Abstract

Fluorescence diffuse optical tomography using a multi-view continuous-wave and non-contact measurement system and an algorithm incorporating the lp (0 < p ≤ 1) sparsity regularization reconstructs a localized fluorescent target in a small animal. The measurement system provides a total of 25 fluorescence surface 2D-images of an object, which are acquired by a CCD camera from five different angles of view with excitation from five different angles. Fluorescence surface emissions from five different angles of view are simultaneously imaged on the CCD sensor, thus leading to fast acquisition of the 25 images within three minutes. The distributions of the fluorophore are reconstructed by solving the inverse problem based on the photon diffusion equations. In the reconstruction process incorporating the lp sparsity regularization, the regularization term is reformulated as a differentiable function for gradient-based non-linear optimization. Numerical simulations and phantom experiments show that the use of the lp sparsity regularization improves the localization of the target and quantitativeness of the fluorophore concentration. A mouse experiment demonstrates that a localized fluorescent target in a mouse is successfully reconstructed.

© 2014 Optical Society of America

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2014 (1)

2012 (4)

2011 (1)

2010 (4)

2009 (3)

2008 (3)

2007 (6)

2006 (3)

A. P. Gibson, T. Austin, N. L. Everdell, M. Schweiger, S. R. Arridge, J. H. Meek, J. S. Wyatt, D. T. Delpy, and J. C. Hebden, “Three-dimensional whole-head optical tomography for passive motor evoked responses in the neonate,” NueroImage30, 521–528 (2006).
[CrossRef]

R. Weissleder, “Molecular imaging in cancer,” Science321, 1168–1171 (2006).
[CrossRef]

M. Huang and Q. Zhu, “Dual-mesh optical tomography reconstruction method with a depth correction that uses a priori ultrasound information,” Appl. Opt.43(8), 1654–1662 (2006).
[CrossRef]

2005 (4)

V. Ntziachristos, J. Ripoll, L. V. Wang, and R. Weissleder, “Looking and listening to light: the evolution of whole-body photonic imaging,” Nat. Biotechnol.23(3), 313–320 (2005).
[CrossRef] [PubMed]

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

T. Yates, C. Hebdan, A. Gibson, N. Everdell, S. R. Arridge, and M. Douek, “Optical tomography of the breast using a multi-channel time-resolved imager,” Phys. Med. Biol.50, 2503–2517 (2005).
[CrossRef] [PubMed]

G. Boverman, E. L. Miller, A. Li, Q. Zhang, T. Chaves, D. H. Brooks, and D. A. Boas, “Quantitative spectroscopic optical tomography of the breast guided by imperfect a priori structural information,” Phys. Med. Biol.50, 3941–3956 (2005).
[CrossRef] [PubMed]

2004 (1)

2003 (2)

A. B. Milstein, S. Oh, K. Webb, C. A. Bouman, Q. Zhang, D. A. Boas, and R. P. Millane, “Fluorescence optical diffusion tomography,” Appl. Opt.42(16), 3081–3094 (2003).
[CrossRef] [PubMed]

E. Graves, J. Ripoll, R. Weissleder, and V. Ntziachristos, “A submillimeter resolution fluorescence molecular imaging system for small animal imaging,” Med. Phys.30, 901–911 (2003).
[CrossRef] [PubMed]

2002 (4)

J. C. Hebden, A. Gibson, R. M. Yusof, N. Everdell, E. M. C. Hillman, D. T. Delpy, S. R. Arridge, T. Austin, J. H. Meek, and J. S. Wyatt, “Three-dimensional optical tomography of the premature infant brain,” Phys. Med. Biol.47, 4155–4166 (2002).
[CrossRef] [PubMed]

V. Ntziachristos, C.-H. Yung, C. Bremerand, and R. Weissleder, “Fluorescence molecular tomography resolves protease activity in vivo,” Nat. Med.8(7), 757–760 (2002).
[CrossRef] [PubMed]

K. Vishwanath, B. Pogue, and M.-A. Mycek, “Quantitative fluorescence lifetime spectroscopy in turbid media: comparison of theoretical, experimental and computational method,” Phys. Med. Biol.47, 3387–3405 (2002).
[CrossRef] [PubMed]

J. Barkhausen, W. Ebert, J. F. Debatin, and H.-J. Weinmann, “Imaging of myocardial infarction: comparison of magnevist and gadophrin-3 in rabbits,” J. Am. Coll. Cardiol.39(8), 1392–1398 (2002).
[CrossRef] [PubMed]

2000 (1)

D. J. Hawrysz and E. M. Sevick-Muraca, “Developments toward diagnostic breast cancer imaging using near-infrared optical measurements and fluorescent contrast agents,” Neoplasia2(5), 388–417 (2000).
[CrossRef]

1999 (2)

1998 (1)

S. R. Arridge, “A gradient-based optimization scheme for optical tomography,” Opt. Express12(6), 213–226 (1998).
[CrossRef]

1997 (1)

1993 (1)

M. Schweiger, S. R. Arridge, and D. T. Delpy, “Application of the finite-element method for the forward and inverse model in optical tomography,” J. Math. Imaging Vis.3, 263–283 (1993).
[CrossRef]

1990 (1)

W. F. Cheong, S. A. Prahl, and A. J. Welch, “A review of the optical properties of biological tissues,” IEEE J. Quantum Electron.26, 2166–2185 (1990).
[CrossRef]

Adibi, A.

Ahn, S.

J. Dutta, S. Ahn, C. Li, S. R. Cherry, and R. M. Leahy, “Joint L1 and total variation regularization for fluorescence molecular tomography,” Phys. Med. Biol.57, 1459–1476 (2012).
[CrossRef] [PubMed]

Amita, T.

Arridge, S. R.

