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Deep learning (DL) has proven to be important for computed tomography (CT) image denoising. However, such models are usually trained under supervision, requiring paired data that may be difficult to obtain in practice. Diffusion models offer unsupervised means of solving a wide range of inverse problems via posterior sampling. In particular, using the estimated unconditional score function of the prior distribution, obtained via unsupervised learning, one can sample from the desired posterior via hijacking and regularization. However, due to the iterative solvers used, the number of function evaluations (NFE) required may be orders of magnitudes larger than for single-step samplers. In this paper, we present a novel image denoising technique for photon-counting CT by extending the unsupervised approach to inverse problem solving to the case of Poisson flow generative models (PFGM)++. By hijacking and regularizing the sampling process we obtain a single-step sampler, that is NFE = 1. Our proposed method incorporates posterior sampling using diffusion models as a special case. We demonstrate that the added robustness afforded by the PFGM++ framework yields significant performance gains. Our results indicate competitive performance compared to popular supervised, including state-of-the-art diffusion-style models with NFE = 1 (consistency models), unsupervised, and non-DL-based image denoising techniques, on clinical low-dose CT data and clinical images from a prototype photon-counting CT system developed by GE HealthCare.
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BACKGROUND: Edge-on-irradiated silicon detectors are currently being investigated for use in full-body photon-counting computed tomography (CT) applications. The low atomic number of silicon leads to a significant number of incident photons being Compton scattered in the detector, depositing a part of their energy and potentially being counted multiple times. Even though the physics of Compton scatter is well established, the effects of Compton interactions in the detector on image quality for an edge-on-irradiated silicon detector have still not been thoroughly investigated. PURPOSE: To investigate and explain effects of Compton scatter on low-frequency detective quantum efficiency (DQE) for photon-counting CT using edge-on-irradiated silicon detectors. METHODS: We extend an existing Monte Carlo model of an edge-on-irradiated silicon detector with 60 mm active absorption depth, previously used to evaluate spatial-frequency-based performance, to develop projection and image domain performance metrics for pure density and pure spectral imaging tasks with 30 and 40 cm water backgrounds. We show that the lowest energy threshold of the detector can be used as an effective discriminator of primary counts and cross-talk caused by Compton scatter. We study the developed metrics as functions of the lowest threshold energy for root-mean-square electronic noise levels of 0.8, 1.6, and 3.2 keV, where the intermediate level 1.6 keV corresponds to the noise level previously measured on a single sensor element in isolation. We also compare the performance of a modeled detector with 8, 4, and 2 optimized energy bins to a detector with 1-keV-wide bins. RESULTS: In terms of low-frequency DQE for density imaging, there is a tradeoff between using a threshold low enough to capture Compton interactions and avoiding electronic noise counts. For 30 cm water phantom, 4 energy bins, and a root-mean-square electronic noise of 0.8, 1.6, and 3.2 keV, it is optimal to put the lowest energy threshold at 3, 6, and 1 keV, which gives optimal projection-domain DQEs of 0.64, 0.59, and 0.52, respectively. Low-frequency DQE for spectral imaging also benefits from measuring Compton interactions with respective optimal thresholds of 12, 12, and 13 keV. No large dependence on background thickness was observed. For the intermediate noise level (1.6 keV), increasing the lowest threshold from 5 to 35 keV increases the variance in a iodine basis image by 60%-62% (30 cm phantom) and 67%-69% (40 cm phantom), with 8 bins. Both spectral and density DQE are adversely affected by increasing the electronic noise level. Image-domain DQE exhibits similar qualitative behavior as projection-domain DQE. CONCLUSIONS: Compton interactions contribute significantly to the density imaging performance of edge-on-irradiated silicon detectors. With the studied detector topology, the benefit of counting primary Compton interactions outweighs the penalty of multiple counting at all lowest threshold energies. Compton interactions also contribute significantly to the spectral imaging performance for measured energies above 10 keV.
