Photon counting detectors are expected to be the next big step in the development of medical computed tomography. Accurate modeling of the behavior of photon counting detectors in the high count rate regime is therefore important for detector performance evaluations and the development of accurate image reconstruction methods. The commonly used ideal nonparalyzable detector model is based on the assumption that photon interactions are converted to pulses with zero extent in time, which is too simplistic to accurately predict the behavior of photon counting detectors in both low and high count rate regimes. In this work we develop a statistical count model for a nonparalyzable detector with finite pulse length and use it to derive the asymptotic mean and variance of the output count distribution using tools from renewal theory. We use the statistical moments of the distribution to construct an estimator of the true number of counts for pileup correction. We confirm the accuracy of the model and evaluate the pileup correction using Monte Carlo simulations. The results show that image quality is preserved for surprisingly high count rates.
Silicon photon-counting spectral detectors are promising candidates as the next generation detectors for medical CT. For silicon detectors, a low noise floor is necessary to obtain good detection efficiency. A low noise floor can be obtained by having a slow shaping filter in the ASIC, but this leads to a long dead-time, thus decreasing the count-rate performance. In this work, we evaluate the benefit of utilizing two sub-channels with different shaping times. It is shown by simulation that utilizing a dual shaper can increase the dose efficiency for equal count-rate capability by up to 17%.
Insufficient angular sampling in computed tomography can lead to aliasing artifacts that impair the quality of the reconstructed images. However, the angular sampling rate is often constrained due to practical limitations, such as the bandwidth of the data read-out or read-out noise. In this work, we present a new sampling scheme that allows aliasing-free image reconstruction with fewer angular samples. This is achieved by introducing a temporal offset between the samples acquired by adjacent detector pixels in the detector array. The temporal shift implies that the positions where the detector pixels sample the 2D Radon transform are interleaved in the angular direction, and if the shift is carefully selected, an optimal (hexagonal) sampling grid can be obtained. Optimal sampling grids are particularly effective in tomographic imaging since the bowtie-shaped spectral support of the sinogram allows a close tiling of the replicated spectra. We derive the sampling requirements when the proposed method is used and demonstrate that the obtained sampling grid reduces the aliasing artifacts compared to standard rectangular sampling at equal number of angular samples in simulated and experimental images. It is shown that the required number of angular samples can be reduced by 25-40%. The method is robust and easy to implement, and can therefore be of practical use for CT imaging where the number of views is limited.
SC1129: Photon Counting CT
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.