossref] [PubMed]

Valentini, G.

Wang, D.

F. Liu, X. Liu, D. Wang, B. Zhang, and J. Bai, “A parallel excitation based fluorescence molecular tomography system for whole-body simultaneous imaging of small animals,” Ann. Biomed. Eng. 38(11), 3440–3448 (2010).
[Crossref] [PubMed]

Wang, G.

L. Chen, T. H. Chan, P. L. Choyke, E. M. C. Hillman, C. Y. Chi, Z. M. Bhujwalla, G. Wang, S. S. Wang, Z. Szabo, and Y. Wang, “CAM-CM: A signal deconvolution tool for in vivo dynamic contrast-enhanced imaging of complex tissues,” Bioinformatics 27(18), 2607–2609 (2011).
[PubMed]

L. Chen, P. L. Choyke, T. H. Chan, C. Y. Chi, G. Wang, and Y. Wang, “Tissue-specific compartmental analysis for dynamic contrast-enhanced MR imaging of complex tumors,” IEEE Trans. Med. Imaging 30(12), 2044–2058 (2011).
[Crossref] [PubMed]

G. Wang and J. Qi, “Generalized algorithms for direct reconstruction of parametric images from dynamic PET data,” IEEE Trans. Med. Imaging 28(11), 1717–1726 (2009).
[Crossref] [PubMed]

Wang, J.

Wang, S. S.

L. Chen, T. H. Chan, P. L. Choyke, E. M. C. Hillman, C. Y. Chi, Z. M. Bhujwalla, G. Wang, S. S. Wang, Z. Szabo, and Y. Wang, “CAM-CM: A signal deconvolution tool for in vivo dynamic contrast-enhanced imaging of complex tissues,” Bioinformatics 27(18), 2607–2609 (2011).
[PubMed]

Wang, T.

C. B. Amoozegar, T. Wang, M. B. Bouchard, A. F. H. McCaslin, W. S. Blaner, R. M. Levenson, and E. M. C. Hillman, “Dynamic contrast-enhanced optical imaging of in vivo organ function,” J. Biomed. Opt. 17(9), 096003 (2012).
[Crossref] [PubMed]

Wang, X.

X. Cao, X. Wang, B. Zhang, F. Liu, J. Luo, and J. Bai, “Accelerated image reconstruction in fluorescence molecular tomography using dimension reduction,” Biomed. Opt. Express 4(1), 1–14 (2013).
[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]

Wang, Y.

L. Chen, T. H. Chan, P. L. Choyke, E. M. C. Hillman, C. Y. Chi, Z. M. Bhujwalla, G. Wang, S. S. Wang, Z. Szabo, and Y. Wang, “CAM-CM: A signal deconvolution tool for in vivo dynamic contrast-enhanced imaging of complex tissues,” Bioinformatics 27(18), 2607–2609 (2011).
[PubMed]

L. Chen, P. L. Choyke, T. H. Chan, C. Y. Chi, G. Wang, and Y. Wang, “Tissue-specific compartmental analysis for dynamic contrast-enhanced MR imaging of complex tumors,” IEEE Trans. Med. Imaging 30(12), 2044–2058 (2011).
[Crossref] [PubMed]

Webb, K. J.

Williams, R. F.

C. C. Martin, R. F. Williams, J. H. Gao, L. D. Nickerson, J. Xiong, and P. T. Fox, “The pharmacokinetics of hyperpolarized xenon: Implications for cerebral MRI,” J. Magn. Reson. Imaging 7(5), 848–854 (1997).
[Crossref] [PubMed]

Wong, D. F.

J. Tang, H. Kuwabara, D. F. Wong, and A. Rahmim, “Direct 4D reconstruction of parametric images incorporating anato-functional joint entropy,” Phys. Med. Biol. 55(15), 4261–4272 (2010).
[Crossref] [PubMed]

Xiong, J.

C. C. Martin, R. F. Williams, J. H. Gao, L. D. Nickerson, J. Xiong, and P. T. Fox, “The pharmacokinetics of hyperpolarized xenon: Implications for cerebral MRI,” J. Magn. Reson. Imaging 7(5), 848–854 (1997).
[Crossref] [PubMed]

Yamaoka, Y.

