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[Crossref]

J. Shi, X. Cao, F. Liu, B. Zhang, J. Luo, and J. Bai, “Greedy reconstruction algorithm for fluorescence molecular tomography by means of truncated singular value decomposition conversion,” J. Opt. Soc. Am. A 30(3), 437–447 (2013).

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[Crossref]

A. K Jha, M. A Kupinski, H. H Barrett, E. Clarkson, and J. H Hartman, “Three-dimensional Neumann-series approach to model light transport in nonuniform media,” J. Opt. Soc. Am. A 29(9), 1885–1899 (2012).

[Crossref]

A. Jin, B. Yazici, A. Ale, and V. Ntziachristos, “Preconditioning of the fluorescence diffuse optical tomography sensing matrix based on compressive sensing,” Opt. Lett. 37(20), 4326–4328 (2012).

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N. C Biswal, A. Aguirre, Y. Xu, S. Zanganeh, Q. Zhu, C. Pavlik, M. B Smith, L. T Kuhn, and K. P Claffey, “Imaging tumor hypoxia by near-infrared fluorescence tomography,” J. Biomed. Opt. 16(6), 066009 (2011).

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[Crossref]
[PubMed]

S. Ahn, A. J. Chaudhari, F. Darvas, C. A. Bouman, and R. M. Leahy, “Fast iterative image reconstruction methods for fully 3D multispectral bioluminescence tomography,” Phys. Med. Biol. 53(14), 3921 (2008).

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[Crossref]
[PubMed]

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

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[Crossref]

N. V. Slavine, M. A. Lewis, E. Richer, and P. P. Antich, “Iterative reconstruction method for light emitting sources based on the diffusion equation,” Med. Phys. 33(1), 61–68 (2006).

[Crossref]
[PubMed]

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[Crossref]

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[Crossref]
[PubMed]

S. R. Arridge and J. C. Schotland, “Optical tomography: forward and inverse problems,” Inverse Probl. 25(12), 123010 (2009).

[Crossref]

SB Raymond, ATN Kumar, DA Boas, and BJ Bacskai, “Optimal parameters for near infrared fluorescence imaging of amyloid plaques in alzheimer’s disease mouse models,” Phys. Med. Biol. 54(20), 6201 (2009).

[Crossref]
[PubMed]

K. Lange, M. Bahn, and R. Little, “A theoretical study of some maximum likelihood algorithms for emission and transmission tomography,” IEEE Trans. Med. Imag. 6(2), 106–114 (1987).

[Crossref]

J. Shi, X. Cao, F. Liu, B. Zhang, J. Luo, and J. Bai, “Greedy reconstruction algorithm for fluorescence molecular tomography by means of truncated singular value decomposition conversion,” J. Opt. Soc. Am. A 30(3), 437–447 (2013).

[Crossref]

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

[Crossref]

A. K. Jha, E. Clarkson, M. A. Kupinski, and H. H. Barrett, “Joint reconstruction of activity and attenuation map using LM SPECT emission data,” Medical Imaging 2013: Physics of Medical Imaging 8668, 86681W (2013).

[Crossref]

A. K. Jha, M. A. Kupinski, T. Masumura, E. Clarkson, A. V. Maslov, and H. H. Barrett, “Simulating photon-transport in uniform media using the radiative transport equation: a study using the Neumann-series approach,” J. Opt. Soc. Am. A 29(8), 1741–1757 (2012).

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[Crossref]

N. C Biswal, A. Aguirre, Y. Xu, S. Zanganeh, Q. Zhu, C. Pavlik, M. B Smith, L. T Kuhn, and K. P Claffey, “Imaging tumor hypoxia by near-infrared fluorescence tomography,” J. Biomed. Opt. 16(6), 066009 (2011).

[Crossref]
[PubMed]

SB Raymond, ATN Kumar, DA Boas, and BJ Bacskai, “Optimal parameters for near infrared fluorescence imaging of amyloid plaques in alzheimer’s disease mouse models,” Phys. Med. Biol. 54(20), 6201 (2009).