C. Panagiotou, S. Somayajula, A. P. Gibson, M. Schweiger, R. M. Leahy, and S. R. Arridge, “Information theoretic regularization in diffuse optical tomography,” J. Opt. Soc. Am. A26(5), 1277–1290 (2009).
[CrossRef]

A. Douiri, M. Schweiger, J. Riley, and S. R. Arridge, “Anisotropic diffusion regularization methods for diffuse optical tomography using edge prior information,” Meas. Sci. Tech.18, 87–95 (2007).
[CrossRef]

A. P. Gibson, T. Austin, N. L. Everdell, M. Schweiger, S. R. Arridge, J. H. Meek, J. S. Wyatt, D. T. Delpy, and J. C. Hebden, “Three-dimensional whole-head optical tomography for passive motor evoked responses in the neonate,” NueroImage30, 521–528 (2006).
[CrossRef]

T. Yates, C. Hebdan, A. Gibson, N. Everdell, S. R. Arridge, and M. Douek, “Optical tomography of the breast using a multi-channel time-resolved imager,” Phys. Med. Biol.50, 2503–2517 (2005).
[CrossRef] [PubMed]

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

J. C. Hebden, A. Gibson, R. M. Yusof, N. Everdell, E. M. C. Hillman, D. T. Delpy, S. R. Arridge, T. Austin, J. H. Meek, and J. S. Wyatt, “Three-dimensional optical tomography of the premature infant brain,” Phys. Med. Biol.47, 4155–4166 (2002).
[CrossRef] [PubMed]

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

S. R. Arridge, “A gradient-based optimization scheme for optical tomography,” Opt. Express12(6), 213–226 (1998).
[CrossRef]

M. Schweiger, S. R. Arridge, and D. T. Delpy, “Application of the finite-element method for the forward and inverse model in optical tomography,” J. Math. Imaging Vis.3, 263–283 (1993).
[CrossRef]

Austin, T.

A. P. Gibson, T. Austin, N. L. Everdell, M. Schweiger, S. R. Arridge, J. H. Meek, J. S. Wyatt, D. T. Delpy, and J. C. Hebden, “Three-dimensional whole-head optical tomography for passive motor evoked responses in the neonate,” NueroImage30, 521–528 (2006).
[CrossRef]

J. C. Hebden, A. Gibson, R. M. Yusof, N. Everdell, E. M. C. Hillman, D. T. Delpy, S. R. Arridge, T. Austin, J. H. Meek, and J. S. Wyatt, “Three-dimensional optical tomography of the premature infant brain,” Phys. Med. Biol.47, 4155–4166 (2002).
[CrossRef] [PubMed]

Bangerth, W.

Barkhausen, J.

J. Barkhausen, W. Ebert, J. F. Debatin, and H.-J. Weinmann, “Imaging of myocardial infarction: comparison of magnevist and gadophrin-3 in rabbits,” J. Am. Coll. Cardiol.39(8), 1392–1398 (2002).
[CrossRef] [PubMed]

Boas, D. A.

G. Boverman, E. L. Miller, A. Li, Q. Zhang, T. Chaves, D. H. Brooks, and D. A. Boas, “Quantitative spectroscopic optical tomography of the breast guided by imperfect a priori structural information,” Phys. Med. Biol.50, 3941–3956 (2005).
[CrossRef] [PubMed]

A. B. Milstein, S. Oh, K. Webb, C. A. Bouman, Q. Zhang, D. A. Boas, and R. P. Millane, “Fluorescence optical diffusion tomography,” Appl. Opt.42(16), 3081–3094 (2003).
[CrossRef] [PubMed]

Bouman, C. A.

Boverman, G.

G. Boverman, E. L. Miller, A. Li, Q. Zhang, T. Chaves, D. H. Brooks, and D. A. Boas, “Quantitative spectroscopic optical tomography of the breast guided by imperfect a priori structural information,” Phys. Med. Biol.50, 3941–3956 (2005).
[CrossRef] [PubMed]

Bremerand, C.

V. Ntziachristos, C.-H. Yung, C. Bremerand, and R. Weissleder, “Fluorescence molecular tomography resolves protease activity in vivo,” Nat. Med.8(7), 757–760 (2002).
[CrossRef] [PubMed]

Brooks, D. H.

G. Boverman, E. L. Miller, A. Li, Q. Zhang, T. Chaves, D. H. Brooks, and D. A. Boas, “Quantitative spectroscopic optical tomography of the breast guided by imperfect a priori structural information,” Phys. Med. Biol.50, 3941–3956 (2005).
[CrossRef] [PubMed]

Calvetti, D.

Cao, N.

Carpenter, C. M.

Chan, T. F.

Chatziioannou, A. F.

Chaves, T.

G. Boverman, E. L. Miller, A. Li, Q. Zhang, T. Chaves, D. H. Brooks, and D. A. Boas, “Quantitative spectroscopic optical tomography of the breast guided by imperfect a priori structural information,” Phys. Med. Biol.50, 3941–3956 (2005).
[CrossRef] [PubMed]

Chen, D.

Chen, H.

P. Xu, Y. Tian, H. Chen, and D. Yao, “Lp Norm Iterative Sparse Solution for EEG Source Localization,” IEEE Trans. Biomed. Eng.54(3), 400–409 (2007).
[CrossRef] [PubMed]

Chen, U. A.

Chen, X.

Cheong, W. F.

W. F. Cheong, S. A. Prahl, and A. J. Welch, “A review of the optical properties of biological tissues,” IEEE J. Quantum Electron.26, 2166–2185 (1990).
[CrossRef]

Cherry, S. R.

J. Dutta, S. Ahn, C. Li, S. R. Cherry, and R. M. Leahy, “Joint L1 and total variation regularization for fluorescence molecular tomography,” Phys. Med. Biol.57, 1459–1476 (2012).
[CrossRef] [PubMed]

Cichocki, A.

Z. He, A. Cichocki, R. Zdunek, and S. Xie, “Improved FOCCUS method with conjugate gradient iterations,” IEEE Trans. Signal Process.57(1), 399–404 (2009).
[CrossRef]

Clason, C.

Debatin, J. F.

J. Barkhausen, W. Ebert, J. F. Debatin, and H.-J. Weinmann, “Imaging of myocardial infarction: comparison of magnevist and gadophrin-3 in rabbits,” J. Am. Coll. Cardiol.39(8), 1392–1398 (2002).
[CrossRef] [PubMed]

Dehghani, H.

Deliolanis, N. C.

Delpy, D. T.

A. P. Gibson, T. Austin, N. L. Everdell, M. Schweiger, S. R. Arridge, J. H. Meek, J. S. Wyatt, D. T. Delpy, and J. C. Hebden, “Three-dimensional whole-head optical tomography for passive motor evoked responses in the neonate,” NueroImage30, 521–528 (2006).
[CrossRef]

J. C. Hebden, A. Gibson, R. M. Yusof, N. Everdell, E. M. C. Hillman, D. T. Delpy, S. R. Arridge, T. Austin, J. H. Meek, and J. S. Wyatt, “Three-dimensional optical tomography of the premature infant brain,” Phys. Med. Biol.47, 4155–4166 (2002).
[CrossRef] [PubMed]

M. Schweiger, S. R. Arridge, and D. T. Delpy, “Application of the finite-element method for the forward and inverse model in optical tomography,” J. Math. Imaging Vis.3, 263–283 (1993).
[CrossRef]

Douek, M.

