S. Tong, A. M. Alessio, P. E. Kinahan, H. Liu, and P. Shi, “A robust state-space kinetics-guided framework for dynamic PET image reconstruction,” Phys. Med. Biol. 56, 2481–2498 (2011).

[CrossRef]

F. O’Sullivan, J. Kirrane, M. Muzi, J. O’Sullivan, A. Spence, D. Mankoff, and K. Krohn, “Kinetic quantitation of cerebral PET-FDG studies without concurrent blood sampling: statistical recovery of the arterial input function,” IEEE Trans. Med. Imag. 29, 610–624 (2010).

[CrossRef]

H. Wieczorek, “The image quality of FBP and MLEM reconstruction,” Phys. Med. Biol. 55, 3161–3176 (2010).

[CrossRef]

G. Wang and J. Qi, “Analysis of penalized likelihood image reconstruction for dynamic PET quantification,” IEEE Trans. Med. Imag. 28, 608–620 (2009).

[CrossRef]

R. Maroy, R. Boisgard, C. Comtat, V. Frouin, P. Cathier, E. Duchesnay, F. Dolle, P. Nielsen, R. Trebossen, and B. Tavitian, “Segmentation of rodent whole-body dynamic PET images: an unsupervised method based on voxel dynamics,” IEEE Trans. Med. Imag. 27, 342–354 (2008).

[CrossRef]

R. M. Lewitt and S. Matej, “Overview of methods for image reconstruction from projections in emission computed tomography,” Proc. IEEE 91, 1588–1611 (2003).

[CrossRef]

F. Kemp, “An introduction to sequential Monte Carlo methods,” J. Roy. Stat. Soc. 52, 694–695 (2003).

[CrossRef]

M. Arulampalam, S. Maskell, N. Gordon, and T. Clapp, “A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking,” IEEE Trans. Signal Process. 50, 174–188 (2002).

[CrossRef]

K.R. Muzic and S. Cornelius, “COMKAT: compartment model kinetic analysis tool,” J. Nucl. Med. 42, 636–645 (2001).

J. Nuyts, C. Michel, and P. Dupont, “Maximum-likelihood expectation-maximization reconstruction of sinograms with arbitrary noise distribution using NEC-transformations,” IEEE Trans. Med. Imag. 20, 365–375 (2001).

[CrossRef]

R. Leahy and J. Qi “Statistical approaches in quantitative positron emission tomography,” Stat. Comput. 10, 147–165 (2000).

[CrossRef]

V.V. Selivanov, Y. Picard, J. Cadorette, S. Rodrigue, and R. Lecomte, “Detector response models for statistical iterative image reconstruction in high resolution PET,” IEEE Trans. Nucl. Sci. 47, 1168–1175 (2000).

[CrossRef]

C. Comtat, P. Kinahan, M. Defrise, C. Michel, and D. Townsend, “Fast reconstruction of 3D PET data with accurate statistical modeling,” IEEE Trans. Nucl. Sci. 45, 1083–1089 (1998).

[CrossRef]

J. Ollinger and J. Fessler, “Positron-emission tomography,” IEEE Signal Process. Mag. 14 (1), 43–55 (1997).

[CrossRef]

A. F. M. Smith and A. E. Gelfand“ Bayesian statistics without tears: a sampling–resampling perspective,” Amer. Stat. 46, 84–88 (1992).

[CrossRef]

L. A. Shepp, and Y. Vardi, “Maximum likelihood reconstruction for emission tomography,” IEEE Trans. Med. Imag. 1, 113–122 (1982).

[CrossRef]

S. Tong, A. M. Alessio, P. E. Kinahan, H. Liu, and P. Shi, “A robust state-space kinetics-guided framework for dynamic PET image reconstruction,” Phys. Med. Biol. 56, 2481–2498 (2011).

[CrossRef]

M. Arulampalam, S. Maskell, N. Gordon, and T. Clapp, “A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking,” IEEE Trans. Signal Process. 50, 174–188 (2002).