[Crossref]
[PubMed]

S. Ahn, A. J. Chaudhari, F. Darvas, C. A. Bouman, and R. M. Leahy, “Fast iterative image reconstruction methods for fully 3D multispectral bioluminescence tomography,” Phys. Med. Biol. 53(14), 3921 (2008).

[Crossref]
[PubMed]

O. Lee, J. Kim, Y. Bresler, and J. Ye, “Compressive diffuse optical tomography: noniterative exact reconstruction using joint sparsity,” IEEE Trans. Med. Imag. 30(5), 1129–1142 (2011).

[Crossref]

A. M. Bruckstein, D. L. Donoho, and M. Elad, “From sparse solutions of systems of equations to sparse modeling of signals and images,” SIAM Rev. 51(1), 34–81 (2009).

[Crossref]

L. Cao and J. Peter, “Bayesian reconstruction strategy of fluorescence-mediated tomography using an integrated SPECT-CT-OT system,” Phys. Med. Biol. 55(9), 2693 (2010).

[Crossref]
[PubMed]

J. H. Chang, J. MM Anderson, and J. R Votaw, “Regularized image reconstruction algorithms for Positron Emission Tomography,” IEEE Trans. Med. Imag. 23(9), 1165–1175 (2004).

[Crossref]

G. Alexandrakis, F. R. Rannou, and A. F. Chatziioannou, “Tomographic bioluminescence imaging by use of a combined optical-PET (OPET) system: a computer simulation feasibility study,” Phys. Med. Biol. 50(17), 4225 (2005).

[Crossref]
[PubMed]

S. Ahn, A. J. Chaudhari, F. Darvas, C. A. Bouman, and R. M. Leahy, “Fast iterative image reconstruction methods for fully 3D multispectral bioluminescence tomography,” Phys. Med. Biol. 53(14), 3921 (2008).

[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(6), 1459 (2012).

[Crossref]
[PubMed]

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

[Crossref]
[PubMed]

N. C Biswal, A. Aguirre, Y. Xu, S. Zanganeh, Q. Zhu, C. Pavlik, M. B Smith, L. T Kuhn, and K. P Claffey, “Imaging tumor hypoxia by near-infrared fluorescence tomography,” J. Biomed. Opt. 16(6), 066009 (2011).

[Crossref]
[PubMed]

A. K. Jha, E. Clarkson, M. A. Kupinski, and H. H. Barrett, “Joint reconstruction of activity and attenuation map using LM SPECT emission data,” Medical Imaging 2013: Physics of Medical Imaging 8668, 86681W (2013).

[Crossref]

A. K Jha, M. A Kupinski, H. H Barrett, E. Clarkson, and J. H Hartman, “Three-dimensional Neumann-series approach to model light transport in nonuniform media,” J. Opt. Soc. Am. A 29(9), 1885–1899 (2012).

[Crossref]

A. K. Jha, M. A. Kupinski, T. Masumura, E. Clarkson, A. V. Maslov, and H. H. Barrett, “Simulating photon-transport in uniform media using the radiative transport equation: a study using the Neumann-series approach,” J. Opt. Soc. Am. A 29(8), 1741–1757 (2012).

[Crossref]

D. Ma, P. Wolf, A. V. Clough, and T. G. Schmidt, “The performance of MLEM for dynamic imaging from simulated few-view, multi-pinhole SPECT,” IEEE Trans. Nucl. Sci. 60(1), 115–123 (2013).

[Crossref]

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[Crossref]

L. Zhao, H. Yang, W. Cong, G. Wang, and X. Intes, “Lp regularization for early gate fluorescence molecular tomography,” Opt. Lett. 39(14), 4156–4159 (2014).

[Crossref]
[PubMed]

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S. Ahn, A. J. Chaudhari, F. Darvas, C. A. Bouman, and R. M. Leahy, “Fast iterative image reconstruction methods for fully 3D multispectral bioluminescence tomography,” Phys. Med. Biol. 53(14), 3921 (2008).

[Crossref]
[PubMed]

A. M. Bruckstein, D. L. Donoho, and M. Elad, “From sparse solutions of systems of equations to sparse modeling of signals and images,” SIAM Rev. 51(1), 34–81 (2009).