H. Shinohara, A. Tanaka, T. Kitai, N. Yanabu, T. Inomoto, S. Satoh, E. Hatano, Y. Yamaoka, and K. Hirao, “Direct measurement of hepatic indocyanine green clearance with near-infrared spectroscopy: separate evaluation of uptake and removal,” Hepatology 23(1), 137–144 (1996).
[Crossref] [PubMed]

Yanabu, N.

H. Shinohara, A. Tanaka, T. Kitai, N. Yanabu, T. Inomoto, S. Satoh, E. Hatano, Y. Yamaoka, and K. Hirao, “Direct measurement of hepatic indocyanine green clearance with near-infrared spectroscopy: separate evaluation of uptake and removal,” Hepatology 23(1), 137–144 (1996).
[Crossref] [PubMed]

Yazici, B.

B. Alacam and B. Yazici, “Direct reconstruction of pharmacokinetic-rate images of optical fluorophores from NIR measurements,” IEEE Trans. Med. Imaging 28(9), 1337–1353 (2009).
[Crossref] [PubMed]

Yu, H.

Zechmann, C. M.

B. M. Kelm, B. H. Menze, O. Nix, C. M. Zechmann, and F. A. Hamprecht, “Estimating kinetic parameter maps from dynamic contrast-enhanced MRI using spatial prior knowledge,” IEEE Trans. Med. Imaging 28(10), 1534–1547 (2009).
[Crossref] [PubMed]

Zhang, B.

G. Zhang, F. Liu, B. Zhang, Y. He, J. Luo, and J. Bai, “Imaging of pharmacokinetic rates of indocyanine green in mouse liver with a hybrid fluorescence molecular tomography/x-ray computed tomography system,” J. Biomed. Opt. 18(4), 040505 (2013).
[Crossref] [PubMed]

X. Cao, X. Wang, B. Zhang, F. Liu, J. Luo, and J. Bai, “Accelerated image reconstruction in fluorescence molecular tomography using dimension reduction,” Biomed. Opt. Express 4(1), 1–14 (2013).
[Crossref] [PubMed]

G. Zhang, X. Cao, B. Zhang, F. Liu, J. Luo, and J. Bai, “MAP estimation with structural priors for fluorescence molecular tomography,” Phys. Med. Biol. 58(2), 351–372 (2012).
[Crossref] [PubMed]

F. Liu, X. Liu, D. Wang, B. Zhang, and J. Bai, “A parallel excitation based fluorescence molecular tomography system for whole-body simultaneous imaging of small animals,” Ann. Biomed. Eng. 38(11), 3440–3448 (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]

Zhang, G.

G. Zhang, H. Pu, W. He, F. Liu, J. Luo, and J. Bai, “Full-direct method for imaging pharmacokinetic parameters in dynamic fluorescence molecular tomography,” Appl. Phys. Lett. 106(8), 081110 (2015).
[Crossref]

G. Zhang, F. Liu, H. Pu, W. He, J. Luo, and J. Bai, “A direct method with structural priors for imaging pharmacokinetic parameters in dynamic fluorescence molecular tomography,” IEEE Trans. Biomed. Eng. 61(3), 986–990 (2014).
[Crossref] [PubMed]

G. Zhang, F. Liu, B. Zhang, Y. He, J. Luo, and J. Bai, “Imaging of pharmacokinetic rates of indocyanine green in mouse liver with a hybrid fluorescence molecular tomography/x-ray computed tomography system,” J. Biomed. Opt. 18(4), 040505 (2013).
[Crossref] [PubMed]

G. Zhang, X. Cao, B. Zhang, F. Liu, J. Luo, and J. Bai, “MAP estimation with structural priors for fluorescence molecular tomography,” Phys. Med. Biol. 58(2), 351–372 (2012).
[Crossref] [PubMed]

G. Zhang, H. Pu, W. He, F. Liu, J. Luo, and J. Bai, “Bayesian framework based direct reconstruction of fluorescence parametric images,” IEEE Trans. Med. Imaging. in press.

Zhang, Y.

X. Liu, F. Liu, Y. Zhang, and J. Bai, “Unmixing dynamic fluorescence diffuse optical tomography images with independent component analysis,” IEEE Trans. Med. Imaging 30(9), 1591–1604 (2011).
[Crossref] [PubMed]

Zientkowska, M.