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Método de Monte Carlo , Fótons , Espalhamento de Radiação , Silício , Tomografia Computadorizada por Raios X , Silício/química , Tomografia Computadorizada por Raios X/instrumentação , Imagens de FantasmasRESUMO
Purpose: Current photon-counting computed tomography detectors are limited to a pixel size of around 0.3 to 0.5 mm due to excessive charge sharing degrading the dose efficiency and energy resolution as the pixels become smaller. In this work, we present measurements of a prototype photon-counting detector that leverages the charge sharing to reach a theoretical sub-pixel resolution in the order of 1 µm. The goal of the study is to validate our Monte-Carlo simulation using measurements, enabling further development. Approach: We measure the channel response at the MAX IV Lab, in the DanMAX beamline, with a 35 keV photon beam, and compare the measurements with a 2D Monte Carlo simulation combined with a charge transport model. Only a few channels on the prototype are connected to keep the number of wire bonds low. Results: The measurements agree generally well with the simulations with the beam close to the electrodes but diverge as the beam is moved further away. The induced charge cloud signals also seem to increase linearly as the beam is moved away from the electrodes. Conclusions: The agreement between measurements and simulations indicates that the Monte-Carlo simulation can accurately model the channel response of the detector with the photon interactions close to the electrodes, which indicates that the unconnected electrodes introduce unwanted effects that need to be further explored. With the same Monte-Carlo simulation previously indicating a resolution of around 1 µm with similar geometry, the results are promising that an ultra-high resolution detector is not far in the future.
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Objective.An ultra-fine-pitch deep silicon detector has been developed for clinical photon-counting computed tomography (CT). With a small pixel size of 14 × 650µm2, it has shown potential to reach micrometre spatial resolution in previous simulation studies. A detector prototype with such geometry has been manufactured, and we report on the first experimental evaluation of its count-rate performance.Approach.The measurement was carried out at MAX IV synchrotron laboratory with 35 keV monochromatic x-rays. By inserting tungsten attenuators of 50, 75, 100, 150, 200, 225, 325µm-thicknesses into the beam, the response of the detector to fluence rates from 3.3 × 107to 1.3 × 1011mm-2s-1was characterized.Main results.The measurement result showed that the detector exhibited count rate linearity up to 6.66 × 108mm-2s-1with 13% count loss and was still functional at count rate up to 2.9 × 1010mm-2s-1. A semi-nonparalyzable dead-time model was fitted to the count-rate behaviour of the detector, showing great agreement with the measured data, with an estimated nonparalyzable dead time of 2.9 ns.Significance.This is the first experimental evaluation of the count-rate performance for a deep silicon detector with such small pixel geometry. The results suggest that this type of detector shows the potential to be used at fluence rates encountered in clinical CT with little count loss due to pile-up.
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Silício , Tomografia Computadorizada por Raios X , Tomografia Computadorizada por Raios X/métodos , Raios X , FótonsRESUMO
Artificial molecular motors are designed to transform external energy into useful work in the form of unidirectional motion1. They have been studied mainly in solution2-4, but also on solid surfaces5,6, which provide fixed reference points, allowing for tracking of their movement. However, these molecules require sophisticated design and synthesis, because the motor function must be imprinted into the chemical structure, and show reduced functionality on surfaces compared with in solution5-8. DNA walkers9,10, on the other hand, impart high directionality as they include the surface as part of the motor function, but they require chemical surface patterning and sequential solvent modification for motor activation. Here we show how efficient motors can operate at much smaller length scales on a homogeneous metal surface without any liquid. This is realized by combining a surface with a simple molecule, which, by itself, does not contain any motor unit. The motion, which is tracked at the single-molecule level, is triggered by intramolecular proton transfer with a corresponding modulation of the potential energy surface. Each molecule moves with 100 percent unidirectionality along an atomically defined straight line. Proof of the motor performing meaningful work is shown by controlled transport of single carbon monoxide molecules. This simplistic concept could form the basis for the controlled bottom-up assembly of nanostructures at the atomic scale.
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The majority of the world population carry the gastric pathogen Helicobacter pylori. Fortunately, most individuals experience only low-grade or no symptoms, but in many cases the chronic inflammatory infection develops into severe gastric disease, including duodenal ulcer disease and gastric cancer. Here we report on a protective mechanism where H. pylori attachment and accompanying chronic mucosal inflammation can be reduced by antibodies that are present in a vast majority of H. pylori carriers. These antibodies block binding of the H. pylori attachment protein BabA by mimicking BabA's binding to the ABO blood group glycans in the gastric mucosa. However, many individuals demonstrate low titers of BabA blocking antibodies, which is associated with an increased risk for duodenal ulceration, suggesting a role for these antibodies in preventing gastric disease.
