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Proceedings Paper

Atomic number resolution for three spectral CT imaging systems
Author(s): J. Eric Tkaczyk; Rogerio Rodrigues; Jeffery Shaw; Jonathan Short; Yanfeng Du; Xiaoye Wu; Deborah Walter; William Leue; Daniel Harrison; Peter Edic
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Paper Abstract

The material specificity of computed tomography is quantified using an experimental benchtop imaging system and a physics-based system model. The apparatus is operated with different detector and system configurations each giving X-ray energy spectral information but with different overlap among the energy-bin weightings and noise statistics. Multislice, computed tomography sinograms are acquired using dual kVp, sequential source filters or a detector with two scintillator/photodiodes layers. Basis-material and atomic number images are created by first applying a material decomposition algorithm followed by filtered backprojection. CT imaging of phantom materials with known elemental composition and density were used for model validation. X-ray scatter levels are measured with a beam-blocking technique and the impact to material accuracy is quantified. The image noise is related to the intensity and spectral characteristics of the X-ray source. For optimal energy separation adequate image noise is required. The system must be optimized to deliver the appropriate high mA at both energies. The dual kVp method supports the opportunity to separately engineer the photon flux at low and high kvp. As a result, an optimized system can achieve superior material specificity in a system with limited acquisition time or dose. In contrast, the dual-layer and sequential acquisition modes rely on a material absorption mechanism that yields weaker energy separation and lower overall performance.

Paper Details

Date Published: 16 March 2007
PDF: 11 pages
Proc. SPIE 6510, Medical Imaging 2007: Physics of Medical Imaging, 651009 (16 March 2007); doi: 10.1117/12.709905
Show Author Affiliations
J. Eric Tkaczyk, Rose Hulman Institute of Technology (United States)
Rogerio Rodrigues, Rose Hulman Institute of Technology (United States)
Jeffery Shaw, Rose Hulman Institute of Technology (United States)
Jonathan Short, Rose Hulman Institute of Technology (United States)
Yanfeng Du, Rose Hulman Institute of Technology (United States)
Xiaoye Wu, Rose Hulman Institute of Technology (United States)
Deborah Walter, Rose Hulman Institute of Technology (United States)
William Leue, General Electric Research (United States)
Daniel Harrison, General Electric Research (United States)
Peter Edic, General Electric Research (United States)


Published in SPIE Proceedings Vol. 6510:
Medical Imaging 2007: Physics of Medical Imaging
Jiang Hsieh; Michael J. Flynn, Editor(s)

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