R. B. Schulz, A. Ale, A. Sarantopoulos, M. Freyer, E. Soehngen, M. Zientkowska, and V. Ntziachristos, “Hybrid system for simultaneous fluorescence and x-ray computed tomography,” IEEE Trans. Med. Imaging 29(2), 465–473 (2010).
[Crossref] [PubMed]

Ann. Biomed. Eng. (1)

F. Liu, X. Liu, D. Wang, B. Zhang, and J. Bai, “A parallel excitation based fluorescence molecular tomography system for whole-body simultaneous imaging of small animals,” Ann. Biomed. Eng. 38(11), 3440–3448 (2010).
[Crossref] [PubMed]

Appl. Opt. (1)

Appl. Phys. Lett. (1)

G. Zhang, H. Pu, W. He, F. Liu, J. Luo, and J. Bai, “Full-direct method for imaging pharmacokinetic parameters in dynamic fluorescence molecular tomography,” Appl. Phys. Lett. 106(8), 081110 (2015).
[Crossref]

Bioinformatics (1)

L. Chen, T. H. Chan, P. L. Choyke, E. M. C. Hillman, C. Y. Chi, Z. M. Bhujwalla, G. Wang, S. S. Wang, Z. Szabo, and Y. Wang, “CAM-CM: A signal deconvolution tool for in vivo dynamic contrast-enhanced imaging of complex tissues,” Bioinformatics 27(18), 2607–2609 (2011).
[PubMed]

Biomed. Opt. Express (1)

Hepatology (1)

H. Shinohara, A. Tanaka, T. Kitai, N. Yanabu, T. Inomoto, S. Satoh, E. Hatano, Y. Yamaoka, and K. Hirao, “Direct measurement of hepatic indocyanine green clearance with near-infrared spectroscopy: separate evaluation of uptake and removal,” Hepatology 23(1), 137–144 (1996).
[Crossref] [PubMed]

IEEE Trans. Biomed. Eng. (2)

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]

G. Zhang, F. Liu, H. Pu, W. He, J. Luo, and J. Bai, “A direct method with structural priors for imaging pharmacokinetic parameters in dynamic fluorescence molecular tomography,” IEEE Trans. Biomed. Eng. 61(3), 986–990 (2014).
[Crossref] [PubMed]

IEEE Trans. Med. Imaging (8)

B. M. Kelm, B. H. Menze, O. Nix, C. M. Zechmann, and F. A. Hamprecht, “Estimating kinetic parameter maps from dynamic contrast-enhanced MRI using spatial prior knowledge,” IEEE Trans. Med. Imaging 28(10), 1534–1547 (2009).
[Crossref] [PubMed]

L. Chen, P. L. Choyke, T. H. Chan, C. Y. Chi, G. Wang, and Y. Wang, “Tissue-specific compartmental analysis for dynamic contrast-enhanced MR imaging of complex tumors,” IEEE Trans. Med. Imaging 30(12), 2044–2058 (2011).
[Crossref] [PubMed]

M. E. Kamasak, C. A. Bouman, E. D. Morris, and K. Sauer, “Direct reconstruction of kinetic parameter images from dynamic PET data,” IEEE Trans. Med. Imaging 24(5), 636–650 (2005).
[Crossref] [PubMed]

G. Wang and J. Qi, “Generalized algorithms for direct reconstruction of parametric images from dynamic PET data,” IEEE Trans. Med. Imaging 28(11), 1717–1726 (2009).
[Crossref] [PubMed]

X. Liu, F. Liu, Y. Zhang, and J. Bai, “Unmixing dynamic fluorescence diffuse optical tomography images with independent component analysis,” IEEE Trans. Med. Imaging 30(9), 1591–1604 (2011).
[Crossref] [PubMed]

B. Alacam and B. Yazici, “Direct reconstruction of pharmacokinetic-rate images of optical fluorophores from NIR measurements,” IEEE Trans. Med. Imaging 28(9), 1337–1353 (2009).
[Crossref] [PubMed]