[CrossRef]

R. Gunn, S. Gunn, F. Turkheimer, J. Aston, and V. Cunningham, “Tracer kinetic modeling via basis pursuit,” in Brain Imaging Using PET, M. Senda, ed. (Academic, 2002), pp. 115–121.

R. Maroy, R. Boisgard, C. Comtat, V. Frouin, P. Cathier, E. Duchesnay, F. Dolle, P. Nielsen, R. Trebossen, and B. Tavitian, “Segmentation of rodent whole-body dynamic PET images: an unsupervised method based on voxel dynamics,” IEEE Trans. Med. Imag. 27, 342–354 (2008).

[CrossRef]

V.V. Selivanov, Y. Picard, J. Cadorette, S. Rodrigue, and R. Lecomte, “Detector response models for statistical iterative image reconstruction in high resolution PET,” IEEE Trans. Nucl. Sci. 47, 1168–1175 (2000).

[CrossRef]

E. Carson and C. Cobelli, Modelling Methodology for Physiology and Medicine (Academic, 2001).

R. Maroy, R. Boisgard, C. Comtat, V. Frouin, P. Cathier, E. Duchesnay, F. Dolle, P. Nielsen, R. Trebossen, and B. Tavitian, “Segmentation of rodent whole-body dynamic PET images: an unsupervised method based on voxel dynamics,” IEEE Trans. Med. Imag. 27, 342–354 (2008).

[CrossRef]

M. Arulampalam, S. Maskell, N. Gordon, and T. Clapp, “A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking,” IEEE Trans. Signal Process. 50, 174–188 (2002).

[CrossRef]

E. Carson and C. Cobelli, Modelling Methodology for Physiology and Medicine (Academic, 2001).

R. Maroy, R. Boisgard, C. Comtat, V. Frouin, P. Cathier, E. Duchesnay, F. Dolle, P. Nielsen, R. Trebossen, and B. Tavitian, “Segmentation of rodent whole-body dynamic PET images: an unsupervised method based on voxel dynamics,” IEEE Trans. Med. Imag. 27, 342–354 (2008).

[CrossRef]

C. Comtat, P. Kinahan, M. Defrise, C. Michel, and D. Townsend, “Fast reconstruction of 3D PET data with accurate statistical modeling,” IEEE Trans. Nucl. Sci. 45, 1083–1089 (1998).

[CrossRef]

K.R. Muzic and S. Cornelius, “COMKAT: compartment model kinetic analysis tool,” J. Nucl. Med. 42, 636–645 (2001).

R. Gunn, S. Gunn, F. Turkheimer, J. Aston, and V. Cunningham, “Tracer kinetic modeling via basis pursuit,” in Brain Imaging Using PET, M. Senda, ed. (Academic, 2002), pp. 115–121.

C. Comtat, P. Kinahan, M. Defrise, C. Michel, and D. Townsend, “Fast reconstruction of 3D PET data with accurate statistical modeling,” IEEE Trans. Nucl. Sci. 45, 1083–1089 (1998).

[CrossRef]

R. Maroy, R. Boisgard, C. Comtat, V. Frouin, P. Cathier, E. Duchesnay, F. Dolle, P. Nielsen, R. Trebossen, and B. Tavitian, “Segmentation of rodent whole-body dynamic PET images: an unsupervised method based on voxel dynamics,” IEEE Trans. Med. Imag. 27, 342–354 (2008).

[CrossRef]

A. Doucet, “On sequential simulation-based methods for Bayesian filtering,” Tech. rep. CUED/F-INFENG/TR. 310 (Cambridge University Department of Engineering, 1998).

R. Maroy, R. Boisgard, C. Comtat, V. Frouin, P. Cathier, E. Duchesnay, F. Dolle, P. Nielsen, R. Trebossen, and B. Tavitian, “Segmentation of rodent whole-body dynamic PET images: an unsupervised method based on voxel dynamics,” IEEE Trans. Med. Imag. 27, 342–354 (2008).

[CrossRef]

J. Nuyts, C. Michel, and P. Dupont, “Maximum-likelihood expectation-maximization reconstruction of sinograms with arbitrary noise distribution using NEC-transformations,” IEEE Trans. Med. Imag. 20, 365–375 (2001).