T. Yates, C. Hebdan, A. Gibson, N. Everdell, S. R. Arridge, and M. Douek, “Optical tomography of the breast using a multi-channel time-resolved imager,” Phys. Med. Biol.50, 2503–2517 (2005).
[CrossRef] [PubMed]

Douiri, A.

A. Douiri, M. Schweiger, J. Riley, and S. R. Arridge, “Anisotropic diffusion regularization methods for diffuse optical tomography using edge prior information,” Meas. Sci. Tech.18, 87–95 (2007).
[CrossRef]

Douraghy, A.

Dutta, J.

J. Dutta, S. Ahn, C. Li, S. R. Cherry, and R. M. Leahy, “Joint L1 and total variation regularization for fluorescence molecular tomography,” Phys. Med. Biol.57, 1459–1476 (2012).
[CrossRef] [PubMed]

Ebert, W.

J. Barkhausen, W. Ebert, J. F. Debatin, and H.-J. Weinmann, “Imaging of myocardial infarction: comparison of magnevist and gadophrin-3 in rabbits,” J. Am. Coll. Cardiol.39(8), 1392–1398 (2002).
[CrossRef] [PubMed]

Eftekhar, A. A.

Everdell, N.

T. Yates, C. Hebdan, A. Gibson, N. Everdell, S. R. Arridge, and M. Douek, “Optical tomography of the breast using a multi-channel time-resolved imager,” Phys. Med. Biol.50, 2503–2517 (2005).
[CrossRef] [PubMed]

J. C. Hebden, A. Gibson, R. M. Yusof, N. Everdell, E. M. C. Hillman, D. T. Delpy, S. R. Arridge, T. Austin, J. H. Meek, and J. S. Wyatt, “Three-dimensional optical tomography of the premature infant brain,” Phys. Med. Biol.47, 4155–4166 (2002).
[CrossRef] [PubMed]

Everdell, N. L.

A. P. Gibson, T. Austin, N. L. Everdell, M. Schweiger, S. R. Arridge, J. H. Meek, J. S. Wyatt, D. T. Delpy, and J. C. Hebden, “Three-dimensional whole-head optical tomography for passive motor evoked responses in the neonate,” NueroImage30, 521–528 (2006).
[CrossRef]

Feng, J.

Freiberger, M.

Gao, F.

Gerega, A.

Gibson, A.

T. Yates, C. Hebdan, A. Gibson, N. Everdell, S. R. Arridge, and M. Douek, “Optical tomography of the breast using a multi-channel time-resolved imager,” Phys. Med. Biol.50, 2503–2517 (2005).
[CrossRef] [PubMed]

J. C. Hebden, A. Gibson, R. M. Yusof, N. Everdell, E. M. C. Hillman, D. T. Delpy, S. R. Arridge, T. Austin, J. H. Meek, and J. S. Wyatt, “Three-dimensional optical tomography of the premature infant brain,” Phys. Med. Biol.47, 4155–4166 (2002).
[CrossRef] [PubMed]

Gibson, A. P.

C. Panagiotou, S. Somayajula, A. P. Gibson, M. Schweiger, R. M. Leahy, and S. R. Arridge, “Information theoretic regularization in diffuse optical tomography,” J. Opt. Soc. Am. A26(5), 1277–1290 (2009).
[CrossRef]

A. P. Gibson, T. Austin, N. L. Everdell, M. Schweiger, S. R. Arridge, J. H. Meek, J. S. Wyatt, D. T. Delpy, and J. C. Hebden, “Three-dimensional whole-head optical tomography for passive motor evoked responses in the neonate,” NueroImage30, 521–528 (2006).
[CrossRef]

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

Goch, G.

Graves, E.

E. Graves, J. Ripoll, R. Weissleder, and V. Ntziachristos, “A submillimeter resolution fluorescence molecular imaging system for small animal imaging,” Med. Phys.30, 901–911 (2003).
[CrossRef] [PubMed]

Han, D.

D. Han, J. Tian, S. Zhu, J. Feng, C. Qin, B. Zhang, and X. Yang, “A fast reconstruction algorithm for fluorescence molecular tomography with sparsity regularization,” Opt. Express18(8), 8630–8646 (2010).
[CrossRef] [PubMed]

D. Han, X. Yang, K. Liu, C. Qin, B. Zhang, X. Ma, and J. Tian, “Efficient reconstruction method for L1 regularization in fluorescence molecular tomography,” Appl. Opt49(36), 6930–6937 (2010).
[CrossRef] [PubMed]

Hawrysz, D. J.

D. J. Hawrysz and E. M. Sevick-Muraca, “Developments toward diagnostic breast cancer imaging using near-infrared optical measurements and fluorescent contrast agents,” Neoplasia2(5), 388–417 (2000).
[CrossRef]

He, Z.

Z. He, A. Cichocki, R. Zdunek, and S. Xie, “Improved FOCCUS method with conjugate gradient iterations,” IEEE Trans. Signal Process.57(1), 399–404 (2009).
[CrossRef]

Hebdan, C.

T. Yates, C. Hebdan, A. Gibson, N. Everdell, S. R. Arridge, and M. Douek, “Optical tomography of the breast using a multi-channel time-resolved imager,” Phys. Med. Biol.50, 2503–2517 (2005).
[CrossRef] [PubMed]

Hebden, J. C.

A. P. Gibson, T. Austin, N. L. Everdell, M. Schweiger, S. R. Arridge, J. H. Meek, J. S. Wyatt, D. T. Delpy, and J. C. Hebden, “Three-dimensional whole-head optical tomography for passive motor evoked responses in the neonate,” NueroImage30, 521–528 (2006).
[CrossRef]

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

J. C. Hebden, A. Gibson, R. M. Yusof, N. Everdell, E. M. C. Hillman, D. T. Delpy, S. R. Arridge, T. Austin, J. H. Meek, and J. S. Wyatt, “Three-dimensional optical tomography of the premature infant brain,” Phys. Med. Biol.47, 4155–4166 (2002).
[CrossRef] [PubMed]

Hillman, E. M. C.

J. C. Hebden, A. Gibson, R. M. Yusof, N. Everdell, E. M. C. Hillman, D. T. Delpy, S. R. Arridge, T. Austin, J. H. Meek, and J. S. Wyatt, “Three-dimensional optical tomography of the premature infant brain,” Phys. Med. Biol.47, 4155–4166 (2002).
[CrossRef] [PubMed]

Hiltunen, P.