R. B. Schulz, A. Ale, A. Sarantopoulos, M. Freyer, E. Soehngen, M. Zientkowska, and V. Ntziachristos, “Hybrid system for simultaneous fluorescence and x-ray computed tomography,” IEEE Trans. Med. Imaging 29(2), 465–473 (2010).
[Crossref] [PubMed]

R. B. Schulz, J. Ripoll, and V. Ntziachristos, “Experimental fluorescence tomography of tissues with noncontact measurements,” IEEE Trans. Med. Imaging 23(4), 492–500 (2004).
[Crossref] [PubMed]

J. Biomed. Opt. (4)

T. Correia, T. Rudge, M. Koch, V. Ntziachristos, and S. Arridge, “Wavelet-based data and solution compression for efficient image reconstruction in fluorescence diffuse optical tomography,” J. Biomed. Opt. 18(8), 086008 (2013).
[Crossref] [PubMed]

G. Zhang, F. Liu, B. Zhang, Y. He, J. Luo, and J. Bai, “Imaging of pharmacokinetic rates of indocyanine green in mouse liver with a hybrid fluorescence molecular tomography/x-ray computed tomography system,” J. Biomed. Opt. 18(4), 040505 (2013).
[Crossref] [PubMed]

M. Choi, K. Choi, S. W. Ryu, J. Lee, and C. Choi, “Dynamic fluorescence imaging for multiparametric measurement of tumor vasculature,” J. Biomed. Opt. 16(4), 046008 (2011).
[Crossref] [PubMed]

C. B. Amoozegar, T. Wang, M. B. Bouchard, A. F. H. McCaslin, W. S. Blaner, R. M. Levenson, and E. M. C. Hillman, “Dynamic contrast-enhanced optical imaging of in vivo organ function,” J. Biomed. Opt. 17(9), 096003 (2012).
[Crossref] [PubMed]

J. Magn. Reson. Imaging (1)

C. C. Martin, R. F. Williams, J. H. Gao, L. D. Nickerson, J. Xiong, and P. T. Fox, “The pharmacokinetics of hyperpolarized xenon: Implications for cerebral MRI,” J. Magn. Reson. Imaging 7(5), 848–854 (1997).
[Crossref] [PubMed]

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

Med. Phys. (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]

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 (1)

Opt. Lett. (4)

Photochem. Photobiol. (1)

M. Gurfinkel, A. B. Thompson, W. Ralston, T. L. Troy, A. L. Moore, T. A. Moore, J. D. Gust, D. Tatman, J. S. Reynolds, B. Muggenburg, K. Nikula, R. Pandey, R. H. Mayer, D. J. Hawrysz, and E. M. Sevick-Muraca, “Pharmacokinetics of ICG and HPPH-car for the detection of normal and tumor tissue using fluorescence, near-infrared reflectance imaging: A case study,” Photochem. Photobiol. 72(1), 94–102 (2000).
[Crossref] [PubMed]

Phys. Med. Biol. (3)

J. Tang, H. Kuwabara, D. F. Wong, and A. Rahmim, “Direct 4D reconstruction of parametric images incorporating anato-functional joint entropy,” Phys. Med. Biol. 55(15), 4261–4272 (2010).
[Crossref] [PubMed]

G. Zhang, X. Cao, B. Zhang, F. Liu, J. Luo, and J. Bai, “MAP estimation with structural priors for fluorescence molecular tomography,” Phys. Med. Biol. 58(2), 351–372 (2012).
[Crossref] [PubMed]

B. Dogdas, D. Stout, A. F. Chatziioannou, and R. M. Leahy, “Digimouse: A 3D whole body mouse atlas from CT and cryosection data,” Phys. Med. Biol. 52(3), 577–587 (2007).
[Crossref] [PubMed]

Other (3)

G. Zhang, H. Pu, W. He, F. Liu, J. Luo, and J. Bai, “Bayesian framework based direct reconstruction of fluorescence parametric images,” IEEE Trans. Med. Imaging. in press.

A. Ishimaru, Wave Propagation and Scattering in Random Media (Academic, 1978).

M. Hsing, Y. Lin, and G. Gulsen, “Pharmacokinetic analysis for tumor characterization using MR-guided dynamic contrast enhanced diffuse optical tomography,” Biomed. Opt. and 3D Imag. BTu2A.3. (2012).

