D. Zhu and C. Li, “Nonconvex regularizations in fluorescence molecular tomography for sparsity enhancement,” Phys. Med. Biol. 59, 2901–2912 (2014).

[Crossref]
[PubMed]

D. Zhu, Y. Zhao, R. Baikejiang, Z. Yuan, and C. Li, “Comparison of regularization methods in fluorescence molecular tomography,” Photonics 1, 95–109 (2014).

[Crossref]

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

[Crossref]
[PubMed]

D. Kim, D. Pal, J.-B. Thibault, and J. Fessler, “Accelerating ordered subsets image reconstruction for x-ray ct using spatially nonuniform optimization transfer,” IEEE Trans. Med. Imaging 32, 1965–1978 (2013).

[Crossref]
[PubMed]

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, 4326–4328 (2012).

[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 (2012).

[Crossref]
[PubMed]

Z. Yu, J.-B. Thibault, C. A. Bouman, K. D. Sauer, and J. Hsieh, “Fast model-based x-ray ct reconstruction using spatially nonhomogeneous icd optimization,” IEEE Trans. Image Process. 20, 161–175 (2011).

[Crossref]

C. Li, Y. Yang, G. S. Mitchell, and S. R. Cherry, “Simultaneous pet and multispectral 3-dimensional fluorescence optical tomography imaging system,” J. Nucl. Med. 52, 1268–1275 (2011).

[Crossref]
[PubMed]

D. Han, J. Tian, C. Qin, B. Zhang, K. Liu, and X. Ma, “A fast reconstruction method for fluorescence molecular tomography based on improved iterated shrinkage,” in “SPIE Medical Imaging,” pp. 79651C (2011).

F. Woolfe, M. Gerdes, M. Bello, X. Tao, and A. Can, “Autofluorescence removal by non-negative matrix factorization,” IEEE Trans. Image Process. 20, 1085–1093 (2011).

[Crossref]

A. S. Montcuquet, L. Hervé, F. Navarro, J. M. Dinten, and J. I. Mars, “In vivo fluorescence spectra unmixing and autofluorescence removal by sparse nonnegative matrix factorization,” IEEE Trans. Bio-Med. Eng. 58, 2554–2565 (2011).

[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, 8630–8646 (2010).

[Crossref]
[PubMed]

Xu Fang, Xu Wei, Jones Mel, Keszthelyi Bettina, Sedat John, Agard David, and Mueller Klaus, “On the efficiency of iterative ordered subset reconstruction algorithms for acceleration on GPUs,” Comput. Meth. Programs Biomed. 98(3), 261–270 (2010).

[Crossref]

J. C. Baritaux, K. Hassler, and M. Unser, “An efficient numerical method for general lp regularization in fluorescence molecular tomography,” IEEE Trans. Med. Imaging 29, 1075–1087 (2010).

[Crossref]
[PubMed]

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

[Crossref]
[PubMed]

A. Beck and M. Teboulle, “A fast iterative shrinkage-thresholding algorithm for linear inverse problems,” SIAM J. Imaging Sci., 2(1), 183–202 (2009).

[Crossref]

F. Tian, G. Alexandrakis, and H. Liu, “Optimization of probe geometry for diffuse optical brain imaging based on measurement density and distribution,” Appl. Opt. 48, 2496–2504 (2009).

[Crossref]
[PubMed]

E. van den Berg and M. P. Friedlander, “Probing the Pareto frontier for basis pursuit solutions,” SIAM J. Sci. Comput. 31(2), 890–912 (2008).

[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, 313–320 (2005).

[Crossref]
[PubMed]

S. R. Cherry, “In vivo molecular and genomic imaging: new challenges for imaging physics,” Phys. Med. Bio. 49, R13 (2004).

[Crossref]

I. Daubechies, M. Defrise, and C. De Mol, “An iterative thresholding algorithm for linear inverse problems with a sparsity constraint,” Comm. Pure Appl. Math., 57, 1413–1457 (2004).

[Crossref]

X. Song, B. W. Pogue, S. Jiang, M. M. Doyley, H. Dehghani, T. D. Tosteson, and K. D. Paulsen, “Automated region detection based on the contrast-to-noise ratio in near-infrared tomography,” Appl. Opt. 43, 1053–1062 (2004).

