C. Caiafa, A. Proto, and E. Kuruoglu, “Long correlation Gaussian random fields: Parameter estimation and noise reduction,” Digital Signal Processing 17, 819–835 (2007).
[Crossref]
R. E. Greenblatt, A. Ossadtchi, and M. E. Pflieger, “Local linear estimators for the bioelectromagnetic inverse problem,” IEEE Trans. Signal Process. 53(9), 3403–3412 (2005).
[Crossref]
S. P. Mµller, C. K. Abbey, F. J. Rybicki, S. C. Moore, and M. F. Kijewski, “Measures of performance in nonlinear estimation tasks: prediction of estimation performance at low signal-to-noise ratio,” Phys. Med. Biol. 50, 3697–3715 (2005).
[Crossref]
S. C. Moore, M. F. Kijewski, and G. El Fakhri, “Collimator Optimization for Detection and Quantitation Tasks: Application to Gallium-67 Imaging,” IEEE Trans. Med. Imaging 24(10), 1347–1356 (2005).
[Crossref]
[PubMed]
M. A. Kupinski, E. Clarkson, K. Gross, and J. W. Hoppin, “Optimizing imaging hardware for estimation tasks,” Proc. SPIE 5034, 309–313 (2003).
[Crossref]
M. Kupinski, J.W. Hoppin, E. Clarkson, and H. H. Barrett, “Ideal-observer computation in medical imaging with use of Markov-chain Monte Carlo techniques,” J. Opt. Soc. Am. A 20, 430–438 (2003).
[Crossref]
G. El Fakhri, S. C. Moore, and M. F. Kijewski, “Optimization of Ga-67 imaging for detection and estimation tasks: Dependence of imaging performance on spectral acquisition parameters,” Med. Phys. 29, 1859–1866 (2002).
[Crossref]
[PubMed]
A. B. Hamza, H. Krim, and G. Unal, “Unifying probabilistic and variational estimation,” IEEE Signal Process Mag. 19, 37–47 (2002).
[Crossref]
H. H. Barrett, K. J. Myers, B. Gallas, E. Clarkson, and H. Zhang, “Megalopinakophobia: Its Symptoms and Cures,” Proc. SPIE 4320, 299–307 (2001).
[Crossref]
F. O. Bochud, J.-F. Valley, and F. R. Verdun, “Estimation of the noisy component of anatomical backgrounds,” Med. Phys. 26(7), 1365–1370 (1999).
[Crossref]
[PubMed]
S. P Mµller, M. F. Kijewski, S. C. Moore, and B. L. Holman, “Maximum-likelihood Estimation: A Mathematical Model for Quantitation in Nuclear Medicine,” J. Nucl. Med. 31, 1693–1701 (1989).
S. P. Mµller, C. K. Abbey, F. J. Rybicki, S. C. Moore, and M. F. Kijewski, “Measures of performance in nonlinear estimation tasks: prediction of estimation performance at low signal-to-noise ratio,” Phys. Med. Biol. 50, 3697–3715 (2005).
[Crossref]
H. H. Barrett, K. J. Myers, N. Devaney, and J. C. Dainty, “Objective Assessment of Image Quality: IV. Application to Adaptive Optics,” J. Opt. Soc. Am. A 23(12), 3080–3105 (2006).
[Crossref]
M. Kupinski, J.W. Hoppin, E. Clarkson, and H. H. Barrett, “Ideal-observer computation in medical imaging with use of Markov-chain Monte Carlo techniques,” J. Opt. Soc. Am. A 20, 430–438 (2003).
[Crossref]
H. H. Barrett, K. J. Myers, B. Gallas, E. Clarkson, and H. Zhang, “Megalopinakophobia: Its Symptoms and Cures,” Proc. SPIE 4320, 299–307 (2001).
[Crossref]
J. P. Rolland and H. H. Barrett, “Effect of random background inhomogeneity on observer detection performance,” J. Opt. Soc. Am. A 9, 649–658 (1992).
[Crossref]
[PubMed]
H. H. Barrett, “Objective assessment of image quality: effects of quantum noise and object variability,” J. Opt. Soc. Am. A 7(7), 1266–1278 (1990).
[Crossref]
[PubMed]
H. H. Barrett and K. J. Myers, Foundations of Image Science (Wiley-Interscience, 2004).
F. O. Bochud, J.-F. Valley, and F. R. Verdun, “Estimation of the noisy component of anatomical backgrounds,” Med. Phys. 26(7), 1365–1370 (1999).
