Variations among detector channels in computed tomography can lead to ring artifacts in the reconstructed images and biased estimates in projection-based material decomposition. Typically, the ring artifacts are corrected by compensation methods based on flat fielding, where transmission measurements are required for a number of material-thickness combinations. Phantoms used in these methods can be rather complex and require an extensive number of transmission measurements. Moreover, material decomposition needs knowledge of the individual response of each detector channel to account for the detector inhomogeneities. For this purpose, we have developed a spectral response model that binwise predicts the response of a multibin photon-counting detector individually for each detector channel. The spectral response model is performed in two steps. The first step employs a forward model to predict the expected numbers of photon counts, taking into account parameters such as the incident x-ray spectrum, absorption efficiency, and energy response of the detector. The second step utilizes a limited number of transmission measurements with a set of flat slabs of two absorber materials to fine-tune the model predictions, resulting in a good correspondence with the physical measurements. To verify the response model, we apply the model in two cases. First, the model is used in combination with a compensation method which requires an extensive number of transmission measurements to determine the necessary parameters. Our spectral response model successfully replaces these measurements by simulations, saving a significant amount of measurement time. Second, the spectral response model is used as the basis of the maximum likelihood approach for projection-based material decomposition. The reconstructed basis images show a good separation between the calcium-like material and the contrast agents, iodine and gadolinium. The contrast agent concentrations are reconstructed with more than 94% accuracy.
Variations among detector channels in CT very sensitively lead to ring artefacts in the reconstructed images. For material decomposition in the projection domain, the variations can result in intolerable biases in the material line integral estimates. A typical way to overcome these effects is to apply calibration methods that try to unify spectral responses from different detector channels to an ideal response from a detector model. However, the calibration procedure can be rather complex and require excessive calibration measurements for a multitude of combinations of x-ray shapes, tissue combinations and thicknesses. In this paper, we propose a channel-wise model for a multibin photon-counting detector for spectral CT. Predictions of this channel-wise model match well with their physical performances, which can thus be used to eliminate ring artefacts in CT images and achieve projection-basis material decomposition. In an experimental validation, image data show significant improvement with respect to ring artefacts compared to images calibrated with flat-fielding data. Projection-based material decomposition gives basis material images showing good separation among individual materials and good quantification of iodine and gadolinium contrast agents. The work indicates that the channel-wise model can be used for quantitative CT with this detector.
Photon-counting detectors are promising candidates for use in the next generation of x-ray CT scanners. Among the foreseen benefits are higher spatial resolution, better trade-off between noise and dose, and energy discriminating capabilities. Silicon is an attractive detector material because of its low cost, mature manufacturing process and high hole mobility. However, it is sometimes claimed to be unsuitable for use in computed tomography because of its low absorption efficiency and high fraction of Compton scatter. The purpose of this work is to demonstrate that high-quality energy-resolved CT images can nonetheless be acquired with clinically realistic exposure parameters using a photon-counting silicon-strip detector with eight energy thresholds developed in our group. We use a single detector module, consisting of a linear array of 50 0.5 × 0.4 mm detector elements, to image a phantom in a table-top lab setup. The phantom consists of a plastic cylinder with circular inserts containing water, fat and aqueous solutions of calcium, iodine and gadolinium, in different concentrations. We use basis material decomposition to obtain water, calcium, iodine and gadolinium basis images and demonstrate that these basis images can be used to separate the different materials in the inserts. We also show results showing that the detector has potential for quantitative measurements of substance concentrations.
Background: We are developing a segmented silicon strip detector that operates in photon-counting mode and
allows pulse-height discrimination with 8 adjustable energy bins. In this work, we determine the energy resolution
of the detector using monoenergetic x-ray radiation from 40 keV to 120 keV. We further investigate the effects
of pulse pileup and charge sharing between detector channels that may lead to a decreased energy resolution.
Methods: For each incident monochromatic x-ray energy, we obtain count spectra at different photon fluxes.
These spectra corresponds to the pulse-height response of the detector and allow the determination of energy
resolution and charge-sharing probability. The energy resolution, however, is influenced by signal pileup and
charge sharing. Both effects are quantified using Monte Carlo simulations of the detector that aim to reproduce
the conditions during the measurements.
Results: The absolute energy resolution is found to increase from 1.7 to 2.1 keV for increasing energies 40
keV to 120 keV at the lowest measured photon flux. The effect of charge sharing is found to increase the absolute
energy resolution by a factor of 1.025 at maximum. This increase is considered as negligibly small. The pileup
of pulses leads to a deterioration rate of the energy resolution of 4 · 10-3 keV Mcps-1 mm2, corresponding to an
increase of 0.04keV per 10 Mcps increase of the detected count rate.
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