[Crossref]
[PubMed]

F. Fedele, J. Laible, and M. Eppstein, “Coupled complex adjoint sensitivities for frequency-domain fluorescence tomography: theory and vectorized implementation,” J. Comput. Phys. 187, 597–619 (2003).

[Crossref]

R. Weissleder, C.-H. Tung, U. Mahmood, and A. Bogdanov, “In vivo imaging of tumors with protease-activated near-infrared fluorescent probes,” Nat. Biotechnol. 17, 375–378 (1999).

[Crossref]
[PubMed]

H. Erdogan and J. A. Fessler, “Ordered subsets algorithms for transmission tomography,” Phys. Med. Bio. 44, 2835 (1999).

[Crossref]

J. A. Fessler, E. P. Ficaro, N. H. Clinthorne, and K. Lange, “Grouped-coordinate ascent algorithms for penalized-likelihood transmission image reconstruction,” IEEE Trans. Med. Imaging 16, 166–175 (1997).

[Crossref]
[PubMed]

H. M. Hudson and R. S. Larkin, “Accelerated image reconstruction using ordered subsets of projection data,” IEEE Trans. Med. Imaging 13, 601–609 (1994).

[Crossref]
[PubMed]

A. R. De Pierro, “On the relation between the ISRA and the EM algorithm for positron emission tomography,” IEEE Trans. Med. Imaging 12, 328–333 (1993).

[Crossref]
[PubMed]

M. E. Daube-Witherspoon and G. Muehllehner, “An iterative image space reconstruction algorthm suitable for volume ect,” IEEE Trans. Med. Imaging 5, 61–66 (1986).

[Crossref]
[PubMed]

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

[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, 1459 (2012).

[Crossref]
[PubMed]

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

[Crossref]
[PubMed]

S. R. Arridge and M. Schweiger, “Inverse methods for optical tomography,” in Information Processing in Medical Imaging (Springer, 1993), pp. 259–277.

[Crossref]

D. Zhu, Y. Zhao, R. Baikejiang, Z. Yuan, and C. Li, “Comparison of regularization methods in fluorescence molecular tomography,” Photonics 1, 95–109 (2014).

[Crossref]

J. C. Baritaux, K. Hassler, and M. Unser, “An efficient numerical method for general lp regularization in fluorescence molecular tomography,” IEEE Trans. Med. Imaging 29, 1075–1087 (2010).

[Crossref]
[PubMed]

A. Beck and M. Teboulle, “A fast iterative shrinkage-thresholding algorithm for linear inverse problems,” SIAM J. Imaging Sci., 2(1), 183–202 (2009).

[Crossref]

F. Woolfe, M. Gerdes, M. Bello, X. Tao, and A. Can, “Autofluorescence removal by non-negative matrix factorization,” IEEE Trans. Image Process. 20, 1085–1093 (2011).

[Crossref]

Xu Fang, Xu Wei, Jones Mel, Keszthelyi Bettina, Sedat John, Agard David, and Mueller Klaus, “On the efficiency of iterative ordered subset reconstruction algorithms for acceleration on GPUs,” Comput. Meth. Programs Biomed. 98(3), 261–270 (2010).

[Crossref]

R. Weissleder, C.-H. Tung, U. Mahmood, and A. Bogdanov, “In vivo imaging of tumors with protease-activated near-infrared fluorescent probes,” Nat. Biotechnol. 17, 375–378 (1999).

[Crossref]
[PubMed]

Z. Yu, J.-B. Thibault, C. A. Bouman, K. D. Sauer, and J. Hsieh, “Fast model-based x-ray ct reconstruction using spatially nonhomogeneous icd optimization,” IEEE Trans. Image Process. 20, 161–175 (2011).

[Crossref]

F. Woolfe, M. Gerdes, M. Bello, X. Tao, and A. Can, “Autofluorescence removal by non-negative matrix factorization,” IEEE Trans. Image Process. 20, 1085–1093 (2011).

[Crossref]

C. Chen, F. Tian, H. Liu, and J. Huang, “Diffuse optical tomography enhanced by clustered sparsity for functional brain imaging,” IEEE Trans. Med. Imaging. doi:

[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, 1459 (2012).

[Crossref]
[PubMed]

C. Li, Y. Yang, G. S. Mitchell, and S. R. Cherry, “Simultaneous pet and multispectral 3-dimensional fluorescence optical tomography imaging system,” J. Nucl. Med. 52, 1268–1275 (2011).