[CrossRef]

J. Ollinger and J. Fessler, “Positron-emission tomography,” IEEE Signal Process. Mag. 14 (1), 43–55 (1997).

[CrossRef]

R. Maroy, R. Boisgard, C. Comtat, V. Frouin, P. Cathier, E. Duchesnay, F. Dolle, P. Nielsen, R. Trebossen, and B. Tavitian, “Segmentation of rodent whole-body dynamic PET images: an unsupervised method based on voxel dynamics,” IEEE Trans. Med. Imag. 27, 342–354 (2008).

[CrossRef]

A. F. M. Smith and A. E. Gelfand“ Bayesian statistics without tears: a sampling–resampling perspective,” Amer. Stat. 46, 84–88 (1992).

[CrossRef]

M. Arulampalam, S. Maskell, N. Gordon, and T. Clapp, “A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking,” IEEE Trans. Signal Process. 50, 174–188 (2002).

[CrossRef]

R. Gunn, S. Gunn, F. Turkheimer, J. Aston, and V. Cunningham, “Tracer kinetic modeling via basis pursuit,” in Brain Imaging Using PET, M. Senda, ed. (Academic, 2002), pp. 115–121.

R. Gunn, S. Gunn, F. Turkheimer, J. Aston, and V. Cunningham, “Tracer kinetic modeling via basis pursuit,” in Brain Imaging Using PET, M. Senda, ed. (Academic, 2002), pp. 115–121.

F. Kemp, “An introduction to sequential Monte Carlo methods,” J. Roy. Stat. Soc. 52, 694–695 (2003).

[CrossRef]

C. Comtat, P. Kinahan, M. Defrise, C. Michel, and D. Townsend, “Fast reconstruction of 3D PET data with accurate statistical modeling,” IEEE Trans. Nucl. Sci. 45, 1083–1089 (1998).

[CrossRef]

S. Tong, A. M. Alessio, P. E. Kinahan, H. Liu, and P. Shi, “A robust state-space kinetics-guided framework for dynamic PET image reconstruction,” Phys. Med. Biol. 56, 2481–2498 (2011).

[CrossRef]

F. O’Sullivan, J. Kirrane, M. Muzi, J. O’Sullivan, A. Spence, D. Mankoff, and K. Krohn, “Kinetic quantitation of cerebral PET-FDG studies without concurrent blood sampling: statistical recovery of the arterial input function,” IEEE Trans. Med. Imag. 29, 610–624 (2010).

[CrossRef]

F. O’Sullivan, J. Kirrane, M. Muzi, J. O’Sullivan, A. Spence, D. Mankoff, and K. Krohn, “Kinetic quantitation of cerebral PET-FDG studies without concurrent blood sampling: statistical recovery of the arterial input function,” IEEE Trans. Med. Imag. 29, 610–624 (2010).

[CrossRef]

R. Leahy and J. Qi “Statistical approaches in quantitative positron emission tomography,” Stat. Comput. 10, 147–165 (2000).

[CrossRef]

V.V. Selivanov, Y. Picard, J. Cadorette, S. Rodrigue, and R. Lecomte, “Detector response models for statistical iterative image reconstruction in high resolution PET,” IEEE Trans. Nucl. Sci. 47, 1168–1175 (2000).

[CrossRef]

R. M. Lewitt and S. Matej, “Overview of methods for image reconstruction from projections in emission computed tomography,” Proc. IEEE 91, 1588–1611 (2003).

[CrossRef]

S. Tong, A. M. Alessio, P. E. Kinahan, H. Liu, and P. Shi, “A robust state-space kinetics-guided framework for dynamic PET image reconstruction,” Phys. Med. Biol. 56, 2481–2498 (2011).

[CrossRef]

F. O’Sullivan, J. Kirrane, M. Muzi, J. O’Sullivan, A. Spence, D. Mankoff, and K. Krohn, “Kinetic quantitation of cerebral PET-FDG studies without concurrent blood sampling: statistical recovery of the arterial input function,” IEEE Trans. Med. Imag. 29, 610–624 (2010).

