A multisegment annular Si-detector system for RBS analysis

Günzler, R.; Schüle, V.; Seeliger, G.; Weiser, M.; Böhringer, K. F.; Kalbitzer, S.; Kemmer, J.

doi:10.1016/0168-583x(88)90324-2

Cited by 23 publications

(6 citation statements)

References 6 publications

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“…But it is necessary to model, because the output depends on the input count rates and spectra, and thus, depends on the object to be imaged. Simple models, such as linear corrections or self-convolution, 80 are not accurate for modeling complex mechanisms of distortion. Various pulse pileup models have been developed, 35,[81][82][83][84] and we have developed a model 83,84 that satisfies the accuracy, efficiency, and ability to handle a large number of coincidence requirements for high input count rates.…”

Section: D Pcd Modelsmentioning

confidence: 99%

Vision 20/20: Single photon counting x‐ray detectors in medical imaging

2013

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Photon counting detectors (PCDs) with energy discrimination capabilities have been developed for medical x-ray computed tomography (CT) and x-ray (XR) imaging. Using detection mechanisms that are completely different from the current energy integrating detectors and measuring the material information of the object to be imaged, these PCDs have the potential not only to improve the current CT and XR images, such as dose reduction, but also to open revolutionary novel applications such as molecular CT and XR imaging. The performance of PCDs is not flawless, however, and it seems extremely challenging to develop PCDs with close to ideal characteristics. In this paper, the authors offer our vision for the future of PCD-CT and PCD-XR with the review of the current status and the prediction of (1) detector technologies, (2) imaging technologies, (3) system technologies, and (4) potential clinical benefits with PCDs.

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Section: D Pcd Modelsmentioning

confidence: 99%

Vision 20/20: Single photon counting x‐ray detectors in medical imaging

2013

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“…Johns and Yaffe 15 used a random or periodic pulse generator, with or without a pulse pileup rejector, to estimate the incident count rate and spectrum, but the method will not work without the special pulse generator. Others have used empirical filters to predict peak pileup effects; 22 however, the accuracy was limited because of simplifications and the use of empirical kernels. To our best knowledge, there have been no analytical models that satisfy all of the requirements discussed above.…”

Section: Introductionmentioning

confidence: 99%

An analytical model of the effects of pulse pileup on the energy spectrum recorded by energy resolved photon counting x‐ray detectors

et al. 2010

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Purpose: Recently, novel CdTe photon counting x-ray detectors ͑PCXDs͒ with energy discrimination capabilities have been developed. When such detectors are operated under a high x-ray flux, however, coincident pulses distort the recorded energy spectrum. These distortions are called pulse pileup effects. It is essential to compensate for these effects on the recorded energy spectrum in order to take full advantage of spectral information PCXDs provide. Such compensation can be achieved by incorporating a pileup model into the image reconstruction process for computed tomography, that is, as a part of the forward imaging process, and iteratively estimating either the imaged object or the line integrals using, e.g., a maximum likelihood approach. The aim of this study was to develop a new analytical pulse pileup model for both peak and tail pileup effects for nonparalyzable detectors. Methods: The model takes into account the following factors: The bipolar shape of the pulse, the distribution function of time intervals between random events, and the input probability density function of photon energies. The authors used Monte Carlo simulations to evaluate the model. Results: The recorded spectra estimated by the model were in an excellent agreement with those obtained by Monte Carlo simulations for various levels of pulse pileup effects. The coefficients of variation ͑i.e., the root mean square difference divided by the mean of measurements͒ were 5.3%-10.0% for deadtime losses of 1%-50% with a polychromatic incident x-ray spectrum. Conclusions:The proposed pulse pileup model can predict recorded spectrum with relatively good accuracy.

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“…17 Analytical models for spectral distortions have also been discussed in the literature. 16,19,[21][22][23][24] A new model has recently been developed for nonparalyzable detectors, 25 which takes into account the following factors: the probability distribution of time intervals between photons, the probability distribution of photon energies, and a more realistic average pulse shape. The aim of this study was to evaluate the agreement between data measured using the DXMCT-1 ͑Refs.…”

Section: Introductionmentioning

confidence: 99%

Modeling the performance of a photon counting x‐ray detector for CT: Energy response and pulse pileup effects

et al. 2011

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Purpose:Recently, photon counting x-ray detectors ͑PCXDs͒ with energy discrimination capabilities have been developed for potential use in clinical computed tomography ͑CT͒ scanners. These PCXDs have great potential to improve the quality of CT images due to the absence of electronic noise and weights applied to the counts and the additional spectral information. With high count rates encountered in clinical CT, however, coincident photons are recorded as one event with a higher or lower energy due to the finite speed of the PCXD. This phenomenon is called a "pulse pileup event" and results in both a loss of counts ͑called "deadtime losses"͒ and distortion of the recorded energy spectrum. Even though the performance of PCXDs is being improved, it is essential to develop algorithmic methods based on accurate models of the properties of detectors to compensate for these effects. To date, only one PCXD ͑model DXMCT-1, DxRay, Inc., Northridge, CA͒ has been used for clinical CT studies. The aim of that study was to evaluate the agreement between data measured by DXMCT-1 and those predicted by analytical models for the energy response, the deadtime losses, and the distorted recorded spectrum caused by pulse pileup effects. Methods: An energy calibration was performed using 99m Tc ͑140 keV͒, 57 Co ͑122 keV͒, and an x-ray beam obtained with four x-ray tube voltages ͑35, 50, 65, and 80 kVp͒. The DXMCT-1 was placed 150 mm from the x-ray focal spot; the count rates and the spectra were recorded at various tube current values from 10 to 500 A for a tube voltage of 80 kVp. Using these measurements, for each pulse height comparator we estimated three parameters describing the photon energy-pulse height curve, the detector deadtime , a coefficient k that relates the x-ray tube current I to an incident count rate a by a = k ϫ I, and the incident spectrum. The mean pulse shape of all comparators was acquired in a separate study and was used in the model to estimate the distorted recorded spectrum. The agreement between data measured by the DXMCT-1 and those predicted by the models was quantified by the coefficient of variation ͑COV͒, i.e., the root mean square difference divided by the mean of the measurement. Results: Photon energy versus pulse height curves calculated with an analytical model and those measured using the DXMCT-1 were in agreement within 0.2% in terms of the COV. The COV between the output count rates measured and those predicted by analytical models was 2.5% for deadtime losses of up to 60%. The COVs between spectra measured and those predicted by the detector model were within 3.7%-7.2% with deadtime losses of 19%-46%. Conclusions: It has been demonstrated that the performance of the DXMCT-1 agreed exceptionally well with the analytical models regarding the energy response, the count rate, and the recorded spectrum with pulse pileup effects. These models will be useful in developing methods to compensate for these effects in PCXD-based clinical CT systems.

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A multisegment annular Si-detector system for RBS analysis

Cited by 23 publications

References 6 publications

Vision 20/20: Single photon counting x‐ray detectors in medical imaging

Vision 20/20: Single photon counting x‐ray detectors in medical imaging

An analytical model of the effects of pulse pileup on the energy spectrum recorded by energy resolved photon counting x‐ray detectors

Modeling the performance of a photon counting x‐ray detector for CT: Energy response and pulse pileup effects

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