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Purpose: Our purpose is to investigate the timing resolution in edge-on silicon strip detectors for photon-counting spectral computed tomography. Today, the timing for detection of individual x-rays is not measured, but in the future, timing information can be valuable to accurately reconstruct the interactions caused by each primary photon. Approach: We assume a pixel size of 12 × 500 µ m 2 and a detector with double-sided readout with low-noise CMOS electronics for pulse processing for every pixel on each side. Due to the electrode width in relation to the wafer thickness, the induced current signals are largely dominated by charge movement close to the collecting electrodes. By employing double-sided readout electrodes, at least two signals are generated for each interaction. By comparing the timing of the induced current pulses, the time of the interaction can be determined and used to identify interactions that originate from the same incident photon. Using a Monte Carlo simulation of photon interactions in combination with a charge transport model, we evaluate the performance of estimating the time of the interaction for different interaction positions. Results: Our simulations indicate that a time resolution of 1 ns can be achieved with a noise level of 0.5 keV. In a detector with no electronic noise, the corresponding time resolution is â¼ 0.1 ns . Conclusions: Time resolution in edge-on silicon strip CT detectors can potentially be used to increase the signal-to-noise-ratio and energy resolution by helping in identifying Compton scattered photons in the detector.
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We have studied 22-oxahemiporphycene molecules by a combination of scanning tunneling microscopy at low temperatures and density functional theory calculations. In contrast to other molecular switches with typically two switching states, these molecules can in principle exist in three different tautomers, due to their asymmetry and three inequivalent binding positions of a hydrogen atom in their macrocycle. Different tautomers are identified from the typical appearance on the surface and tunneling electrons can be used to tautomerize single molecules in a controllable way with the highest rates if the STM tip is placed close to the hydrogen binding positions in the cavity. Characteristic switching processes are explained by the different energy pathways upon adsorption on the surface. Upon applying higher bias voltages, deprotonation occurs instead of tautomerization, which becomes evident in the molecular appearance.
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Purpose: Compton interactions amount to a significant fraction of the registered counts in a silicon detector. In a Compton interaction, only a part of the photon energy is deposited and a single incident photon can result in multiple counts unless tungsten shielding is used. Deep silicon has proved to be a competitive material for photon-counting CT detectors, but to improve the performance further, one possibility is to use coincidence techniques to identify Compton-scattered photons and reconstruct their incident energies. Approach: In a detector with no tungsten shielding, incident photons can interact through a series of interactions. Based on the position and energy of each interaction, probability-based methods can be used to estimate the incident photon energy. Here, we present a maximum likelihood estimation framework along with an alternative method to estimate the incident photon energy and position in a silicon detector. Results: Assuming one incident photon per time frame, we show that the incident photon energy can be estimated with a mean error of - 0.07 ± 0.03 keV and an RMS error of 3.36 ± 0.02 keV for a realistic case in which we assume a detector with limited energy and spatial resolution. The interaction position was estimated with a mean error of - 2 ± 11 µ m in x direction and 7 ± 11 µ m in y direction. Corresponding RMS errors of 1.09 ± 0.01 and 1.10 ± 0.01 mm were achieved in x and y , respectively. Conclusions: The presented results show the potential of using probability-based methods to improve the performance of silicon detectors for CT.