Hiroe, N.

Hoshi, Y.

Huang, J.

Huang, M.

Hyde, D.

Inoue, Y.

Jacob, M.

Jiang, S.

Joshi, A.

Kavuri, V. C.

Kosaka, T.

Lasser, T.

Leahy, R. M.

J. Dutta, S. Ahn, C. Li, S. R. Cherry, and R. M. Leahy, “Joint L1 and total variation regularization for fluorescence molecular tomography,” Phys. Med. Biol.57, 1459–1476 (2012).
[CrossRef] [PubMed]

C. Panagiotou, S. Somayajula, A. P. Gibson, M. Schweiger, R. M. Leahy, and S. R. Arridge, “Information theoretic regularization in diffuse optical tomography,” J. Opt. Soc. Am. A26(5), 1277–1290 (2009).
[CrossRef]

Li, A.

G. Boverman, E. L. Miller, A. Li, Q. Zhang, T. Chaves, D. H. Brooks, and D. A. Boas, “Quantitative spectroscopic optical tomography of the breast guided by imperfect a priori structural information,” Phys. Med. Biol.50, 3941–3956 (2005).
[CrossRef] [PubMed]

Li, C.

J. Dutta, S. Ahn, C. Li, S. R. Cherry, and R. M. Leahy, “Joint L1 and total variation regularization for fluorescence molecular tomography,” Phys. Med. Biol.57, 1459–1476 (2012).
[CrossRef] [PubMed]

Liang, J.

Liebert, A.

Lin, Z.-J.

Liu, H.

Liu, K.

D. Han, X. Yang, K. Liu, C. Qin, B. Zhang, X. Ma, and J. Tian, “Efficient reconstruction method for L1 regularization in fluorescence molecular tomography,” Appl. Opt49(36), 6930–6937 (2010).
[CrossRef] [PubMed]

Lösterberg, U.

Lu, Y.

Ma, X.

D. Han, X. Yang, K. Liu, C. Qin, B. Zhang, X. Ma, and J. Tian, “Efficient reconstruction method for L1 regularization in fluorescence molecular tomography,” Appl. Opt49(36), 6930–6937 (2010).
[CrossRef] [PubMed]

Marjono, A.

McBride, T. O.

Meek, J. H.

A. P. Gibson, T. Austin, N. L. Everdell, M. Schweiger, S. R. Arridge, J. H. Meek, J. S. Wyatt, D. T. Delpy, and J. C. Hebden, “Three-dimensional whole-head optical tomography for passive motor evoked responses in the neonate,” NueroImage30, 521–528 (2006).
[CrossRef]

J. C. Hebden, A. Gibson, R. M. Yusof, N. Everdell, E. M. C. Hillman, D. T. Delpy, S. R. Arridge, T. Austin, J. H. Meek, and J. S. Wyatt, “Three-dimensional optical tomography of the premature infant brain,” Phys. Med. Biol.47, 4155–4166 (2002).
[CrossRef] [PubMed]

Milej, D.

Millane, R. P.

Miller, E. L.

G. Boverman, E. L. Miller, A. Li, Q. Zhang, T. Chaves, D. H. Brooks, and D. A. Boas, “Quantitative spectroscopic optical tomography of the breast guided by imperfect a priori structural information,” Phys. Med. Biol.50, 3941–3956 (2005).
[CrossRef] [PubMed]

Milstein, A. B.

Mohajerani, P.

Mycek, M.-A.

K. Vishwanath, B. Pogue, and M.-A. Mycek, “Quantitative fluorescence lifetime spectroscopy in turbid media: comparison of theoretical, experimental and computational method,” Phys. Med. Biol.47, 3387–3405 (2002).
[CrossRef] [PubMed]

Nehorai, A.

Neifeld, M. A.

Ntziachristos, V.

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

V. Ntziachristos, J. Ripoll, L. V. Wang, and R. Weissleder, “Looking and listening to light: the evolution of whole-body photonic imaging,” Nat. Biotechnol.23(3), 313–320 (2005).
[CrossRef] [PubMed]

E. Graves, J. Ripoll, R. Weissleder, and V. Ntziachristos, “A submillimeter resolution fluorescence molecular imaging system for small animal imaging,” Med. Phys.30, 901–911 (2003).
[CrossRef] [PubMed]

V. Ntziachristos, C.-H. Yung, C. Bremerand, and R. Weissleder, “Fluorescence molecular tomography resolves protease activity in vivo,” Nat. Med.8(7), 757–760 (2002).
[CrossRef] [PubMed]

Oh, S.

Okawa, S.

Paithankar, D. Y.

Panagiotou, C.

Patterson, M. S.

Paulsen, K. D.

Peng, K.

Pogue, B.

K. Vishwanath, B. Pogue, and M.-A. Mycek, “Quantitative fluorescence lifetime spectroscopy in turbid media: comparison of theoretical, experimental and computational method,” Phys. Med. Biol.47, 3387–3405 (2002).
[CrossRef] [PubMed]

Pogue, B. W.

Prahl, S. A.

W. F. Cheong, S. A. Prahl, and A. J. Welch, “A review of the optical properties of biological tissues,” IEEE J. Quantum Electron.26, 2166–2185 (1990).
[CrossRef]

Prewitt, J.

Qin, C.

D. Han, X. Yang, K. Liu, C. Qin, B. Zhang, X. Ma, and J. Tian, “Efficient reconstruction method for L1 regularization in fluorescence molecular tomography,” Appl. Opt49(36), 6930–6937 (2010).
[CrossRef] [PubMed]

D. Han, J. Tian, S. Zhu, J. Feng, C. Qin, B. Zhang, and X. Yang, “A fast reconstruction algorithm for fluorescence molecular tomography with sparsity regularization,” Opt. Express18(8), 8630–8646 (2010).
[CrossRef] [PubMed]

Qu, X.

Riley, J.

A. Douiri, M. Schweiger, J. Riley, and S. R. Arridge, “Anisotropic diffusion regularization methods for diffuse optical tomography using edge prior information,” Meas. Sci. Tech.18, 87–95 (2007).
[CrossRef]

Ripoll, J.

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

V. Ntziachristos, J. Ripoll, L. V. Wang, and R. Weissleder, “Looking and listening to light: the evolution of whole-body photonic imaging,” Nat. Biotechnol.23(3), 313–320 (2005).
[CrossRef] [PubMed]

E. Graves, J. Ripoll, R. Weissleder, and V. Ntziachristos, “A submillimeter resolution fluorescence molecular imaging system for small animal imaging,” Med. Phys.30, 901–911 (2003).
[CrossRef] [PubMed]

Sato, M.