[Crossref]
[PubMed]
C. Caiafa, A. Proto, and E. Kuruoglu, “Long correlation Gaussian random fields: Parameter estimation and noise reduction,” Digital Signal Processing 17, 819–835 (2007).
[Crossref]
M. A. Kupinski, E. Clarkson, K. Gross, and J. W. Hoppin, “Optimizing imaging hardware for estimation tasks,” Proc. SPIE 5034, 309–313 (2003).
[Crossref]
M. Kupinski, J.W. Hoppin, E. Clarkson, and H. H. Barrett, “Ideal-observer computation in medical imaging with use of Markov-chain Monte Carlo techniques,” J. Opt. Soc. Am. A 20, 430–438 (2003).
[Crossref]
H. H. Barrett, K. J. Myers, B. Gallas, E. Clarkson, and H. Zhang, “Megalopinakophobia: Its Symptoms and Cures,” Proc. SPIE 4320, 299–307 (2001).
[Crossref]
J. L. Melsa and D. L. Cohn, Decision and Estimation Theory (McGraw-Hill, 1978).
S. C. Moore, M. F. Kijewski, and G. El Fakhri, “Collimator Optimization for Detection and Quantitation Tasks: Application to Gallium-67 Imaging,” IEEE Trans. Med. Imaging 24(10), 1347–1356 (2005).
[Crossref]
[PubMed]
G. El Fakhri, S. C. Moore, and M. F. Kijewski, “Optimization of Ga-67 imaging for detection and estimation tasks: Dependence of imaging performance on spectral acquisition parameters,” Med. Phys. 29, 1859–1866 (2002).
[Crossref]
[PubMed]
Y. C. Eldar, “Comparing between estimation approaches: admissible and dominating linear estimators,” IEEE Trans. Signal Process. 54(5), 1689–1702 (2006).
[Crossref]
H. H. Barrett, K. J. Myers, B. Gallas, E. Clarkson, and H. Zhang, “Megalopinakophobia: Its Symptoms and Cures,” Proc. SPIE 4320, 299–307 (2001).
[Crossref]
R. E. Greenblatt, A. Ossadtchi, and M. E. Pflieger, “Local linear estimators for the bioelectromagnetic inverse problem,” IEEE Trans. Signal Process. 53(9), 3403–3412 (2005).
[Crossref]
M. A. Kupinski, E. Clarkson, K. Gross, and J. W. Hoppin, “Optimizing imaging hardware for estimation tasks,” Proc. SPIE 5034, 309–313 (2003).
[Crossref]
A. B. Hamza, H. Krim, and G. Unal, “Unifying probabilistic and variational estimation,” IEEE Signal Process Mag. 19, 37–47 (2002).
[Crossref]
S. P Mµller, M. F. Kijewski, S. C. Moore, and B. L. Holman, “Maximum-likelihood Estimation: A Mathematical Model for Quantitation in Nuclear Medicine,” J. Nucl. Med. 31, 1693–1701 (1989).
M. A. Kupinski, E. Clarkson, K. Gross, and J. W. Hoppin, “Optimizing imaging hardware for estimation tasks,” Proc. SPIE 5034, 309–313 (2003).
[Crossref]
S. C. Moore, M. F. Kijewski, and G. El Fakhri, “Collimator Optimization for Detection and Quantitation Tasks: Application to Gallium-67 Imaging,” IEEE Trans. Med. Imaging 24(10), 1347–1356 (2005).
[Crossref]
[PubMed]
S. P. Mµller, C. K. Abbey, F. J. Rybicki, S. C. Moore, and M. F. Kijewski, “Measures of performance in nonlinear estimation tasks: prediction of estimation performance at low signal-to-noise ratio,” Phys. Med. Biol. 50, 3697–3715 (2005).
[Crossref]
G. El Fakhri, S. C. Moore, and M. F. Kijewski, “Optimization of Ga-67 imaging for detection and estimation tasks: Dependence of imaging performance on spectral acquisition parameters,” Med. Phys. 29, 1859–1866 (2002).
[Crossref]
[PubMed]
S. P Mµller, M. F. Kijewski, S. C. Moore, and B. L. Holman, “Maximum-likelihood Estimation: A Mathematical Model for Quantitation in Nuclear Medicine,” J. Nucl. Med. 31, 1693–1701 (1989).
A. B. Hamza, H. Krim, and G. Unal, “Unifying probabilistic and variational estimation,” IEEE Signal Process Mag. 19, 37–47 (2002).