[CrossRef]

R. Maroy, R. Boisgard, C. Comtat, V. Frouin, P. Cathier, E. Duchesnay, F. Dolle, P. Nielsen, R. Trebossen, and B. Tavitian, “Segmentation of rodent whole-body dynamic PET images: an unsupervised method based on voxel dynamics,” IEEE Trans. Med. Imag. 27, 342–354 (2008).

[CrossRef]

M. Arulampalam, S. Maskell, N. Gordon, and T. Clapp, “A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking,” IEEE Trans. Signal Process. 50, 174–188 (2002).

[CrossRef]

R. M. Lewitt and S. Matej, “Overview of methods for image reconstruction from projections in emission computed tomography,” Proc. IEEE 91, 1588–1611 (2003).

[CrossRef]

J. Nuyts, C. Michel, and P. Dupont, “Maximum-likelihood expectation-maximization reconstruction of sinograms with arbitrary noise distribution using NEC-transformations,” IEEE Trans. Med. Imag. 20, 365–375 (2001).

[CrossRef]

C. Comtat, P. Kinahan, M. Defrise, C. Michel, and D. Townsend, “Fast reconstruction of 3D PET data with accurate statistical modeling,” IEEE Trans. Nucl. Sci. 45, 1083–1089 (1998).

[CrossRef]

F. O’Sullivan, J. Kirrane, M. Muzi, J. O’Sullivan, A. Spence, D. Mankoff, and K. Krohn, “Kinetic quantitation of cerebral PET-FDG studies without concurrent blood sampling: statistical recovery of the arterial input function,” IEEE Trans. Med. Imag. 29, 610–624 (2010).

[CrossRef]

K.R. Muzic and S. Cornelius, “COMKAT: compartment model kinetic analysis tool,” J. Nucl. Med. 42, 636–645 (2001).

R. Maroy, R. Boisgard, C. Comtat, V. Frouin, P. Cathier, E. Duchesnay, F. Dolle, P. Nielsen, R. Trebossen, and B. Tavitian, “Segmentation of rodent whole-body dynamic PET images: an unsupervised method based on voxel dynamics,” IEEE Trans. Med. Imag. 27, 342–354 (2008).

[CrossRef]

J. Nuyts, C. Michel, and P. Dupont, “Maximum-likelihood expectation-maximization reconstruction of sinograms with arbitrary noise distribution using NEC-transformations,” IEEE Trans. Med. Imag. 20, 365–375 (2001).

[CrossRef]

F. O’Sullivan, J. Kirrane, M. Muzi, J. O’Sullivan, A. Spence, D. Mankoff, and K. Krohn, “Kinetic quantitation of cerebral PET-FDG studies without concurrent blood sampling: statistical recovery of the arterial input function,” IEEE Trans. Med. Imag. 29, 610–624 (2010).

[CrossRef]

F. O’Sullivan, J. Kirrane, M. Muzi, J. O’Sullivan, A. Spence, D. Mankoff, and K. Krohn, “Kinetic quantitation of cerebral PET-FDG studies without concurrent blood sampling: statistical recovery of the arterial input function,” IEEE Trans. Med. Imag. 29, 610–624 (2010).

[CrossRef]

J. Ollinger and J. Fessler, “Positron-emission tomography,” IEEE Signal Process. Mag. 14 (1), 43–55 (1997).

[CrossRef]

M. Phelps, PET: Molecular Imaging and Its Biological Applications (Springer, 2004).

V.V. Selivanov, Y. Picard, J. Cadorette, S. Rodrigue, and R. Lecomte, “Detector response models for statistical iterative image reconstruction in high resolution PET,” IEEE Trans. Nucl. Sci. 47, 1168–1175 (2000).

[CrossRef]

G. Wang and J. Qi, “Analysis of penalized likelihood image reconstruction for dynamic PET quantification,” IEEE Trans. Med. Imag. 28, 608–620 (2009).

[CrossRef]

R. Leahy and J. Qi “Statistical approaches in quantitative positron emission tomography,” Stat. Comput. 10, 147–165 (2000).