Scharfetter, H.

Schweiger, M.

C. Panagiotou, S. Somayajula, A. P. Gibson, M. Schweiger, R. M. Leahy, and S. R. Arridge, “Information theoretic regularization in diffuse optical tomography,” J. Opt. Soc. Am. A26(5), 1277–1290 (2009).
[CrossRef]

A. Douiri, M. Schweiger, J. Riley, and S. R. Arridge, “Anisotropic diffusion regularization methods for diffuse optical tomography using edge prior information,” Meas. Sci. Tech.18, 87–95 (2007).
[CrossRef]

A. P. Gibson, T. Austin, N. L. Everdell, M. Schweiger, S. R. Arridge, J. H. Meek, J. S. Wyatt, D. T. Delpy, and J. C. Hebden, “Three-dimensional whole-head optical tomography for passive motor evoked responses in the neonate,” NueroImage30, 521–528 (2006).
[CrossRef]

M. Schweiger, S. R. Arridge, and D. T. Delpy, “Application of the finite-element method for the forward and inverse model in optical tomography,” J. Math. Imaging Vis.3, 263–283 (1993).
[CrossRef]

Sevick-Muraca, E. M.

Shankar, P. M.

Shimokawa, T.

Somayajula, S.

Somersalo, E.

Soubret, A.

Stout, D.

Tian, F.

Tian, J.

Tian, Y.

P. Xu, Y. Tian, H. Chen, and D. Yao, “Lp Norm Iterative Sparse Solution for EEG Source Localization,” IEEE Trans. Biomed. Eng.54(3), 400–409 (2007).
[CrossRef] [PubMed]

Toczylowska, B.

Vishwanath, K.

K. Vishwanath, B. Pogue, and M.-A. Mycek, “Quantitative fluorescence lifetime spectroscopy in turbid media: comparison of theoretical, experimental and computational method,” Phys. Med. Biol.47, 3387–3405 (2002).
[CrossRef] [PubMed]

Vogel, C. R.

C. R. Vogel, Computational Methods for Inverse Problems (Frontiers in Applied Mathematics) (SIAM, Philadelphia, 2002).
[CrossRef]

Wang, L. V.

V. Ntziachristos, J. Ripoll, L. V. Wang, and R. Weissleder, “Looking and listening to light: the evolution of whole-body photonic imaging,” Nat. Biotechnol.23(3), 313–320 (2005).
[CrossRef] [PubMed]

Webb, K.

Weinmann, H.-J.

J. Barkhausen, W. Ebert, J. F. Debatin, and H.-J. Weinmann, “Imaging of myocardial infarction: comparison of magnevist and gadophrin-3 in rabbits,” J. Am. Coll. Cardiol.39(8), 1392–1398 (2002).
[CrossRef] [PubMed]

Weissleder, R.

R. Weissleder, “Molecular imaging in cancer,” Science321, 1168–1171 (2006).
[CrossRef]

V. Ntziachristos, J. Ripoll, L. V. Wang, and R. Weissleder, “Looking and listening to light: the evolution of whole-body photonic imaging,” Nat. Biotechnol.23(3), 313–320 (2005).
[CrossRef] [PubMed]

E. Graves, J. Ripoll, R. Weissleder, and V. Ntziachristos, “A submillimeter resolution fluorescence molecular imaging system for small animal imaging,” Med. Phys.30, 901–911 (2003).
[CrossRef] [PubMed]

V. Ntziachristos, C.-H. Yung, C. Bremerand, and R. Weissleder, “Fluorescence molecular tomography resolves protease activity in vivo,” Nat. Med.8(7), 757–760 (2002).
[CrossRef] [PubMed]

Welch, A. J.

W. F. Cheong, S. A. Prahl, and A. J. Welch, “A review of the optical properties of biological tissues,” IEEE J. Quantum Electron.26, 2166–2185 (1990).
[CrossRef]

Wyatt, J. S.

A. P. Gibson, T. Austin, N. L. Everdell, M. Schweiger, S. R. Arridge, J. H. Meek, J. S. Wyatt, D. T. Delpy, and J. C. Hebden, “Three-dimensional whole-head optical tomography for passive motor evoked responses in the neonate,” NueroImage30, 521–528 (2006).
[CrossRef]

J. C. Hebden, A. Gibson, R. M. Yusof, N. Everdell, E. M. C. Hillman, D. T. Delpy, S. R. Arridge, T. Austin, J. H. Meek, and J. S. Wyatt, “Three-dimensional optical tomography of the premature infant brain,” Phys. Med. Biol.47, 4155–4166 (2002).
[CrossRef] [PubMed]

Xie, S.

Z. He, A. Cichocki, R. Zdunek, and S. Xie, “Improved FOCCUS method with conjugate gradient iterations,” IEEE Trans. Signal Process.57(1), 399–404 (2009).
[CrossRef]

Xu, P.

P. Xu, Y. Tian, H. Chen, and D. Yao, “Lp Norm Iterative Sparse Solution for EEG Source Localization,” IEEE Trans. Biomed. Eng.54(3), 400–409 (2007).
[CrossRef] [PubMed]

Yalavarthy, P. K.

Yamada, Y.

Yamashita, O.

Yang, X.

D. Han, J. Tian, S. Zhu, J. Feng, C. Qin, B. Zhang, and X. Yang, “A fast reconstruction algorithm for fluorescence molecular tomography with sparsity regularization,” Opt. Express18(8), 8630–8646 (2010).
[CrossRef] [PubMed]

D. Han, X. Yang, K. Liu, C. Qin, B. Zhang, X. Ma, and J. Tian, “Efficient reconstruction method for L1 regularization in fluorescence molecular tomography,” Appl. Opt49(36), 6930–6937 (2010).
[CrossRef] [PubMed]

Yano, A.

Yao, D.

P. Xu, Y. Tian, H. Chen, and D. Yao, “Lp Norm Iterative Sparse Solution for EEG Source Localization,” IEEE Trans. Biomed. Eng.54(3), 400–409 (2007).
[CrossRef] [PubMed]

Yates, T.

T. Yates, C. Hebdan, A. Gibson, N. Everdell, S. R. Arridge, and M. Douek, “Optical tomography of the breast using a multi-channel time-resolved imager,” Phys. Med. Biol.50, 2503–2517 (2005).
[CrossRef] [PubMed]

Yi, H.

Yung, C.-H.