[Crossref]
[PubMed]

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

[Crossref]
[PubMed]

S. R. Cherry, “In vivo molecular and genomic imaging: new challenges for imaging physics,” Phys. Med. Bio. 49, R13 (2004).

[Crossref]

J. A. Fessler, E. P. Ficaro, N. H. Clinthorne, and K. Lange, “Grouped-coordinate ascent algorithms for penalized-likelihood transmission image reconstruction,” IEEE Trans. Med. Imaging 16, 166–175 (1997).

[Crossref]
[PubMed]

I. Daubechies, M. Defrise, and C. De Mol, “An iterative thresholding algorithm for linear inverse problems with a sparsity constraint,” Comm. Pure Appl. Math., 57, 1413–1457 (2004).

[Crossref]

M. E. Daube-Witherspoon and G. Muehllehner, “An iterative image space reconstruction algorthm suitable for volume ect,” IEEE Trans. Med. Imaging 5, 61–66 (1986).

[Crossref]
[PubMed]

Xu Fang, Xu Wei, Jones Mel, Keszthelyi Bettina, Sedat John, Agard David, and Mueller Klaus, “On the efficiency of iterative ordered subset reconstruction algorithms for acceleration on GPUs,” Comput. Meth. Programs Biomed. 98(3), 261–270 (2010).

[Crossref]

I. Daubechies, M. Defrise, and C. De Mol, “An iterative thresholding algorithm for linear inverse problems with a sparsity constraint,” Comm. Pure Appl. Math., 57, 1413–1457 (2004).

[Crossref]

A. R. De Pierro, “On the relation between the ISRA and the EM algorithm for positron emission tomography,” IEEE Trans. Med. Imaging 12, 328–333 (1993).

[Crossref]
[PubMed]

I. Daubechies, M. Defrise, and C. De Mol, “An iterative thresholding algorithm for linear inverse problems with a sparsity constraint,” Comm. Pure Appl. Math., 57, 1413–1457 (2004).

[Crossref]

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

[Crossref]

A. S. Montcuquet, L. Hervé, F. Navarro, J. M. Dinten, and J. I. Mars, “In vivo fluorescence spectra unmixing and autofluorescence removal by sparse nonnegative matrix factorization,” IEEE Trans. Bio-Med. Eng. 58, 2554–2565 (2011).

[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, 1459 (2012).

[Crossref]
[PubMed]

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

[Crossref]
[PubMed]

F. Fedele, J. Laible, and M. Eppstein, “Coupled complex adjoint sensitivities for frequency-domain fluorescence tomography: theory and vectorized implementation,” J. Comput. Phys. 187, 597–619 (2003).

[Crossref]

H. Erdogan and J. A. Fessler, “Ordered subsets algorithms for transmission tomography,” Phys. Med. Bio. 44, 2835 (1999).

[Crossref]

Xu Fang, Xu Wei, Jones Mel, Keszthelyi Bettina, Sedat John, Agard David, and Mueller Klaus, “On the efficiency of iterative ordered subset reconstruction algorithms for acceleration on GPUs,” Comput. Meth. Programs Biomed. 98(3), 261–270 (2010).

[Crossref]

F. Fedele, J. Laible, and M. Eppstein, “Coupled complex adjoint sensitivities for frequency-domain fluorescence tomography: theory and vectorized implementation,” J. Comput. Phys. 187, 597–619 (2003).

[Crossref]

D. Kim, D. Pal, J.-B. Thibault, and J. Fessler, “Accelerating ordered subsets image reconstruction for x-ray ct using spatially nonuniform optimization transfer,” IEEE Trans. Med. Imaging 32, 1965–1978 (2013).

[Crossref]
[PubMed]

H. Erdogan and J. A. Fessler, “Ordered subsets algorithms for transmission tomography,” Phys. Med. Bio. 44, 2835 (1999).

[Crossref]

J. A. Fessler, E. P. Ficaro, N. H. Clinthorne, and K. Lange, “Grouped-coordinate ascent algorithms for penalized-likelihood transmission image reconstruction,” IEEE Trans. Med. Imaging 16, 166–175 (1997).

[Crossref]
[PubMed]

J. A. Fessler, E. P. Ficaro, N. H. Clinthorne, and K. Lange, “Grouped-coordinate ascent algorithms for penalized-likelihood transmission image reconstruction,” IEEE Trans. Med. Imaging 16, 166–175 (1997).