[CrossRef]

V.V. Selivanov, Y. Picard, J. Cadorette, S. Rodrigue, and R. Lecomte, “Detector response models for statistical iterative image reconstruction in high resolution PET,” IEEE Trans. Nucl. Sci. 47, 1168–1175 (2000).

[CrossRef]

V.V. Selivanov, Y. Picard, J. Cadorette, S. Rodrigue, and R. Lecomte, “Detector response models for statistical iterative image reconstruction in high resolution PET,” IEEE Trans. Nucl. Sci. 47, 1168–1175 (2000).

[CrossRef]

L. A. Shepp, and Y. Vardi, “Maximum likelihood reconstruction for emission tomography,” IEEE Trans. Med. Imag. 1, 113–122 (1982).

[CrossRef]

S. Tong, A. M. Alessio, P. E. Kinahan, H. Liu, and P. Shi, “A robust state-space kinetics-guided framework for dynamic PET image reconstruction,” Phys. Med. Biol. 56, 2481–2498 (2011).

[CrossRef]

S. Tong and P. Shi, “Tracer kinetics guided dynamic PET reconstruction,” Information Process in Medical Imaging (2007), pp. 421–433.

A. F. M. Smith and A. E. Gelfand“ Bayesian statistics without tears: a sampling–resampling perspective,” Amer. Stat. 46, 84–88 (1992).

[CrossRef]

F. O’Sullivan, J. Kirrane, M. Muzi, J. O’Sullivan, A. Spence, D. Mankoff, and K. Krohn, “Kinetic quantitation of cerebral PET-FDG studies without concurrent blood sampling: statistical recovery of the arterial input function,” IEEE Trans. Med. Imag. 29, 610–624 (2010).

[CrossRef]

R. Maroy, R. Boisgard, C. Comtat, V. Frouin, P. Cathier, E. Duchesnay, F. Dolle, P. Nielsen, R. Trebossen, and B. Tavitian, “Segmentation of rodent whole-body dynamic PET images: an unsupervised method based on voxel dynamics,” IEEE Trans. Med. Imag. 27, 342–354 (2008).

[CrossRef]

S. Tong, A. M. Alessio, P. E. Kinahan, H. Liu, and P. Shi, “A robust state-space kinetics-guided framework for dynamic PET image reconstruction,” Phys. Med. Biol. 56, 2481–2498 (2011).

[CrossRef]

S. Tong and P. Shi, “Tracer kinetics guided dynamic PET reconstruction,” Information Process in Medical Imaging (2007), pp. 421–433.

C. Comtat, P. Kinahan, M. Defrise, C. Michel, and D. Townsend, “Fast reconstruction of 3D PET data with accurate statistical modeling,” IEEE Trans. Nucl. Sci. 45, 1083–1089 (1998).

[CrossRef]

R. Maroy, R. Boisgard, C. Comtat, V. Frouin, P. Cathier, E. Duchesnay, F. Dolle, P. Nielsen, R. Trebossen, and B. Tavitian, “Segmentation of rodent whole-body dynamic PET images: an unsupervised method based on voxel dynamics,” IEEE Trans. Med. Imag. 27, 342–354 (2008).

[CrossRef]

R. Gunn, S. Gunn, F. Turkheimer, J. Aston, and V. Cunningham, “Tracer kinetic modeling via basis pursuit,” in Brain Imaging Using PET, M. Senda, ed. (Academic, 2002), pp. 115–121.

L. A. Shepp, and Y. Vardi, “Maximum likelihood reconstruction for emission tomography,” IEEE Trans. Med. Imag. 1, 113–122 (1982).

[CrossRef]

G. Wang and J. Qi, “Analysis of penalized likelihood image reconstruction for dynamic PET quantification,” IEEE Trans. Med. Imag. 28, 608–620 (2009).

[CrossRef]

H. Wieczorek, “The image quality of FBP and MLEM reconstruction,” Phys. Med. Biol. 55, 3161–3176 (2010).

[CrossRef]

A. F. M. Smith and A. E. Gelfand“ Bayesian statistics without tears: a sampling–resampling perspective,” Amer. Stat. 46, 84–88 (1992).