V. Ntziachristos, C.-H. Yung, C. Bremerand, and R. Weissleder, “Fluorescence molecular tomography resolves protease activity in vivo,” Nat. Med.8(7), 757–760 (2002).
[CrossRef] [PubMed]

Yusof, R. M.

J. C. Hebden, A. Gibson, R. M. Yusof, N. Everdell, E. M. C. Hillman, D. T. Delpy, S. R. Arridge, T. Austin, J. H. Meek, and J. S. Wyatt, “Three-dimensional optical tomography of the premature infant brain,” Phys. Med. Biol.47, 4155–4166 (2002).
[CrossRef] [PubMed]

Zdunek, R.

Z. He, A. Cichocki, R. Zdunek, and S. Xie, “Improved FOCCUS method with conjugate gradient iterations,” IEEE Trans. Signal Process.57(1), 399–404 (2009).
[CrossRef]

Zhang, B.

D. Han, J. Tian, S. Zhu, J. Feng, C. Qin, B. Zhang, and X. Yang, “A fast reconstruction algorithm for fluorescence molecular tomography with sparsity regularization,” Opt. Express18(8), 8630–8646 (2010).
[CrossRef] [PubMed]

D. Han, X. Yang, K. Liu, C. Qin, B. Zhang, X. Ma, and J. Tian, “Efficient reconstruction method for L1 regularization in fluorescence molecular tomography,” Appl. Opt49(36), 6930–6937 (2010).
[CrossRef] [PubMed]

Zhang, Q.

G. Boverman, E. L. Miller, A. Li, Q. Zhang, T. Chaves, D. H. Brooks, and D. A. Boas, “Quantitative spectroscopic optical tomography of the breast guided by imperfect a priori structural information,” Phys. Med. Biol.50, 3941–3956 (2005).
[CrossRef] [PubMed]

A. B. Milstein, S. Oh, K. Webb, C. A. Bouman, Q. Zhang, D. A. Boas, and R. P. Millane, “Fluorescence optical diffusion tomography,” Appl. Opt.42(16), 3081–3094 (2003).
[CrossRef] [PubMed]

Zhang, X.

Zhou, Y.

Zhu, Q.

Zhu, S.

Zieminska, E.

Appl. Opt (1)

D. Han, X. Yang, K. Liu, C. Qin, B. Zhang, X. Ma, and J. Tian, “Efficient reconstruction method for L1 regularization in fluorescence molecular tomography,” Appl. Opt49(36), 6930–6937 (2010).
[CrossRef] [PubMed]

Appl. Opt. (7)

M. Freiberger, C. Clason, and H. Scharfetter, “Total variation regularization for nonlinear fluorescence tomography with an augmented Lagrangian splitting approach,” Appl. Opt.49(19), 3741–3747 (2010).
[CrossRef] [PubMed]

H. Yi, D. Chen, X. Qu, K. Peng, X. Chen, Y. Zhou, J. Tian, and J. Liang, “Multilevel, hybrid regularization method for reconstruction of florescent molecular tomography,” Appl. Opt.51(7), 975–986 (2012).
[CrossRef] [PubMed]

P. Mohajerani, A. A. Eftekhar, J. Huang, and A. Adibi, “Optimal sparse solution for fluorescent diffuse optical tomography: theory and phantom experimental results,” Appl. Opt.46(10), 1679–1685 (2007).
[CrossRef] [PubMed]

D. Y. Paithankar, U. A. Chen, B. W. Pogue, M. S. Patterson, and E. M. Sevick-Muraca, “Imaging of fluorescent yield and lifetime from multiply scattered light reemitted from random medium,” Appl. Opt.36(10), 2260–2272 (1997).
[CrossRef] [PubMed]

B. W. Pogue, T. O. McBride, J. Prewitt, U. Lösterberg, and K. D. Paulsen, “Spatially variant regularization improves diffuse optical tomography,” Appl. Opt.38(13), 2950–2961 (1999).
[CrossRef]

A. B. Milstein, S. Oh, K. Webb, C. A. Bouman, Q. Zhang, D. A. Boas, and R. P. Millane, “Fluorescence optical diffusion tomography,” Appl. Opt.42(16), 3081–3094 (2003).
[CrossRef] [PubMed]

M. Huang and Q. Zhu, “Dual-mesh optical tomography reconstruction method with a depth correction that uses a priori ultrasound information,” Appl. Opt.43(8), 1654–1662 (2006).
[CrossRef]

Biomed. Opt. Express (3)

IEEE J. Quantum Electron. (1)

W. F. Cheong, S. A. Prahl, and A. J. Welch, “A review of the optical properties of biological tissues,” IEEE J. Quantum Electron.26, 2166–2185 (1990).
[CrossRef]

IEEE Trans. Biomed. Eng. (1)

P. Xu, Y. Tian, H. Chen, and D. Yao, “Lp Norm Iterative Sparse Solution for EEG Source Localization,” IEEE Trans. Biomed. Eng.54(3), 400–409 (2007).
[CrossRef] [PubMed]

IEEE Trans. Signal Process. (1)

Z. He, A. Cichocki, R. Zdunek, and S. Xie, “Improved FOCCUS method with conjugate gradient iterations,” IEEE Trans. Signal Process.57(1), 399–404 (2009).
[CrossRef]

Inverse Prob. (1)

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

J. Am. Coll. Cardiol. (1)

J. Barkhausen, W. Ebert, J. F. Debatin, and H.-J. Weinmann, “Imaging of myocardial infarction: comparison of magnevist and gadophrin-3 in rabbits,” J. Am. Coll. Cardiol.39(8), 1392–1398 (2002).
[CrossRef] [PubMed]

J. Math. Imaging Vis. (1)

M. Schweiger, S. R. Arridge, and D. T. Delpy, “Application of the finite-element method for the forward and inverse model in optical tomography,” J. Math. Imaging Vis.3, 263–283 (1993).
[CrossRef]

J. Opt. Soc. Am. A (2)

Meas. Sci. Tech. (1)

A. Douiri, M. Schweiger, J. Riley, and S. R. Arridge, “Anisotropic diffusion regularization methods for diffuse optical tomography using edge prior information,” Meas. Sci. Tech.18, 87–95 (2007).
[CrossRef]

Med. Phys. (1)

E. Graves, J. Ripoll, R. Weissleder, and V. Ntziachristos, “A submillimeter resolution fluorescence molecular imaging system for small animal imaging,” Med. Phys.30, 901–911 (2003).
[CrossRef] [PubMed]

Nat. Biotechnol. (1)

