Presentation + Paper
12 March 2018 Energy dependence of SNR and DQE for effective monoenergetic imaging in spectral CT
Author Affiliations +
Abstract
Synthesized monoenergetic images, generated using linear weighted combination of basis material images, portray the anatomy at a selected effective energy. Images at both high and low effective energies have been proposed as clinically useful. This paper studies the dependence of signal-to-noise ratio (SNR) and detective quantum efficiency (DQE) on the selected energy for CdTe PCDs, and for other spectral CT that uses scintillator detectors. DQE is estimated as the squared of SNR for the system being evaluated divided by that of an ideal PCD. Signal is the unbiased line integral of a material of interest and noise is estimated using propagation of the Cramer-Rao Lower Bound through the weighted sum. SNR and DQE are unimodal with the optimal energy dependent on the mean and width of the measured spectrum, on the spectral response, and system, and weakly on the material of interest. For the CdTe detectors simulated, DQE(0) at the optimal energy is relatively tolerant of spectral degradation (85-92% depending on pixel size), but is highly dependent on effective energy, with maximum variation (in 250 μm pixels) of 22-85% for effective energies between 30 to 120 keV. Study of effect of spectral distribution on DQE shows that a wider spectrum shifts the optimum to lower energy and weakens the energy dependence. In comparison to dual kV and dual layer spectral CT, PCDs have lower optimal effective energy and show higher DQE at low effective energies than energy integrating detectors with dual kV spectra.
Conference Presentation
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Paurakh L. Rajbhandary and Norbert J. Pelc "Energy dependence of SNR and DQE for effective monoenergetic imaging in spectral CT", Proc. SPIE 10573, Medical Imaging 2018: Physics of Medical Imaging, 105731F (12 March 2018); https://doi.org/10.1117/12.2293932
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KEYWORDS
Signal to noise ratio

Sensors

Spatial frequencies

Bone

Quantum efficiency

X-rays

Imaging systems

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