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Figures (16)

Fig. 1
Fig. 1

Schematic diagram of the hybrid FMT/XCT system. The FMT system is a free-space, full-angle system. In the FMT system, a special optical fiber is used to form a line-shaped excitation source, which can provide much better whole-body imaging quality than conventional FMT systems with point illumination [21]. The XCT system is used to obtain the anatomical information of the small animals, which is used as the structural priors in the reconstruction algorithm [19, 20].

Fig. 2
Fig. 2

Schematic diagram of the measurement scheme. (a) The 3-D view of the phantom. The blue geometry in the phantom is a target, in which the fluorophore concentration varies with time continuously. (b) The concentration curve of the target. (c) The top view of the phantom. The phantom is rotated anticlockwise, and boundary measurements are acquired at different projections. It is assumed that S projections are acquired in each circle, and the phantom is continuously rotated for L circles.

Fig. 3
Fig. 3

Flow chart of the proposed acceleration method.

Fig. 4
Fig. 4

Numerical simulation settings. (a) The 3-D Digimouse model used in the simulation. The mouse torso from the neck to the bottom of the kidneys was selected as the investigated region, totally 3.1 cm in length. Three organs were included in the model: liver, lungs and kidneys. In the liver, an IRI region was simulated. (b) ICG concentration curves simulating the metabolic processes of ICG in different metabolic regions. The corresponding pharmacokinetic parameters of the curves are shown in Table 1.

Fig. 5
Fig. 5

Segmented XCT results of the numerical simulation. (a)–(c) Segmented XCT slices indicated by the red, cyan and blue lines in Fig. 4(a), respectively. The model was segmented into the liver (green color), lungs (cyan color), kidneys (blue color) and other tissues (gray color). The IRI region in the liver cannot be seen in XCT images. The segmentation results were used as the structural priors.

Fig. 6
Fig. 6

Parametric images A (a.u.), B (a.u.), α ( min 1 ) and β ( min 1 ) of the numerical simulation (CPV = 0.90). This is the representative slice of the liver shown in Fig. 5(a). The true parametric images were obtained according to Table 1. The reconstructed parametric images were acquired using methods without and with PCA acceleration, respectively.

Fig. 7
Fig. 7

Parametric images A (a.u.), B (a.u.), α ( min 1 ) and β ( min 1 ) of the numerical simulation (CPV = 0.90). This is the representative slice of the lungs shown in Fig. 5(b). The true parametric images were obtained according to Table 1. The reconstructed parametric images were acquired using methods without and with PCA acceleration, respectively.

Fig. 8
Fig. 8

Parametric images A (a.u.), B (a.u.), α ( min 1 ) and β ( min 1 ) of the numerical simulation (CPV = 0.90). This is the representative slice of the kidneys shown in Fig. 5(c). The true parametric images were obtained according to Table 1. The reconstructed parametric images were acquired using methods without and with PCA acceleration, respectively.

Fig. 9
Fig. 9

Influence of CPV on the reconstructed parametric images A (a.u.), B (a.u.), α ( min 1 ) and β ( min 1 ) in the numerical simulation. This is the representative slice of the liver shown in Fig. 5(a). The reconstructed parametric images were acquired with the CPV set as 0.98, 0.95, 0.90, 0.80, 0.70 and 0.60, respectively.

Fig. 10
Fig. 10

Influence of CPV on NRMSE and computation time in the numerical simulation. The NRMSE and computation time were obtained with the CPV set as 0.98, 0.95, 0.90, 0.80, 0.70 and 0.60, respectively.

Fig. 11
Fig. 11

XCT results of the mouse experiment. The mouse torso from the neck to the bottom of the kidneys was selected as the investigated region, totally 3.2 cm in length. (a) Representative coronal XCT slice. (b)–(d) Transversal XCT slices indicated by the green, cyan and blue dashed lines in (a), respectively. (e)–(g) Segmentation results for (b)–(d). All transversal XCT slices getting from the mouse torso in (a) were manually segmented into the liver, lungs, kidneys and other tissues. The segmentation results were used as the structural priors.

Fig. 12
Fig. 12

Parametric images A (a.u.), B (a.u.), α ( min 1 ) and β ( min 1 ) corresponding to the representative slice of liver of the mouse experiment shown in Fig. 11(e) (CPV = 0.90).

