The Effects of Compensation for Scatter, Lead X-Rays, and High-Energy Contamination on Tumor Detectability and Activity Estimation in Ga-67 Imaging

IEEE Transactions on Nuclear Science

Volumn 50, Issue 3, 2003, Pages 439-445

  Fakhri, G El ^a   Kijewski, M F ^a   Moore, S C ^a   Maksud, P ^b  

^a BRIGHAM AND WOMEN S HOSPITAL   (United States)

^b UNIVERSITÉ PARIS SACLAY   (France)

Author keywords

Activity estimation; artificial neural networks; Compton scatter; cross talk; Ga 67 imaging; lead X rays; lesion detection

Indexed keywords

MONTE CARLO METHODS; NEURAL NETWORKS; OPTICAL COLLIMATORS; SIGNAL TO NOISE RATIO; X RAY SCATTERING;

COMPTON SCATTER; GENERALIZED SPECTRAL APPROACH; OPTIMAL ENERGY WINDOWS; THREE-CHANNEL HOTELLING OBSERVER;

X RAYS;

EID: 0038720392     PISSN: 00189499     EISSN: 15581578     Source Type: Journal    
DOI: 10.1109/TNS.2003.812446     Document Type: Article

References (11)

1. S. P. Bartold et al., “Procedure guideline for gallium scintigraphy in the evaluation of malignant disease,” J. Nucl. Med, vol. 38, pp. 990-994, 1997.
2. T. H. Farncombe et al., “An optimization of reconstruction parameters and investigation into the impact of photon scatter in Ga-67 SPECT,” IEEE Trans. Nucl. Sci., vol. 49, pp. 2148-2154, 2002.
3. G. El Fakhri, S. Moore, and P. Maksud, “A new scatter compensation method for Ga-67 imaging using artificial neural networks,” IEEE Trans. Nucl. Sci., vol. 48, pp. 799-804, 2001.
4. S. C. Moore, G. El Fakhri, and P. Maksud, “Comparative assessment of energy-based methods of compensating for scatter and lead X-rays in Ga-67 imaging,” in Conf. Rec. Nuclear Science Symp., San Diego, CA, 2001.
5. S. C. Moore and G. El Fakhri, “Realistic Monte Carlo simulation of Ga-67 SPECT imaging,” IEEE Trans. Nucl. Sci., vol. 48, pp. 720-724, 2001.
6. D. Rumelhart, G. Hinton, and R. Williams, “Learning internal representation by error propagation,” in Parallel Distributed Processing: Explorations in the Microstructures of Cognition, D. E. Rumelhart and J. L. McClell, Eds. Cambridge, MA: MIT Press, 1986, pp. 318-362.
7. S. C. Moore, M. F. Kijewski, S. P. Müller, F. Rybicki, and R. E. Zimmerman, “Evaluation of scatter compensation methods by their effects on parameter estimation from SPECT projections,” Med. Phys., vol. 28, pp. 278-287, 2001.
8. 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., vol. 29, pp. 1859-1866, 2002.
9. K. J. Myers and H. H. Barrett, “Addition of a channel mechanism to the ideal-observer model,” J. Opt. Soc. Amer. A, vol. 4, pp. 2447-2457, 1987.
10. C. K. Abbey and H. H. Barrett, “Human-and model-observer performance in ramp-spectrum noise; effects of regularization and object variability,” J. Opt. Soc. Amer. A, vol. 18, pp. 473-488, 2001.
11. D. J. de Vries et al., “Effects of scatter subtraction on detection and quantitation in hepatic SPECT,” J. Nucl. Med., vol. 40, pp. 1011-1023, 1999.