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, sequentially imposed 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 with good temporal registration. 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.
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