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Purpose: Spatial resolution for current scintillator-based computed tomography (CT) detectors is limited by the pixel size of about 1 mm. Direct conversion photon-counting detector prototypes with silicon- or cadmium-based detector materials have lately demonstrated spatial resolution equivalent to about 0.3 mm. We propose a development of the deep silicon photon-counting detector which will enable a resolution of 1 µ m , a substantial improvement compared to the state of the art. Approach: With the deep silicon sensor, it is possible to integrate CMOS electronics and reduce the pixel size at the same time as significant on-sensor data processing capability is introduced. A Gaussian curve can then be fitted to the charge cloud created in each interaction.We evaluate the feasibility of measuring the charge cloud shape of Compton interactions for deep silicon to increase the spatial resolution. By combining a Monte Carlo photon simulation with a charge transport model, we study the charge cloud distributions and induced currents as functions of the interaction position. For a simulated deep silicon detector with a pixel size of 12 µ m , we present a method for estimating the interaction position. Results: Using estimations for electronic noise and a lowest threshold of 0.88 keV, we obtain a spatial resolution equivalent to 1.37 µ m in the direction parallel to the silicon wafer and 78.28 µ m in the direction orthogonal to the wafer. Conclusions: We have presented a simulation study of a deep silicon detector with a pixel size of 12 × 500 µ m 2 and a method to estimate the x-ray interaction position with ultra-high resolution. Higher spatial resolution can in general be important to detect smaller details in the image. The very high spatial resolution in one dimension could be a path to a practical implementation of phase contrast imaging in CT.
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We describe the creation and characterization of a calibration CT mini-lung-phantom incorporating simulated airways and ground-glass densities. Ten duplicate mini-lung-phantoms with Three-Dimensional (3-D) printed tubes simulating airways and gradated density polyurethane foam blocks were designed and built. Dimensional accuracy and CT numbers were measured using micro-CT and clinical CT scanners. Micro-CT images of airway tubes demonstrated an average dimensional variation of 0.038 mm from nominal values. The five different densities of incorporated foam blocks, simulating ground-glass, showed mean CT numbers (±standard deviation) of -897.0 ± 1.5, -844.1 ± 1.5, -774.1 ± 2.6, -695.3 ± 1.6, and -351.0 ± 3.7 HU, respectively. Three-Dimensional printing and subtractive manufacturing enabled rapid, cost-effective production of ground-truth calibration mini-lung-phantoms with low inter-sample variation that can be scanned simultaneously with the patient undergoing lung quantitative CT.
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Impressão Tridimensional , Tomografia Computadorizada por Raios X , Calibragem , Humanos , Pulmão/diagnóstico por imagem , Imagens de FantasmasRESUMO
By employing single charge injections with an atomic force microscope, we investigated redox reactions of a molecule on a multilayer insulating film. First, we charged the molecule positively by attaching a single hole. Then we neutralized it by attaching an electron and observed three channels for the neutralization. We rationalize that the three channels correspond to transitions to the neutral ground state, to the lowest energy triplet excited states and to the lowest energy singlet excited states. By single-electron tunneling spectroscopy we measured the energy differences between the transitions obtaining triplet and singlet excited state energies. The experimental values are compared with density functional theory calculations of the excited state energies. Our results show that molecules in excited states can be prepared and that energies of optical gaps can be quantified by controlled single-charge injections. Our work demonstrates the access to, and provides insight into, ubiquitous electron-attachment processes related to excited-state transitions important in electron transfer and molecular optoelectronics phenomena on surfaces.
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The introduction of photon-counting detectors is expected to be the next major breakthrough in clinical x-ray computed tomography (CT). During the last decade, there has been considerable research activity in the field of photon-counting CT, in terms of both hardware development and theoretical understanding of the factors affecting image quality. In this article, we review the recent progress in this field with the intent of highlighting the relationship between detector design considerations and the resulting image quality. We discuss detector design choices such as converter material, pixel size, and readout electronics design, and then elucidate their impact on detector performance in terms of dose efficiency, spatial resolution, and energy resolution. Furthermore, we give an overview of data processing, reconstruction methods and metrics of imaging performance; outline clinical applications; and discuss potential future developments.
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Interpretação de Imagem Assistida por Computador/instrumentação , Interpretação de Imagem Assistida por Computador/métodos , Fótons , Tomografia Computadorizada por Raios X/instrumentação , Tomografia Computadorizada por Raios X/métodos , HumanosRESUMO
Photon-counting computed tomography (PCCT) is an emerging technology promising to substantially improve cardiovascular imaging. Recent engineering and manufacturing advances by several vendors are expected to imminently launch this new technology into clinical reality. Photon-counting detectors (PCDs) have multiple potential advantages over conventional energy integrating detectors (EIDs) such as the absence of electronic noise, multi-energy capability, and increased spatial resolution. These developments will have different timescales for implementation and will affect different clinical scopes. We describe the technical aspects of PCCT, explain the current developments, and finally discuss potential advantages of PCCT in cardiovascular imaging.