V. Ntziachristos, J. Ripoll, L. V. Wang, and R. Weissleder, “Looking and listening to light: the evolution of whole-body photonic imaging,” Nat. Biotechnol.23(3), 313–320 (2005).
[CrossRef] [PubMed]

Nat. Med. (1)

V. Ntziachristos, C.-H. Yung, C. Bremerand, and R. Weissleder, “Fluorescence molecular tomography resolves protease activity in vivo,” Nat. Med.8(7), 757–760 (2002).
[CrossRef] [PubMed]

Neoplasia (1)

D. J. Hawrysz and E. M. Sevick-Muraca, “Developments toward diagnostic breast cancer imaging using near-infrared optical measurements and fluorescent contrast agents,” Neoplasia2(5), 388–417 (2000).
[CrossRef]

NueroImage (1)

A. P. Gibson, T. Austin, N. L. Everdell, M. Schweiger, S. R. Arridge, J. H. Meek, J. S. Wyatt, D. T. Delpy, and J. C. Hebden, “Three-dimensional whole-head optical tomography for passive motor evoked responses in the neonate,” NueroImage30, 521–528 (2006).
[CrossRef]

Opt. Express (10)

P. Hiltunen, D. Calvetti, and E. Somersalo, “An adaptive smoothness regularization algorithm for optical tomography,” Opt. Express16(24), 19957–19977 (2008).
[CrossRef] [PubMed]

N. Cao, A. Nehorai, and M. Jacob, “Image reconstruction for diffuse optical tomography using sparsity regularization and expectation-maximization algorithm,” Opt. Express, 15(21), 13695–13708 (2007).
[CrossRef] [PubMed]

T. Shimokawa, T. Kosaka, O. Yamashita, N. Hiroe, T. Amita, Y. Inoue, and M. Sato, “Hierarchical Bayesian estimation improves depth accuracy and spatial resolution of diffuse optical tomography,” Opt. Express20(18), 20427–20446 (2012).
[CrossRef] [PubMed]

P. K. Yalavarthy, B. W. Pogue, H. Dehghani, C. M. Carpenter, S. Jiang, and K. D. Paulsen, “Structural information within regularization matrices improves near infrared diffuse optical tomography,” Opt. Express15(13), 8043–8058 (2007).
[CrossRef] [PubMed]

D. Han, J. Tian, S. Zhu, J. Feng, C. Qin, B. Zhang, and X. Yang, “A fast reconstruction algorithm for fluorescence molecular tomography with sparsity regularization,” Opt. Express18(8), 8630–8646 (2010).
[CrossRef] [PubMed]

S. R. Arridge, “A gradient-based optimization scheme for optical tomography,” Opt. Express12(6), 213–226 (1998).
[CrossRef]

Y. Lu, X. Zhang, A. Douraghy, D. Stout, J. Tian, T. F. Chan, and A. F. Chatziioannou, “Source reconstruction for spectrally-resolved bioluminescence tomography with aparse A priori information,” Opt. Express17(10), 8062–8088 (2009).
[CrossRef] [PubMed]

S. Okawa and Y. Yamada, “Reconstruction of fluorescence/bioluminescence sources in biological medium with spatial filter,” Opt. Express18(12), 13151–13172 (2010).
[CrossRef] [PubMed]

A. Joshi, W. Bangerth, and E. M. Sevick-Muraca, “Adaptive finite element based tomography for fluorescence optical imaging in tissue,” Opt. Express, 12(22), 5402–5417 (2004).
[CrossRef] [PubMed]

A. Marjono, A. Yano, S. Okawa, F. Gao, and Y. Yamada, “Total light approach of time-domain fluorescence diffuse optical tomography,” Opt. Express, 16(19), 15268–15285 (2008).
[CrossRef] [PubMed]

Opt. Lett. (1)

Phys. Med. Biol. (6)

T. Yates, C. Hebdan, A. Gibson, N. Everdell, S. R. Arridge, and M. Douek, “Optical tomography of the breast using a multi-channel time-resolved imager,” Phys. Med. Biol.50, 2503–2517 (2005).
[CrossRef] [PubMed]

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

G. Boverman, E. L. Miller, A. Li, Q. Zhang, T. Chaves, D. H. Brooks, and D. A. Boas, “Quantitative spectroscopic optical tomography of the breast guided by imperfect a priori structural information,” Phys. Med. Biol.50, 3941–3956 (2005).
[CrossRef] [PubMed]

J. C. Hebden, A. Gibson, R. M. Yusof, N. Everdell, E. M. C. Hillman, D. T. Delpy, S. R. Arridge, T. Austin, J. H. Meek, and J. S. Wyatt, “Three-dimensional optical tomography of the premature infant brain,” Phys. Med. Biol.47, 4155–4166 (2002).
[CrossRef] [PubMed]

K. Vishwanath, B. Pogue, and M.-A. Mycek, “Quantitative fluorescence lifetime spectroscopy in turbid media: comparison of theoretical, experimental and computational method,” Phys. Med. Biol.47, 3387–3405 (2002).
[CrossRef] [PubMed]

J. Dutta, S. Ahn, C. Li, S. R. Cherry, and R. M. Leahy, “Joint L1 and total variation regularization for fluorescence molecular tomography,” Phys. Med. Biol.57, 1459–1476 (2012).
[CrossRef] [PubMed]

Science (1)

R. Weissleder, “Molecular imaging in cancer,” Science321, 1168–1171 (2006).
[CrossRef]

Other (1)

C. R. Vogel, Computational Methods for Inverse Problems (Frontiers in Applied Mathematics) (SIAM, Philadelphia, 2002).
[CrossRef]

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Figures (16)

Fig. 1
Fig. 1

(a) Schematics of the CW measurement system to acquire the surface fluorescence images of the measured object, and the angular positions of (b) excitation and (c) emission light.

Fig. 2
Fig. 2

The geometry of a cylindrical object, and true and reconstructed xy sectional images of the ICG concentration normalized by their maxima for Case (i). True images (first column), reconstructed images using the Tikhonov regularization (second column) and using the lp sparsity regularization with p = 1 (third column) and p = 0.5 (fourth column) for the depths of the true target being 4 mm (top row), 6 mm (middle row) and 9 mm (bottom row).

Fig. 3
Fig. 3

Reconstructed quantities of ICG in the VOI using the Tikhonov regularization (blue dashed line) and the lp sparsity regularization with p = 1 (green chained line) and p = 0.5 (red solid line) as a function of the depth of the target.