[Crossref]
[PubMed]

E. van den Berg and M. P. Friedlander, “Probing the Pareto frontier for basis pursuit solutions,” SIAM J. Sci. Comput. 31(2), 890–912 (2008).

[Crossref]

F. Woolfe, M. Gerdes, M. Bello, X. Tao, and A. Can, “Autofluorescence removal by non-negative matrix factorization,” IEEE Trans. Image Process. 20, 1085–1093 (2011).

[Crossref]

D. Han, J. Tian, C. Qin, B. Zhang, K. Liu, and X. Ma, “A fast reconstruction method for fluorescence molecular tomography based on improved iterated shrinkage,” in “SPIE Medical Imaging,” pp. 79651C (2011).

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, 8630–8646 (2010).

[Crossref]
[PubMed]

J. C. Baritaux, K. Hassler, and M. Unser, “An efficient numerical method for general lp regularization in fluorescence molecular tomography,” IEEE Trans. Med. Imaging 29, 1075–1087 (2010).

[Crossref]
[PubMed]

A. S. Montcuquet, L. Hervé, F. Navarro, J. M. Dinten, and J. I. Mars, “In vivo fluorescence spectra unmixing and autofluorescence removal by sparse nonnegative matrix factorization,” IEEE Trans. Bio-Med. Eng. 58, 2554–2565 (2011).

[Crossref]

Z. Yu, J.-B. Thibault, C. A. Bouman, K. D. Sauer, and J. Hsieh, “Fast model-based x-ray ct reconstruction using spatially nonhomogeneous icd optimization,” IEEE Trans. Image Process. 20, 161–175 (2011).

[Crossref]

C. Chen, F. Tian, H. Liu, and J. Huang, “Diffuse optical tomography enhanced by clustered sparsity for functional brain imaging,” IEEE Trans. Med. Imaging. doi:

[Crossref]

H. M. Hudson and R. S. Larkin, “Accelerated image reconstruction using ordered subsets of projection data,” IEEE Trans. Med. Imaging 13, 601–609 (1994).

[Crossref]
[PubMed]

Xu Fang, Xu Wei, Jones Mel, Keszthelyi Bettina, Sedat John, Agard David, and Mueller Klaus, “On the efficiency of iterative ordered subset reconstruction algorithms for acceleration on GPUs,” Comput. Meth. Programs Biomed. 98(3), 261–270 (2010).

[Crossref]

D. Kim, D. Pal, J.-B. Thibault, and J. Fessler, “Accelerating ordered subsets image reconstruction for x-ray ct using spatially nonuniform optimization transfer,” IEEE Trans. Med. Imaging 32, 1965–1978 (2013).

[Crossref]
[PubMed]

Xu Fang, Xu Wei, Jones Mel, Keszthelyi Bettina, Sedat John, Agard David, and Mueller Klaus, “On the efficiency of iterative ordered subset reconstruction algorithms for acceleration on GPUs,” Comput. Meth. Programs Biomed. 98(3), 261–270 (2010).

[Crossref]

F. Fedele, J. Laible, and M. Eppstein, “Coupled complex adjoint sensitivities for frequency-domain fluorescence tomography: theory and vectorized implementation,” J. Comput. Phys. 187, 597–619 (2003).

[Crossref]

J. A. Fessler, E. P. Ficaro, N. H. Clinthorne, and K. Lange, “Grouped-coordinate ascent algorithms for penalized-likelihood transmission image reconstruction,” IEEE Trans. Med. Imaging 16, 166–175 (1997).

[Crossref]
[PubMed]

K. Lange, “The MM algorithm,” in Optimization (Springer, 2013), pp. 185–219.

[Crossref]

H. M. Hudson and R. S. Larkin, “Accelerated image reconstruction using ordered subsets of projection data,” IEEE Trans. Med. Imaging 13, 601–609 (1994).

[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 (2012).

[Crossref]
[PubMed]

D. D. Lee and H. S. Seung, “Algorithms for non-negative matrix factorization,” in Advances in Neural Information Processing Systems (2000), pp. 556–562.

D. Zhu and C. Li, “Nonconvex regularizations in fluorescence molecular tomography for sparsity enhancement,” Phys. Med. Biol. 59, 2901–2912 (2014).