[Crossref]

Y. Zhu, A. K. Jha, J. K. Dreyer, H. N. D. Le, J. U. Kang, P. E. Roland, D. F. Wong, and A. Rahmim, “A three-step reconstruction method for fluorescence molecular tomography based on compressive sensing,” Proc. SPIE 10059, 1005911 (2017).

[Crossref]

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(6), 1459 (2012).

[Crossref]
[PubMed]

A. M. Bruckstein, D. L. Donoho, and M. Elad, “From sparse solutions of systems of equations to sparse modeling of signals and images,” SIAM Rev. 51(1), 34–81 (2009).

[Crossref]

G. Strangman, M. A. Franceschini, and D. A. Boas, “Factors affecting the accuracy of near-infrared spectroscopy concentration calculations for focal changes in oxygenation parameters,” Neuroimage 18(4), 865–879 (2003).

[Crossref]
[PubMed]

W. P. Segars, B. M. W. Tsui, E. C. Frey, G. A. Johnson, and S. S. Berr, “Development of a 4-D digital mouse phantom for molecular imaging research,” Mol. Imag. Biol. 6(3), 149–159 (2004).

[Crossref]

J. Llacer, E. Veklerov, K. J. Coakley, E. J. Hoffman, and J. Nunez, “Statistical analysis of maximum likelihood estimator images of human brain FDG PET studies,” IEEE Trans. Med. Imag. 12(2), 215–231 (1993).

[Crossref]

R. Yao, Q. Pian, and X. Intes, “Wide-field fluorescence molecular tomography with compressive sensing based preconditioning,” Biomed. Opt. Express 6(12), 4887–4898 (2015).

[Crossref]
[PubMed]

Q. Pian, R. Yao, L. Zhao, and X. Intes, “Hyperspectral time-resolved wide-field fluorescence molecular tomography based on structured light and single-pixel detection,” Opt. Lett. 40(3), 431–434 (2015).

[Crossref]
[PubMed]

L. Zhao, H. Yang, W. Cong, G. Wang, and X. Intes, “Lp regularization for early gate fluorescence molecular tomography,” Opt. Lett. 39(14), 4156–4159 (2014).

[Crossref]
[PubMed]

A. K. Jha, Y. Zhu, S. Arridge, D. F. Wong, and A. Rahmim, “Incorporating reflection boundary conditions in the Neumann series radiative transport equation: application to photon propagation and reconstruction in diffuse optical imaging,” Biomed. Opt. Express 9(4), 1389–1407 (2018).

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[Crossref]

A. K. Jha, E. Clarkson, M. A. Kupinski, and H. H. Barrett, “Joint reconstruction of activity and attenuation map using LM SPECT emission data,” Medical Imaging 2013: Physics of Medical Imaging 8668, 86681W (2013).

[Crossref]

A. K. Jha, M. A. Kupinski, T. Masumura, E. Clarkson, A. V. Maslov, and H. H. Barrett, “Simulating photon-transport in uniform media using the radiative transport equation: a study using the Neumann-series approach,” J. Opt. Soc. Am. A 29(8), 1741–1757 (2012).

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A. Jin, B. Yazici, and V. Ntziachristos, “Light illumination and detection patterns for fluorescence diffuse optical tomography based on compressive sensing,” IEEE Trans. Med. Imag. 23(6), 2609–2624 (2014).

[Crossref]

A. Jin, B. Yazici, A. Ale, and V. Ntziachristos, “Preconditioning of the fluorescence diffuse optical tomography sensing matrix based on compressive sensing,” Opt. Lett. 37(20), 4326–4328 (2012).

[Crossref]
[PubMed]

W. P. Segars, B. M. W. Tsui, E. C. Frey, G. A. Johnson, and S. S. Berr, “Development of a 4-D digital mouse phantom for molecular imaging research,” Mol. Imag. Biol. 6(3), 149–159 (2004).

[Crossref]

T. Tarvainen, M. Vauhkonen, V. Kolehmainen, S. R Arridge, and J. P Kaipio, “Coupled radiative transfer equation and diffusion approximation model for photon migration in turbid medium with low-scattering and non-scattering regions,” Phys. Med. Biol. 50(20), 4913 (2005).

