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Proceedings Paper

Physics-based modeling of X-ray CT measurements with energy-integrating detectors
Author(s): Yong Long; Hewei Gao; Mingye Wu; Jed D. Pack; Hao Xu; Kun Tao; Paul F. Fitzgerald; Bruno De Man
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Paper Abstract

Computer simulation tools for X-ray CT are important for research efforts in developing reconstructionmethods, designing new CT architectures, and improving X-ray source and detector technologies. In this paper, we propose a physics-based modeling method for X-ray CT measurements with energy-integrating detectors. It accurately accounts for the dependence characteristics on energy, depth and spatial location of the X-ray detection process, which is either ignored or over simplified in most existing CT simulation methods. Compared with methods based on Monte Carlo simulations, it is computationally much more efficient due to the use of a look-up table for optical collection efficiency. To model the CT measurments, the proposed model considers five separate effects: energy- and location-dependent absorption of the incident X-rays, conversion of the absorbed X-rays into the optical photons emitted by the scintillator, location-dependent collection of the emitted optical photons, quantumefficiency of converting fromoptical photons to electrons, and electronic noise. We evaluated the proposed method by comparing the noise levels in the reconstructed images from measured data and simulations of a GE LightSpeed VCT system. Using the results of a 20 cm water phantom and a 35 cm polyethylene (PE) disk at various X-ray tube voltages (kVp) and currents (mA), we demonstrated that the proposed method produces realistic CT simulations. The difference in noise standard deviation between measurements and simulations is approximately 2% for the water phantom and 10% for the PE phantom.

Paper Details

Date Published: 19 March 2014
PDF: 8 pages
Proc. SPIE 9033, Medical Imaging 2014: Physics of Medical Imaging, 90334S (19 March 2014); doi: 10.1117/12.2043144
Show Author Affiliations
Yong Long, GE Global Research Ctr. (United States)
Hewei Gao, GE Healthcare Technologies (United States)
Mingye Wu, GE China Technology Ctr. (China)
Jed D. Pack, GE Global Research Ctr. (United States)
Hao Xu, GE China Technology Ctr. (China)
Kun Tao, GE China Technology Ctr. (China)
Paul F. Fitzgerald, GE Global Research Ctr. (United States)
Bruno De Man, GE Global Research Ctr. (United States)


Published in SPIE Proceedings Vol. 9033:
Medical Imaging 2014: Physics of Medical Imaging
Bruce R. Whiting; Christoph Hoeschen, Editor(s)

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