[Crossref]
[PubMed]

D. Zhu, Y. Zhao, R. Baikejiang, Z. Yuan, and C. Li, “Comparison of regularization methods in fluorescence molecular tomography,” Photonics 1, 95–109 (2014).

[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, 1459 (2012).

[Crossref]
[PubMed]

C. Li, Y. Yang, G. S. Mitchell, and S. R. Cherry, “Simultaneous pet and multispectral 3-dimensional fluorescence optical tomography imaging system,” J. Nucl. Med. 52, 1268–1275 (2011).

[Crossref]
[PubMed]

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

[Crossref]
[PubMed]

F. Tian, G. Alexandrakis, and H. Liu, “Optimization of probe geometry for diffuse optical brain imaging based on measurement density and distribution,” Appl. Opt. 48, 2496–2504 (2009).

[Crossref]
[PubMed]

C. Chen, F. Tian, H. Liu, and J. Huang, “Diffuse optical tomography enhanced by clustered sparsity for functional brain imaging,” IEEE Trans. Med. Imaging. doi:

[Crossref]

D. Han, J. Tian, C. Qin, B. Zhang, K. Liu, and X. Ma, “A fast reconstruction method for fluorescence molecular tomography based on improved iterated shrinkage,” in “SPIE Medical Imaging,” pp. 79651C (2011).

D. Han, J. Tian, C. Qin, B. Zhang, K. Liu, and X. Ma, “A fast reconstruction method for fluorescence molecular tomography based on improved iterated shrinkage,” in “SPIE Medical Imaging,” pp. 79651C (2011).

R. Weissleder, C.-H. Tung, U. Mahmood, and A. Bogdanov, “In vivo imaging of tumors with protease-activated near-infrared fluorescent probes,” Nat. Biotechnol. 17, 375–378 (1999).

[Crossref]
[PubMed]

A. S. Montcuquet, L. Hervé, F. Navarro, J. M. Dinten, and J. I. Mars, “In vivo fluorescence spectra unmixing and autofluorescence removal by sparse nonnegative matrix factorization,” IEEE Trans. Bio-Med. Eng. 58, 2554–2565 (2011).

[Crossref]

Xu Fang, Xu Wei, Jones Mel, Keszthelyi Bettina, Sedat John, Agard David, and Mueller Klaus, “On the efficiency of iterative ordered subset reconstruction algorithms for acceleration on GPUs,” Comput. Meth. Programs Biomed. 98(3), 261–270 (2010).

[Crossref]

C. Li, Y. Yang, G. S. Mitchell, and S. R. Cherry, “Simultaneous pet and multispectral 3-dimensional fluorescence optical tomography imaging system,” J. Nucl. Med. 52, 1268–1275 (2011).

[Crossref]
[PubMed]

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

[Crossref]
[PubMed]

A. S. Montcuquet, L. Hervé, F. Navarro, J. M. Dinten, and J. I. Mars, “In vivo fluorescence spectra unmixing and autofluorescence removal by sparse nonnegative matrix factorization,” IEEE Trans. Bio-Med. Eng. 58, 2554–2565 (2011).

[Crossref]

M. E. Daube-Witherspoon and G. Muehllehner, “An iterative image space reconstruction algorthm suitable for volume ect,” IEEE Trans. Med. Imaging 5, 61–66 (1986).

[Crossref]
[PubMed]

A. S. Montcuquet, L. Hervé, F. Navarro, J. M. Dinten, and J. I. Mars, “In vivo fluorescence spectra unmixing and autofluorescence removal by sparse nonnegative matrix factorization,” IEEE Trans. Bio-Med. Eng. 58, 2554–2565 (2011).

[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, 4326–4328 (2012).

[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, 313–320 (2005).

[Crossref]
[PubMed]

D. Kim, D. Pal, J.-B. Thibault, and J. Fessler, “Accelerating ordered subsets image reconstruction for x-ray ct using spatially nonuniform optimization transfer,” IEEE Trans. Med. Imaging 32, 1965–1978 (2013).

[Crossref]
[PubMed]

D. Han, J. Tian, C. Qin, B. Zhang, K. Liu, and X. Ma, “A fast reconstruction method for fluorescence molecular tomography based on improved iterated shrinkage,” in “SPIE Medical Imaging,” pp. 79651C (2011).

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, 8630–8646 (2010).

[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, 313–320 (2005).