Fig. 4
Fig. 4

True and reconstructed xy sectional images of the ICG concentration normalized by their maxima for Case (ii). True images (first column), reconstructed images using the Tikhonov regularization (second column) and the lp sparsity regularization with p = 1 (third column) and p = 0.5 (fourth column) for the true quantity of ICG in the targets of 100 pmol (top row), 10 pmol (middle row) and 1 pmol (bottom row).

Fig. 5
Fig. 5

Reconstructed quantities of ICG in the VOI using the Tikhonov regularization (blue dashed line) and the lp sparsity regularization with p = 1 (green chained line) and p = 0.5 (red solid line) as a function of the true fluorophore quantity.

Fig. 6
Fig. 6

True and reconstructed xy sectional images of the normalized ICG concentration for Case (iii). True images (first column), reconstructed images using the Tikhonov regularization (second column) and the lp sparsity regularization with p = 1 (third column) and p = 0.5 (fourth column) for the true targets of 1 mm3 (top row), 8 mm3 (middle row) and 27 mm3 (bottom row).

Fig. 7
Fig. 7

True and reconstructed xy sectional images of the normalized ICG concentration for Case (iv). True images (first column), reconstructed images using the Tikhonov regularization (second column) and the lp sparsity regularization with p = 1 (third column) and p = 0.5 (fourth column) for the distances between the targets of 4 mm (top row), 6 mm (middle row) and 8 mm (bottom row).

Fig. 8
Fig. 8

The profiles of the reconstructed quantities of ICG along the line connecting the two target centers, Q(x), using the Tikhonov regularization (blue dashed line) and the lp sparsity regularization with p = 1 (green chained line) and p = 0.5 (red solid line) for Case (iv) when the distance between the two targets is (a) 4mm, (b) 6 mm and (c) 8 mm. The true quantities are 100 pmol for both targets.

Fig. 9
Fig. 9

True and reconstructed xy sectional images of the ICG concentration normalized by the maxima of the reconstructed ICG concentration for Case (v) for Case (v). True images (first column), reconstructed images using the Tikhonov regularization (second column) and the lp sparsity regularization with p = 1 (third column) and p = 0.5 (fourth column). The two targets are at the fixed positions but with different ICG quantities; 100 pmol and 75 pmol (top row), 100 pmol and 50 pmol (middle row), and 100 pmol and 25 pmol (bottom row).

Fig. 10
Fig. 10

Profiles of Q(x) reconstructed using the Tikhonov regularization (blue dashed line) and the lp sparsity regularization with p = 1 (green chained line) and p = 0.5 (red solid line) for Case (v). The target on the left hand side contain 100 pmol of ICG while the targets on the right hand side contain (a) 75 pmol, (b) 50 pmol and (c) 25 pmol of ICG.

Fig. 11
Fig. 11

Fluorescence surface images superimposed on the visible light images of the phantom acquired by Clairvivo OPT with 5 angular positions of the excitation light, Ex 1 to 5 (numbered in Fig. 1(b)), for the targets at the depths of (a) 4 mm, (b) 6 mm and (c) 9 mm. Five views of Emissions 4, 5, 1, 2, and 3 (numbered in Fig. 1(c)) are aligned from left to right in each images. Color bars indicate the photon counts per second.

Fig. 12
Fig. 12

True and reconstructed xy sectional images of the ICG concentration in the phantom experiments for the true targets at the depths of (a) 4 mm (top row), (b) 6 mm (middle row) and (c) 9 mm (bottom row); true images (first column), reconstructed images using the Tikhonov regularization (second column) and the lp sparsity regularization with p = 1 (third column) and p = 0.5 (fourth column).

Fig. 13
Fig. 13

Reconstructed quantities of ICG in the VOI using the Tikhonov regularization (blue dashed line) and the lp sparsity regularization with p = 1 (green chained line) and p = 0.5 (red solid line) as a function of the target depth of the target in the phantom experiment.

Fig. 14
Fig. 14

Fluorescence surface images of the mouse acquired by Clairvivo OPT with 5 angular positions of excitation light, Excitation 1 to 5 (numbered in Fig. 1(b)). Five views of Emission 4, 5, 1, 2, and 3 (numbered in Fig. 1(c)) are aligned from left to right in each image. Color bar indicates the photon counts per second.

Fig. 15
Fig. 15

MR images (first column) and reconstructed fluorescence tomographic images using the Tikhonov regularization (second column), and the lp sparsity regularization with p = 1 (third column) and p = 0.5 (fourth column). The sagittal (top row), coronal (middle row) and axial (bottom row) images are shown. Red circles in the MR images indicate the correct position of the target.

Fig. 16
Fig. 16

Reconstructed quantities of ICG, Q(y), (right) along the y-axis indicated in the reconstructed axial MR image (left). The reconstructed values using the Tikhonov regularization (blue dashed line), and the lp sparsity regularization with p = 1 (green chained line) and p = 0.5 (red solid line) are shown together with the true values (black dotted line).

Tables (2)

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Table 1 Summary of the conditions of simulations with single target and experiments

Tables Icon

Table 2 Summary of the conditions of simulations with multiple targets

Equations (10)

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{ D x ( r ) + μ a x ( r ) + ε N ( r ) } Φ x ( r ) = q 0 ( r ) ,
{ D m ( r ) + μ a m ( r ) } Φ m ( r ) = ε γ N ( r ) Φ x ( r )
F = H f ,
H = ( Γ 1 , 1 , 1 , 1 Γ 1 , 1 , 1 , l Γ 1 , 1 , 1 , L Γ 1 , 1 , 2 , 1 Γ 1 , 1 , 2 , l Γ 1 , 1 , 2 , L Γ 1 , 1 , K , 1 Γ 1 , 1 , K , l Γ 1 , 1 , K , L Γ 1 , 2 , 1 , 1 Γ 1 , 2 , 1 , l Γ 1 , 2 , 1 , L Γ 1 , 5 , K , 1 Γ 1 , 5 , K , l Γ 1 , 5 , 1 , L Γ 5 , 5 , K , 1 Γ 5 , 5 , K , l Γ 5 , 5 , K , L )
min f [ M H f 2 + λ l = 1 L | f l | p ] ,
f l = | z l | 2 / p sgn ( z l ) .
min z [ M H f ( z ) 2 + λ l = 1 L | z l | 2 ] ,
R VOI = x c 2.5 x c + 2.5 y c 2.5 y c + 2.5 z c 2.5 z c + 2.5 N ( x , y , z ) d z d y d x .
Q ( y ) = 0.5 0.5 25 25 N ( x , y , z ) d z d x .
Q ( x ) = 6 7 25 25 N ( x , y , z ) d z d y .

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