[Crossref]
[PubMed]

Y. Zhu, A. K. Jha, J. K. Dreyer, H. N. D. Le, J. U. Kang, P. E. Roland, D. F. Wong, and A. Rahmim, “A three-step reconstruction method for fluorescence molecular tomography based on compressive sensing,” Proc. SPIE 10059, 1005911 (2017).

[Crossref]

Y. Vardi, L. Shepp, and L. Kaufman, “A statistical model for positron emission tomography,” J. Am. Stat. Assoc. 80(389), 8–20 (1985).

[Crossref]

O. Lee, J. Kim, Y. Bresler, and J. Ye, “Compressive diffuse optical tomography: noniterative exact reconstruction using joint sparsity,” IEEE Trans. Med. Imag. 30(5), 1129–1142 (2011).

[Crossref]

T. Tarvainen, M. Vauhkonen, V. Kolehmainen, S. R Arridge, and J. P Kaipio, “Coupled radiative transfer equation and diffusion approximation model for photon migration in turbid medium with low-scattering and non-scattering regions,” Phys. Med. Biol. 50(20), 4913 (2005).

[Crossref]
[PubMed]

G. Kontaxakis and L. G Strauss, “Maximum likelihood algorithms for image reconstruction in Positron Emission Tomography,” Radionuclides Oncol. 8, 73–106 (1998)

N. C Biswal, A. Aguirre, Y. Xu, S. Zanganeh, Q. Zhu, C. Pavlik, M. B Smith, L. T Kuhn, and K. P Claffey, “Imaging tumor hypoxia by near-infrared fluorescence tomography,” J. Biomed. Opt. 16(6), 066009 (2011).

[Crossref]
[PubMed]

SB Raymond, ATN Kumar, DA Boas, and BJ Bacskai, “Optimal parameters for near infrared fluorescence imaging of amyloid plaques in alzheimer’s disease mouse models,” Phys. Med. Biol. 54(20), 6201 (2009).

[Crossref]
[PubMed]

A. K. Jha, E. Clarkson, M. A. Kupinski, and H. H. Barrett, “Joint reconstruction of activity and attenuation map using LM SPECT emission data,” Medical Imaging 2013: Physics of Medical Imaging 8668, 86681W (2013).

[Crossref]

A. K. Jha, M. A. Kupinski, T. Masumura, E. Clarkson, A. V. Maslov, and H. H. Barrett, “Simulating photon-transport in uniform media using the radiative transport equation: a study using the Neumann-series approach,” J. Opt. Soc. Am. A 29(8), 1741–1757 (2012).

[Crossref]

K. Lange, M. Bahn, and R. Little, “A theoretical study of some maximum likelihood algorithms for emission and transmission tomography,” IEEE Trans. Med. Imag. 6(2), 106–114 (1987).

[Crossref]

Y. Zhu, A. K. Jha, J. K. Dreyer, H. N. D. Le, J. U. Kang, P. E. Roland, D. F. Wong, and A. Rahmim, “A three-step reconstruction method for fluorescence molecular tomography based on compressive sensing,” Proc. SPIE 10059, 1005911 (2017).

[Crossref]

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(6), 1459 (2012).

[Crossref]
[PubMed]

S. Ahn, A. J. Chaudhari, F. Darvas, C. A. Bouman, and R. M. Leahy, “Fast iterative image reconstruction methods for fully 3D multispectral bioluminescence tomography,” Phys. Med. Biol. 53(14), 3921 (2008).

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[Crossref]

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[Crossref]

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

[Crossref]
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[Crossref]
[PubMed]

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

[Crossref]
[PubMed]

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[Crossref]
[PubMed]

R. Yao, Q. Pian, and X. Intes, “Wide-field fluorescence molecular tomography with compressive sensing based preconditioning,” Biomed. Opt. Express 6(12), 4887–4898 (2015).

[Crossref]
[PubMed]

A. Jin, B. Yazici, and V. Ntziachristos, “Light illumination and detection patterns for fluorescence diffuse optical tomography based on compressive sensing,” IEEE Trans. Med. Imag. 23(6), 2609–2624 (2014).

[Crossref]

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[Crossref]
[PubMed]

L. Zhou and B. Yazici, “Discretization error analysis and adaptive meshing algorithms for fluorescence diffuse optical tomography in the presence of measurement noise,” IEEE Trans. Image Process. 20(4), 1049–1111 (2011).