[Crossref]
[PubMed]

Z. Yu, J.-B. Thibault, C. A. Bouman, K. D. Sauer, and J. Hsieh, “Fast model-based x-ray ct reconstruction using spatially nonhomogeneous icd optimization,” IEEE Trans. Image Process. 20, 161–175 (2011).

[Crossref]

S. R. Arridge and M. Schweiger, “Inverse methods for optical tomography,” in Information Processing in Medical Imaging (Springer, 1993), pp. 259–277.

[Crossref]

D. D. Lee and H. S. Seung, “Algorithms for non-negative matrix factorization,” in Advances in Neural Information Processing Systems (2000), pp. 556–562.

F. Woolfe, M. Gerdes, M. Bello, X. Tao, and A. Can, “Autofluorescence removal by non-negative matrix factorization,” IEEE Trans. Image Process. 20, 1085–1093 (2011).

[Crossref]

A. Beck and M. Teboulle, “A fast iterative shrinkage-thresholding algorithm for linear inverse problems,” SIAM J. Imaging Sci., 2(1), 183–202 (2009).

[Crossref]

D. Kim, D. Pal, J.-B. Thibault, and J. Fessler, “Accelerating ordered subsets image reconstruction for x-ray ct using spatially nonuniform optimization transfer,” IEEE Trans. Med. Imaging 32, 1965–1978 (2013).

[Crossref]
[PubMed]

Z. Yu, J.-B. Thibault, C. A. Bouman, K. D. Sauer, and J. Hsieh, “Fast model-based x-ray ct reconstruction using spatially nonhomogeneous icd optimization,” IEEE Trans. Image Process. 20, 161–175 (2011).

[Crossref]

F. Tian, G. Alexandrakis, and H. Liu, “Optimization of probe geometry for diffuse optical brain imaging based on measurement density and distribution,” Appl. Opt. 48, 2496–2504 (2009).

[Crossref]
[PubMed]

C. Chen, F. Tian, H. Liu, and J. Huang, “Diffuse optical tomography enhanced by clustered sparsity for functional brain imaging,” IEEE Trans. Med. Imaging. doi:

[Crossref]

D. Han, J. Tian, C. Qin, B. Zhang, K. Liu, and X. Ma, “A fast reconstruction method for fluorescence molecular tomography based on improved iterated shrinkage,” in “SPIE Medical Imaging,” pp. 79651C (2011).

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, 8630–8646 (2010).

[Crossref]
[PubMed]

R. Weissleder, C.-H. Tung, U. Mahmood, and A. Bogdanov, “In vivo imaging of tumors with protease-activated near-infrared fluorescent probes,” Nat. Biotechnol. 17, 375–378 (1999).

[Crossref]
[PubMed]

J. C. Baritaux, K. Hassler, and M. Unser, “An efficient numerical method for general lp regularization in fluorescence molecular tomography,” IEEE Trans. Med. Imaging 29, 1075–1087 (2010).

[Crossref]
[PubMed]

E. van den Berg and M. P. Friedlander, “Probing the Pareto frontier for basis pursuit solutions,” SIAM J. Sci. Comput. 31(2), 890–912 (2008).

[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, 313–320 (2005).

[Crossref]
[PubMed]

Xu Fang, Xu Wei, Jones Mel, Keszthelyi Bettina, Sedat John, Agard David, and Mueller Klaus, “On the efficiency of iterative ordered subset reconstruction algorithms for acceleration on GPUs,” Comput. Meth. Programs Biomed. 98(3), 261–270 (2010).

[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, 313–320 (2005).

[Crossref]
[PubMed]

R. Weissleder, C.-H. Tung, U. Mahmood, and A. Bogdanov, “In vivo imaging of tumors with protease-activated near-infrared fluorescent probes,” Nat. Biotechnol. 17, 375–378 (1999).

[Crossref]
[PubMed]

F. Woolfe, M. Gerdes, M. Bello, X. Tao, and A. Can, “Autofluorescence removal by non-negative matrix factorization,” IEEE Trans. Image Process. 20, 1085–1093 (2011).

[Crossref]

C. Li, Y. Yang, G. S. Mitchell, and S. R. Cherry, “Simultaneous pet and multispectral 3-dimensional fluorescence optical tomography imaging system,” J. Nucl. Med. 52, 1268–1275 (2011).

[Crossref]
[PubMed]

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