[Crossref]
M. A. Kupinski, E. Clarkson, K. Gross, and J. W. Hoppin, “Optimizing imaging hardware for estimation tasks,” Proc. SPIE 5034, 309–313 (2003).
[Crossref]
C. Caiafa, A. Proto, and E. Kuruoglu, “Long correlation Gaussian random fields: Parameter estimation and noise reduction,” Digital Signal Processing 17, 819–835 (2007).
[Crossref]
S. P Mµller, M. F. Kijewski, S. C. Moore, and B. L. Holman, “Maximum-likelihood Estimation: A Mathematical Model for Quantitation in Nuclear Medicine,” J. Nucl. Med. 31, 1693–1701 (1989).
S. P. Mµller, C. K. Abbey, F. J. Rybicki, S. C. Moore, and M. F. Kijewski, “Measures of performance in nonlinear estimation tasks: prediction of estimation performance at low signal-to-noise ratio,” Phys. Med. Biol. 50, 3697–3715 (2005).
[Crossref]
J. L. Melsa and D. L. Cohn, Decision and Estimation Theory (McGraw-Hill, 1978).
S. P. Mµller, C. K. Abbey, F. J. Rybicki, S. C. Moore, and M. F. Kijewski, “Measures of performance in nonlinear estimation tasks: prediction of estimation performance at low signal-to-noise ratio,” Phys. Med. Biol. 50, 3697–3715 (2005).
[Crossref]
S. C. Moore, M. F. Kijewski, and G. El Fakhri, “Collimator Optimization for Detection and Quantitation Tasks: Application to Gallium-67 Imaging,” IEEE Trans. Med. Imaging 24(10), 1347–1356 (2005).
[Crossref]
[PubMed]
G. El Fakhri, S. C. Moore, and M. F. Kijewski, “Optimization of Ga-67 imaging for detection and estimation tasks: Dependence of imaging performance on spectral acquisition parameters,” Med. Phys. 29, 1859–1866 (2002).
[Crossref]
[PubMed]
S. P Mµller, M. F. Kijewski, S. C. Moore, and B. L. Holman, “Maximum-likelihood Estimation: A Mathematical Model for Quantitation in Nuclear Medicine,” J. Nucl. Med. 31, 1693–1701 (1989).
H. H. Barrett, K. J. Myers, N. Devaney, and J. C. Dainty, “Objective Assessment of Image Quality: IV. Application to Adaptive Optics,” J. Opt. Soc. Am. A 23(12), 3080–3105 (2006).
[Crossref]
H. H. Barrett, K. J. Myers, B. Gallas, E. Clarkson, and H. Zhang, “Megalopinakophobia: Its Symptoms and Cures,” Proc. SPIE 4320, 299–307 (2001).
[Crossref]
H. H. Barrett and K. J. Myers, Foundations of Image Science (Wiley-Interscience, 2004).
R. E. Greenblatt, A. Ossadtchi, and M. E. Pflieger, “Local linear estimators for the bioelectromagnetic inverse problem,” IEEE Trans. Signal Process. 53(9), 3403–3412 (2005).
[Crossref]
R. E. Greenblatt, A. Ossadtchi, and M. E. Pflieger, “Local linear estimators for the bioelectromagnetic inverse problem,” IEEE Trans. Signal Process. 53(9), 3403–3412 (2005).
[Crossref]
C. Caiafa, A. Proto, and E. Kuruoglu, “Long correlation Gaussian random fields: Parameter estimation and noise reduction,” Digital Signal Processing 17, 819–835 (2007).
[Crossref]
S. P. Mµller, C. K. Abbey, F. J. Rybicki, S. C. Moore, and M. F. Kijewski, “Measures of performance in nonlinear estimation tasks: prediction of estimation performance at low signal-to-noise ratio,” Phys. Med. Biol. 50, 3697–3715 (2005).
[Crossref]
J. Shao, Mathematical Statistics (Springer, 1999).
A. B. Hamza, H. Krim, and G. Unal, “Unifying probabilistic and variational estimation,” IEEE Signal Process Mag. 19, 37–47 (2002).
[Crossref]
F. O. Bochud, J.-F. Valley, and F. R. Verdun, “Estimation of the noisy component of anatomical backgrounds,” Med. Phys. 26(7), 1365–1370 (1999).
[Crossref]
[PubMed]
F. O. Bochud, J.-F. Valley, and F. R. Verdun, “Estimation of the noisy component of anatomical backgrounds,” Med. Phys. 26(7), 1365–1370 (1999).