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Doenças Cardiovasculares/diagnóstico por imagem , Fótons , Tomografia Computadorizada por Raios X , Humanos , Valor Preditivo dos Testes , Interpretação de Imagem Radiográfica Assistida por Computador , Tomógrafos Computadorizados , Tomografia Computadorizada por Raios X/instrumentaçãoRESUMO
Purpose: Photon-counting silicon strip detectors are attracting interest for use in next-generation CT scanners. For CT detectors in a clinical environment, it is desirable to have a low power consumption. However, decreasing the power consumption leads to higher noise. This is particularly detrimental for silicon detectors, which require a low noise floor to obtain a good dose efficiency. The increase in noise can be mitigated using a longer shaping time in the readout electronics. This also results in longer pulses, which requires an increased deadtime, thereby degrading the count-rate performance. However, as the photon flux varies greatly during a typical CT scan, not all projection lines require a high count-rate capability. We propose adjusting the shaping time to counteract the increased noise that results from decreasing the power consumption. Approach: To show the potential of increasing the shaping time to decrease the noise level, synchrotron measurements were performed using a detector prototype with two shaping time settings. From the measurements, a simulation model was developed and used to predict the performance of a future channel design. Results: Based on the synchrotron measurements, we show that increasing the shaping time from 28.1 to 39.4 ns decreases the noise and increases the signal-to-noise ratio with 6.5% at low count rates. With the developed simulation model, we predict that a 50% decrease in power can be attained in a proposed future detector design by increasing the shaping time with a factor of 1.875. Conclusion: Our results show that the shaping time can be an important tool to adapt the pulse length and noise level to the photon flux and thereby optimize the dose efficiency of photon-counting silicon detectors.
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Purpose: Developing photon-counting CT detectors requires understanding the impact of parameters, such as converter material, thickness, and pixel size. We apply a linear-systems framework, incorporating spatial and energy resolution, to study realistic silicon (Si) and cadmium telluride (CdTe) detectors at a low count rate. Approach: We compared CdTe detector designs with 0.5 × 0.5 mm 2 and 0.225 × 0.225 mm 2 pixels and Si detector designs with 0.5 × 0.5 mm 2 pixels of 30 and 60 mm active thickness, with and without tungsten scatter blockers. Monte-Carlo simulations of photon transport were used together with Gaussian charge sharing models fitted to published data. Results: For detection in a 300-mm-thick object at 120 kVp, the 0.5- and 0.225-mm pixel CdTe systems have 28% to 41% and 5% to 29% higher detective quantum efficiency (DQE), respectively, than the 60-mm Si system with tungsten, whereas the corresponding numbers for two-material decomposition are 2% lower to 11% higher DQE and 31% to 54% lower DQE compared to Si. We also show that combining these detectors with dual-spectrum acquisition is beneficial. Conclusions: In the low-count-rate regime, CdTe detector systems outperform the Si systems for detection tasks, whereas silicon outperforms one or both of the CdTe systems for material decomposition.
