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Cadmium telluride (CdTe) is one of the materials used in photon-counting detectors for x-ray computed tomography. One challenge with this material is that it is susceptible to polarisation due to holes being trapped in impurities in the material. This can potentially lead to the buildup of bulk charge in the semiconductor, causing decreased charge collection efficiency and degraded energy resolution.
In this work, we develop a simulation model of CdTe detectors with polarisation and use it to study the effect of polarisation on the measured energy spectrum for different charge collection times. To this end, we use a theoretical model of charge buildup to find the critical charge in the detector’s bulk above which the detector can be considered completely polarised. We then simulate a 320-by-270-by-1600 μm CdTe detector used in CT clinical imaging, for varying degrees of polarisation (ratio between the actual charge and the critical charge) and charge collection time. Our results show that the measured spectrum gets heavily distorted for large degrees of polarisation or for short charge collection time. We also put these results in context by discussing how they relate to the critical fluence rate and the time of flight of the charge carriers. These results can lead to improved simulation models of CdTe detectors and a better understanding the factors affecting their imaging performance.
Photon-counting detectors are expected to bring a range of improvements to patient imaging with x-ray computed tomography (CT). One is higher spatial resolution. We demonstrate the resolution obtained using a commercial CT scanner where the original energy-integrating detector has been replaced by a single-slice, silicon-based, photon-counting detector. This prototype constitutes the first full-field-of-view silicon-based CT scanner capable of patient scanning. First, the pixel response function and focal spot profile are measured and, combining the two, the system modulation transfer function is calculated. Second, the prototype is used to scan a resolution phantom and a skull phantom. The resolution images are compared to images from a state-of-the-art CT scanner. The comparison shows that for the prototype 19 lp / cm are detectable with the same clarity as 14 lp / cm on the reference scanner at equal dose and reconstruction grid, with more line pairs visible with increasing dose and decreasing image pixel size. The high spatial resolution remains evident in the anatomy of the skull phantom and is comparable to that of other photon-counting CT prototypes present in the literature. We conclude that the deep silicon-based detector used in our study could provide improved spatial resolution in patient imaging without increasing the x-ray dose.
This course explains the principles of photon counting detectors for spectral x-ray imaging. Typical technical implementations are described and fundamental differences to energy integrating systems are pointed out. In particular, the issues of high-rate handling and the effect of detector cross talk on energy resolution are described. Requirements on electronics for spectral imaging in computed tomography is also discussed.
A second objective of the course is to describe how energy sensitive counting detectors make use of the energy sampling of the linear attenuation coefficients of the background and target materials for any given imaging task; methods like material basis decomposition and optimal energy weighting will be explained.
The second objective highlights the interesting fact that while the spatial-frequency descriptor of signal-to-noise-ratio transfer (DQE) of a system gives a complete characterization of performance for energy integrating (and pure photon counting) systems, it fails to characterize multibin systems since a complete description of the transfer characteristics requires specification of how the information of each energy bin is handled. The latter is in turn dependent on the imaging case at hand which shows that there is no such thing as an imaging case independent system DQE for photon counting multibin systems. We also suggest how this issue could be resolved.
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