[Crossref]
[PubMed]
N WienerExtrapolation, Interpolation, and Smoothing of Stationary Time Series with Engineering Applications (The MIT press, 1949).
[PubMed]
H. H. Barrett, K. J. Myers, B. Gallas, E. Clarkson, and H. Zhang, “Megalopinakophobia: Its Symptoms and Cures,” Proc. SPIE 4320, 299–307 (2001).
[Crossref]
C. Caiafa, A. Proto, and E. Kuruoglu, “Long correlation Gaussian random fields: Parameter estimation and noise reduction,” Digital Signal Processing 17, 819–835 (2007).
[Crossref]
A. B. Hamza, H. Krim, and G. Unal, “Unifying probabilistic and variational estimation,” IEEE Signal Process Mag. 19, 37–47 (2002).
[Crossref]
S. C. Moore, M. F. Kijewski, and G. El Fakhri, “Collimator Optimization for Detection and Quantitation Tasks: Application to Gallium-67 Imaging,” IEEE Trans. Med. Imaging 24(10), 1347–1356 (2005).
[Crossref]
[PubMed]
R. E. Greenblatt, A. Ossadtchi, and M. E. Pflieger, “Local linear estimators for the bioelectromagnetic inverse problem,” IEEE Trans. Signal Process. 53(9), 3403–3412 (2005).
[Crossref]
Y. C. Eldar, “Comparing between estimation approaches: admissible and dominating linear estimators,” IEEE Trans. Signal Process. 54(5), 1689–1702 (2006).
[Crossref]
S. P Mµller, M. F. Kijewski, S. C. Moore, and B. L. Holman, “Maximum-likelihood Estimation: A Mathematical Model for Quantitation in Nuclear Medicine,” J. Nucl. Med. 31, 1693–1701 (1989).
H. H. Barrett, “Objective assessment of image quality: effects of quantum noise and object variability,” J. Opt. Soc. Am. A 7(7), 1266–1278 (1990).
[Crossref]
[PubMed]
J. P. Rolland and H. H. Barrett, “Effect of random background inhomogeneity on observer detection performance,” J. Opt. Soc. Am. A 9, 649–658 (1992).
[Crossref]
[PubMed]
M. Kupinski, J.W. Hoppin, E. Clarkson, and H. H. Barrett, “Ideal-observer computation in medical imaging with use of Markov-chain Monte Carlo techniques,” J. Opt. Soc. Am. A 20, 430–438 (2003).
[Crossref]
H. H. Barrett, K. J. Myers, N. Devaney, and J. C. Dainty, “Objective Assessment of Image Quality: IV. Application to Adaptive Optics,” J. Opt. Soc. Am. A 23(12), 3080–3105 (2006).
[Crossref]
G. El Fakhri, S. C. Moore, and M. F. Kijewski, “Optimization of Ga-67 imaging for detection and estimation tasks: Dependence of imaging performance on spectral acquisition parameters,” Med. Phys. 29, 1859–1866 (2002).
[Crossref]
[PubMed]
F. O. Bochud, J.-F. Valley, and F. R. Verdun, “Estimation of the noisy component of anatomical backgrounds,” Med. Phys. 26(7), 1365–1370 (1999).
[Crossref]
[PubMed]
S. P. Mµller, C. K. Abbey, F. J. Rybicki, S. C. Moore, and M. F. Kijewski, “Measures of performance in nonlinear estimation tasks: prediction of estimation performance at low signal-to-noise ratio,” Phys. Med. Biol. 50, 3697–3715 (2005).
[Crossref]
M. A. Kupinski, E. Clarkson, K. Gross, and J. W. Hoppin, “Optimizing imaging hardware for estimation tasks,” Proc. SPIE 5034, 309–313 (2003).
[Crossref]
H. H. Barrett, K. J. Myers, B. Gallas, E. Clarkson, and H. Zhang, “Megalopinakophobia: Its Symptoms and Cures,” Proc. SPIE 4320, 299–307 (2001).
[Crossref]
N WienerExtrapolation, Interpolation, and Smoothing of Stationary Time Series with Engineering Applications (The MIT press, 1949).
[PubMed]
J. L. Melsa and D. L. Cohn, Decision and Estimation Theory (McGraw-Hill, 1978).
J. Shao, Mathematical Statistics (Springer, 1999).
H. H. Barrett and K. J. Myers, Foundations of Image Science (Wiley-Interscience, 2004).