Fig. 13
Fig. 13

Parametric images A (a.u.), B (a.u.), α ( min 1 ) and β ( min 1 ) corresponding to the representative slice of lungs of the mouse experiment shown in Fig. 11(f) (CPV = 0.90).

Fig. 14
Fig. 14

Parametric images A (a.u.), B (a.u.), α ( min 1 ) and β ( min 1 ) corresponding to the representative slice of kidneys of the mouse experiment shown in Fig. 11(g) (CPV = 0.90).

Fig. 15
Fig. 15

Influence of CPV on the reconstructed parametric images A (a.u.), B (a.u.), α ( min 1 ) and β ( min 1 ) in the mouse experiment. This is the representative slice of the liver shown in Fig. 11(e). The reconstructed parametric images were acquired with the CPV set as 0.98, 0.95, 0.90, 0.80, 0.70 and 0.60, respectively.

Fig. 16
Fig. 16

Influence of CPV on NRMSE and computation time in the mouse experiment. The NRMSE and computation time were obtained with the CPV set as 0.98, 0.95, 0.90, 0.80, 0.70 and 0.60, respectively.

Tables (3)

Tables Icon

Table 1 Pharmacokinetic parameters used in the numerical simulation.

Tables Icon

Table 2 Quantification results of the two methods in the numerical simulation (CPV = 0.90).

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Table 3 Quantification results of the two methods in the mouse experiment (CPV = 0.90).

Equations (28)

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{ [ D x (r) Φ x (r) ] μ ax (r) Φ x (r)=S(r) [ D m (r) Φ m (r) ] μ am (r) Φ m (r)=ηn(r) Φ x (r)
Φ x,m (r)+2ρ D x,m (r) Φ x,m (r) v =0( rΩ )
LS(r):={ { r l } LS(r)dr =1 LS( r 1 )=LS( r 2 ) r 1 , r 2 { r l } LS(r)=0 r{ r l }
Φ m ( r d ,L S s )=Θ Ω G m ( r d ,r)n(r) G x (r,L S s ) d 3 r
n(r,t)=A(r)exp( α(r)t )+B(r)exp( β(r)t )
X=[ x 1 , x 2 , x 3 , x 4 ]=[ A,B,α,β ]
n(X, t k )= [ n( r 1 , t k ),,n( r N , t k ) ] T
n( r j , t k )=A( r j )exp( α( r j ) t k )+B( r j )exp( β( r j ) t k )
Φ m ( r d i ,L S s , t k )= j=1 N W s (i,j)n( r j , t k ) = j=1 N W s (i,j)[ A( r j )exp( α( r j ) t k )+B( r j )exp( β( r j ) t k ) ]
W s (i,j)=ΔVΘ G m ( r d i , r j ) G x ( r j ,L S s )
f(X, t k )= [ Φ m ( r d 1 ,L S s , t k ),, Φ m ( r d M s ,L S s , t k ) ] T
f(X)= [ f (X, t 1 ) T ,,f (X, t K ) T ] T
f(X, t k )= W s n(X, t k )
y( t k )= [ y( r d 1 ,L S s , t k ),,y( r d M s ,L S s , t k ) ] T
y= [ y ( t 1 ) T ,,y ( t K ) T ] T
y=f(X)+ζ
Ψ( X )= yf( X ) 2 2 + u=1 4 λ u L x u 2 2
C=PΛ P T
W ¯ s =P W s
f ¯ (X, t k )=Pf(X, t k )
y ¯ ( t k )=Py( t k )
f ¯ (X, t k )= W ¯ s n(X, t k )
f ¯ θ (X, t k )= W ¯ s θ n(X, t k )
CPV(θ)= i=1 θ σ i 2 i=1 M s σ i 2
f ¯ θ (X)= [ f ¯ θ (X, t 1 ) T ,, f ¯ θ (X, t K ) T ] T
y ¯ θ = [ y ¯ θ ( t 1 ) T ,, y ¯ θ ( t K ) T ] T
Ψ( X )= y ¯ θ f ¯ θ ( X ) 2 2 + u=1 4 λ u L x u 2 2
NRMSE= X PCA X org 2 X org 2

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