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RATIONALE AND OBJECTIVES: The purpose of this study was to evaluate the feasibility of unconstrained three-material decomposition in a human tissue specimen containing iodinated contrast agent, using an experimental multi-bin photon-counting silicon detector. It was further to evaluate potential added clinical value compared to a 1st-generation state-of-the-art dual-energy computed tomography system. MATERIALS AND METHODS: A prototype photon-counting silicon detector in a bench-top setup for x-ray tomographic imaging was calibrated using a multi-material calibration phantom. A heart with calcified plaque was obtained from a deceased patient, and the coronary arteries were injected with an iodinated contrast agent mixed with gelatin. The heart was imaged in the experimental setup and on a 1st-generation state-of-the-art dual-energy computed tomography system. Projection-based three-material decomposition without any constraints was performed with the photon-counting detector data, and the resulting images were compared with those obtained from the dual-energy system. RESULTS: The photon-counting detector images show better separation of iodine and calcium compared to the dual-energy images. Additional experiments confirmed that unbiased estimates of soft tissue, calcium, and iodine could be achieved without any constraints. CONCLUSION: The proposed experimental system could provide added clinical value compared to current dual-energy systems for imaging tasks where mix-up of iodine and calcium is an issue, and the anatomy is sufficiently small to allow iodine to be differentiated from calcium. Considering its previously shown count rate capability, these results show promise for future integration of this detector in a clinical CT scanner. KEY POINTS: ⢠Spectral photon-counting detectors can solve some of the fundamental problems with conventional single-energy CT. ⢠Dual-energy methods can be used to differentiate iodine and calcium, but to do so must rely on constraints, since solving for three unknowns with only two measurements is not possible. Photon-counting detectors can improve upon these methods by allowing unconstrained three-material decomposition. ⢠A prototype photon-counting silicon detector with high count rate capability allows performing unconstrained three-material decomposition and qualitatively shows better differentiation of iodine and calcium than dual-energy CT.
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Meios de Contraste/farmacologia , Imagens de Fantasmas , Silício , Tomografia Computadorizada por Raios X/métodos , Calibragem , Estudos de Viabilidade , HumanosRESUMO
On page 1862 of [1] (the second page of the article), in the second column, between (5) and (6), the current text "variations in the measured number of counts between different dels" should be replaced with "variations in the log normalized measured number of counts between different dels."
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PURPOSE: Charge sharing and migration of scattered and fluorescence photons in an energy discriminating photon counting detector (PCD) degrade the detector's energy response and can cause a single incident photon to be registered as multiple events at different energies among neighboring pixels, leading to spatio-energetic correlation. Such a correlation in conventional linear, space-invariant imaging system can be usefully characterized by the frequency dependent detective quantum efficiency DQE(f). Defining and estimating DQE(f) for PCDs in a manner consistent with that of conventional detectors is complicated because the traditional definition of DQE(f) does not address spectral information. METHODS: We introduce the concept of presampling spectroscopic detective quantum efficiency, DQEs (f), and present an analysis of it for CdTe PCDs using a spatial domain method that starts from a previously described analytic computation of spatio-energetic crosstalk. DQEs (f) is estimated as the squared signal-to-noise ratio of the amplitude of a small-signal sinusoidal modulation of the object (cortical bone) thickness at frequency f estimated using data from the detector under consideration compared that obtained from the photon distribution incident on the detector. DQEs for material decomposition (spectral) and effective monoenergetic imaging tasks for different pixel pitch is studied based on the multipixel Cramér-Rao lower bound (CRLB) that accounts for inter pixel basis material correlation. Effective monoenergetic DQEs is estimated from the CRLB of a linear weighted combination of basis materials, and its energy dependence is also studied. RESULTS: Zero frequency DQEs for the spectral task was ~18%, 25%, and 34% for 250 µm, 500 µm, and 1 mm detector pixels respectively. Inter pixel signal correlation results in positive noise correlation between same basis material estimates of neighboring pixels, resulting in least impact on DQEs at the detector's Nyquist frequency. Effective monoenergetic DQEs (0) at the optimal energy is relatively tolerant of spectral degradation (85-91% depending on pixel size), but is highly dependent on the selected effective energy, with maximum variation (in 250 µm pixels) of 17% to 85% for effective energy between 30 to 120 keV. CONCLUSIONS: Our results show that spatio-energetic correlations degrade DQEs (f) beyond what is lost by poor spectral response in a single detector element. The positive correlation between computed single basis material values in neighboring pixels results in the penalty to DQEs (f) to be the least at the Nyquist frequency of the detector. It is desirable to reduce spectral degradation and crosstalk to minimize the impact on system performance. Larger pixels sizes have better spatio-energetic response due to lower charge sharing and escape of scatter and K-fluorescence photons, and therefore higher DQEs (0). Effective monoenergetic DQEs (0) at the optimal energy is much less affected by spectral degradation and crosstalk compared to DQEs for spectral tasks.
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Fótons , Monitoramento de Radiação/métodos , Modelos Teóricos , Espalhamento de RadiaçãoRESUMO
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.