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

[Crossref]
[PubMed]

O. Lee, J. Kim, Y. Bresler, and J. Ye, “Compressive diffuse optical tomography: noniterative exact reconstruction using joint sparsity,” IEEE Trans. Med. Imag. 30(5), 1129–1142 (2011).

[Crossref]

N. C Biswal, A. Aguirre, Y. Xu, S. Zanganeh, Q. Zhu, C. Pavlik, M. B Smith, L. T Kuhn, and K. P Claffey, “Imaging tumor hypoxia by near-infrared fluorescence tomography,” J. Biomed. Opt. 16(6), 066009 (2011).

[Crossref]
[PubMed]

J. Shi, X. Cao, F. Liu, B. Zhang, J. Luo, and J. Bai, “Greedy reconstruction algorithm for fluorescence molecular tomography by means of truncated singular value decomposition conversion,” J. Opt. Soc. Am. A 30(3), 437–447 (2013).

[Crossref]

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. Express 18(8), 8630–8646 (2010).

[Crossref]

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

[Crossref]
[PubMed]

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[Crossref]

Q. Pian, R. Yao, L. Zhao, and X. Intes, “Hyperspectral time-resolved wide-field fluorescence molecular tomography based on structured light and single-pixel detection,” Opt. Lett. 40(3), 431–434 (2015).

[Crossref]
[PubMed]

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[Crossref]
[PubMed]

L. Zhou and B. Yazici, “Discretization error analysis and adaptive meshing algorithms for fluorescence diffuse optical tomography in the presence of measurement noise,” IEEE Trans. Image Process. 20(4), 1049–1111 (2011).

L. Adhikari, D. Zhu, C. Li, and R. F. Marcia, “Nonconvex reconstruction for low-dimensional fluorescence molecular tomographic poisson observations,” 2015 IEEE International Conference on Image Processing (ICIP), 2404–2408 (2015).

N. C Biswal, A. Aguirre, Y. Xu, S. Zanganeh, Q. Zhu, C. Pavlik, M. B Smith, L. T Kuhn, and K. P Claffey, “Imaging tumor hypoxia by near-infrared fluorescence tomography,” J. Biomed. Opt. 16(6), 066009 (2011).

[Crossref]
[PubMed]

A. K. Jha, Y. Zhu, S. Arridge, D. F. Wong, and A. Rahmim, “Incorporating reflection boundary conditions in the Neumann series radiative transport equation: application to photon propagation and reconstruction in diffuse optical imaging,” Biomed. Opt. Express 9(4), 1389–1407 (2018).

[Crossref]
[PubMed]

Y. Zhu, A. K. Jha, J. K. Dreyer, H. N. D. Le, J. U. Kang, P. E. Roland, D. F. Wong, and A. Rahmim, “A three-step reconstruction method for fluorescence molecular tomography based on compressive sensing,” Proc. SPIE 10059, 1005911 (2017).

[Crossref]

Y. Zhu, A. K. Jha, D. Wong, and A. Rahmim, “Improved sparse reconstruction for fluorescence molecular tomography with poisson noise modeling,” Biophotonics Congress: Biomedical Optics Congress 2018, JTu3A.51 (2018).

V. Ntziachristos, “Fluorescence molecular imaging,” Annu. Rev. Biomed. Eng. 8,1–33 (2006).

[Crossref]
[PubMed]

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

[Crossref]
[PubMed]

R. Yao, Q. Pian, and X. Intes, “Wide-field fluorescence molecular tomography with compressive sensing based preconditioning,” Biomed. Opt. Express 6(12), 4887–4898 (2015).

[Crossref]
[PubMed]

O. Lehtikangas, T. Tarvainen, and A. D. Kim, “Modeling boundary measurements of scattered light using the corrected diffusion approximation,” Biomed. Opt. Express 3(3), 552–571 (2012).

[Crossref]
[PubMed]

A. K. Jha, Y. Zhu, S. Arridge, D. F. Wong, and A. Rahmim, “Incorporating reflection boundary conditions in the Neumann series radiative transport equation: application to photon propagation and reconstruction in diffuse optical imaging,” Biomed. Opt. Express 9(4), 1389–1407 (2018).