[CrossRef]

J. Ollinger and J. Fessler, “Positron-emission tomography,” IEEE Signal Process. Mag. 14 (1), 43–55 (1997).

[CrossRef]

L. A. Shepp, and Y. Vardi, “Maximum likelihood reconstruction for emission tomography,” IEEE Trans. Med. Imag. 1, 113–122 (1982).

[CrossRef]

J. Nuyts, C. Michel, and P. Dupont, “Maximum-likelihood expectation-maximization reconstruction of sinograms with arbitrary noise distribution using NEC-transformations,” IEEE Trans. Med. Imag. 20, 365–375 (2001).

[CrossRef]

G. Wang and J. Qi, “Analysis of penalized likelihood image reconstruction for dynamic PET quantification,” IEEE Trans. Med. Imag. 28, 608–620 (2009).

[CrossRef]

R. Maroy, R. Boisgard, C. Comtat, V. Frouin, P. Cathier, E. Duchesnay, F. Dolle, P. Nielsen, R. Trebossen, and B. Tavitian, “Segmentation of rodent whole-body dynamic PET images: an unsupervised method based on voxel dynamics,” IEEE Trans. Med. Imag. 27, 342–354 (2008).

[CrossRef]

F. O’Sullivan, J. Kirrane, M. Muzi, J. O’Sullivan, A. Spence, D. Mankoff, and K. Krohn, “Kinetic quantitation of cerebral PET-FDG studies without concurrent blood sampling: statistical recovery of the arterial input function,” IEEE Trans. Med. Imag. 29, 610–624 (2010).

[CrossRef]

V.V. Selivanov, Y. Picard, J. Cadorette, S. Rodrigue, and R. Lecomte, “Detector response models for statistical iterative image reconstruction in high resolution PET,” IEEE Trans. Nucl. Sci. 47, 1168–1175 (2000).

[CrossRef]

C. Comtat, P. Kinahan, M. Defrise, C. Michel, and D. Townsend, “Fast reconstruction of 3D PET data with accurate statistical modeling,” IEEE Trans. Nucl. Sci. 45, 1083–1089 (1998).

[CrossRef]

M. Arulampalam, S. Maskell, N. Gordon, and T. Clapp, “A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking,” IEEE Trans. Signal Process. 50, 174–188 (2002).

[CrossRef]

K.R. Muzic and S. Cornelius, “COMKAT: compartment model kinetic analysis tool,” J. Nucl. Med. 42, 636–645 (2001).

F. Kemp, “An introduction to sequential Monte Carlo methods,” J. Roy. Stat. Soc. 52, 694–695 (2003).

[CrossRef]

S. Tong, A. M. Alessio, P. E. Kinahan, H. Liu, and P. Shi, “A robust state-space kinetics-guided framework for dynamic PET image reconstruction,” Phys. Med. Biol. 56, 2481–2498 (2011).

[CrossRef]

H. Wieczorek, “The image quality of FBP and MLEM reconstruction,” Phys. Med. Biol. 55, 3161–3176 (2010).

[CrossRef]

R. M. Lewitt and S. Matej, “Overview of methods for image reconstruction from projections in emission computed tomography,” Proc. IEEE 91, 1588–1611 (2003).

[CrossRef]

R. Leahy and J. Qi “Statistical approaches in quantitative positron emission tomography,” Stat. Comput. 10, 147–165 (2000).

[CrossRef]

E. Carson and C. Cobelli, Modelling Methodology for Physiology and Medicine (Academic, 2001).

S. Tong and P. Shi, “Tracer kinetics guided dynamic PET reconstruction,” Information Process in Medical Imaging (2007), pp. 421–433.

M. Phelps, PET: Molecular Imaging and Its Biological Applications (Springer, 2004).

R. Gunn, S. Gunn, F. Turkheimer, J. Aston, and V. Cunningham, “Tracer kinetic modeling via basis pursuit,” in Brain Imaging Using PET, M. Senda, ed. (Academic, 2002), pp. 115–121.

A. Doucet, “On sequential simulation-based methods for Bayesian filtering,” Tech. rep. CUED/F-INFENG/TR. 310 (Cambridge University Department of Engineering, 1998).