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arXiv · physics/0411236

Validation of the GATE Monte Carlo simulation platform for modelling a CsI(Tl) scintillation camera dedicated to small animal imaging

Abstract

Monte Carlo simulations are increasingly used in scintigraphic imaging to model imaging systems and to develop and assess tomographic reconstruction algorithms and correction methods for improved image quantitation. GATE (GEANT 4 Application for Tomographic Emission) is a new Monte Carlo simulation platform based on GEANT4 dedicated to nuclear imaging applications. This paper describes the GATE simulation of a prototype of scintillation camera dedicated to small animal imaging and consisting of a CsI(Tl) crystal array coupled to a position sensitive photomultiplier tube. The relevance of GATE to model the camera prototype was assessed by comparing simulated 99mTc point spread functions, energy spectra, sensitivities, scatter fractions and image of a capillary phantom with the corresponding experimental measurements. Results showed an excellent agreement between simulated and experimental data: experimental spatial resolutions were predicted with an error less than 100 mu m. The difference between experimental and simulated system sensitivities for different source-to-collimator distances was within 2%. Simulated and experimental scatter fractions in a [98-182 keV] energy window differed by less than 2% for sources located in water. Simulated and experimental energy spectra agreed very well between 40 and 180 keV. These results demonstrate the ability and flexibility of GATE for simulating original detector designs. The main weakness of GATE concerns the long computation time it requires: this issue is currently under investigation by the GEANT4 and the GATE collaborations

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BibTeXRIS

D. Lazaro, I. Buvat, G. Loudos, D. Strul, G. Santin, N. Giokaris, D. Donnarieix, L. Maigne, V. Spanoudaki, S. Styliaris, S. Staelens, V. Breton. 2004-11-26. Validation of the GATE Monte Carlo simulation platform for modelling a CsI(Tl) scintillation camera dedicated to small animal imaging. https://doi.org/10.1088/0031-9155%2F49%2F2%2F007

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