[Crossref]
[PubMed]

L. Zhou and B. Yazici, “Discretization error analysis and adaptive meshing algorithms for fluorescence diffuse optical tomography in the presence of measurement noise,” IEEE Trans. Image Process. 20(4), 1049–1111 (2011).

O. Lee, J. Kim, Y. Bresler, and J. Ye, “Compressive diffuse optical tomography: noniterative exact reconstruction using joint sparsity,” IEEE Trans. Med. Imag. 30(5), 1129–1142 (2011).

[Crossref]

K. Lange, M. Bahn, and R. Little, “A theoretical study of some maximum likelihood algorithms for emission and transmission tomography,” IEEE Trans. Med. Imag. 6(2), 106–114 (1987).

[Crossref]

J. Llacer, E. Veklerov, K. J. Coakley, E. J. Hoffman, and J. Nunez, “Statistical analysis of maximum likelihood estimator images of human brain FDG PET studies,” IEEE Trans. Med. Imag. 12(2), 215–231 (1993).

[Crossref]

A. Jin, B. Yazici, and V. Ntziachristos, “Light illumination and detection patterns for fluorescence diffuse optical tomography based on compressive sensing,” IEEE Trans. Med. Imag. 23(6), 2609–2624 (2014).

[Crossref]

J. H. Chang, J. MM Anderson, and J. R Votaw, “Regularized image reconstruction algorithms for Positron Emission Tomography,” IEEE Trans. Med. Imag. 23(9), 1165–1175 (2004).

[Crossref]

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

[Crossref]

D. Ma, P. Wolf, A. V. Clough, and T. G. Schmidt, “The performance of MLEM for dynamic imaging from simulated few-view, multi-pinhole SPECT,” IEEE Trans. Nucl. Sci. 60(1), 115–123 (2013).

[Crossref]

S. R. Arridge and J. C. Schotland, “Optical tomography: forward and inverse problems,” Inverse Probl. 25(12), 123010 (2009).

[Crossref]

Y. Vardi, L. Shepp, and L. Kaufman, “A statistical model for positron emission tomography,” J. Am. Stat. Assoc. 80(389), 8–20 (1985).

[Crossref]

N. C Biswal, A. Aguirre, Y. Xu, S. Zanganeh, Q. Zhu, C. Pavlik, M. B Smith, L. T Kuhn, and K. P Claffey, “Imaging tumor hypoxia by near-infrared fluorescence tomography,” J. Biomed. Opt. 16(6), 066009 (2011).

[Crossref]
[PubMed]

PS. Mohan, T. Tarvainen, M. Schweiger, A. Pulkkinen, and S. R Arridge, “Variable order spherical harmonic expansion scheme for the radiative transport equation using finite elements,” J. Comput. Phys. 230(19), 7364–7383 (2011).

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[Crossref]

N. V. Slavine, M. A. Lewis, E. Richer, and P. P. Antich, “Iterative reconstruction method for light emitting sources based on the diffusion equation,” Med. Phys. 33(1), 61–68 (2006).

[Crossref]
[PubMed]

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[Crossref]
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[Crossref]

G. Strangman, M. A. Franceschini, and D. A. Boas, “Factors affecting the accuracy of near-infrared spectroscopy concentration calculations for focal changes in oxygenation parameters,” Neuroimage 18(4), 865–879 (2003).

[Crossref]
[PubMed]

M. Jiang, T. Zhou, J. Cheng, W. Cong, and G. Wang, “Image reconstruction for bioluminescence tomography from partial measurement,” Opt. Express 15(18), 11095–11116 (2007).

[Crossref]
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[Crossref]

V. Ntziachristos and R. Weissleder, “Experimental three-dimensional fluorescence reconstruction of diffuse media by use of a normalized Born approximation,” Opt. Lett. 26(12), 893–895 (2001).

[Crossref]

L. Zhao, H. Yang, W. Cong, G. Wang, and X. Intes, “Lp regularization for early gate fluorescence molecular tomography,” Opt. Lett. 39(14), 4156–4159 (2014).

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