Photon-counting detector (PCD) bring multiple advantages, including higher contrast, lower noise, and improved spatial resolution compared to the conventional energy-integrating detector (EID) scanners. We investigated the image quality performance of a prototype CdZnTe-based photon-counting detector (PCD) CT scanner in this phantom study. We performed a phantom study 3D-printed inserts which mimicked coronary artery plaques along with calibrated concentrations of iodine, water, soft plaque (fat), and hard plaque (calcium). The phantom was scanned with similar settings on a CdZnTe-based PCD-CT system and a comparable state-of-the-art EID-CT system. Image noise, CT number stability, and CNR were measured in matched circular regions of interest. PCD-CT demonstrated ~50% lower noise compared to EID-CT across all x-ray exposures. Both systems showed a CT number deviation due to noise in the ±2 HU range. CNR across iodine, soft and hard plaques, and water showed improvement in the 201%-332% range for PCD-CT over EID-CT. Lastly, in a noise-matched setting PCD-CT can achieve similar image quality as EID-CT at 25% of the radiation dose.
Semiconductor-based photon counting detectors (PCDs) measure each incident photon energy through direct conversion process. Comparing to the conventional scintillator-based energy-integrating detectors (EIDs), it can be made with smaller pixel sizes and hence improve the system spatial resolution. The actual performance of the PCDs in CT system is compromised from ideal mainly due to two factors: charge sharing effect and pulse pileup. In particular, the charge sharing effect introduces signal crosstalk between neighboring pixels and degrade the detection spatial resolution. In this study, we derive a rigorous charge sharing detection formalism based on a comprehensive detector response model. The simulated results are compared with a pixel-to-pixel covariance measurement from a CZT-based prototype photon counting system. The results suggests that while a large fraction of detected events is affected by charge sharing, the actual measured crosstalk between neighboring pixels is greatly suppressed by a proper detection threshold in the counting mode. To understand the practical impact in image quality and optimize system design, a simplified crosstalk model based on the estimated charge sharing event rate is integrated into a system level simulation framework with realistic system specifications. The simulated image MTFs are measured for systems with four different pixel sizes. Results indicate that with realistic charge sharing effect, in the pixel size range that we tested, the image MTF steadily increases as the detector pixel size decreases.
Accurate physics modeling of a photon counting detector is essential for detector design and performance evaluation, Computer Tomography (CT) system-level performance investigation, material decomposition, image reconstruction. The detector response is complicated because various effects involve, including fluorescence X-rays, primary electron path, charge diffusion, charge repulsion, and charge trapping. In this paper, we will present a comprehensive detector modeling approach, which incorporates all these effect into account.
For large cone angle multi-detector CT (MDCT), the scattered radiation remains a challenging problem as it is part of the physics process in X-ray interaction. For a photon counting CT system, the scattered radiation has more profound impact to the system performance, as the scattered photons dominate the low energy regime of the measurement. Without proper corrections, the scattered radiation could introduce significant errors in the material decomposition, and degrade the material characterization and quantification accuracy. To mitigate the scatter problem, typically, hardware rejection and software correction algorithms can be both employed. The anti-scatter grids (ASG) are commonly used to absorb the scattered photons and help generate cleaner measurements. For semiconductor based photon counting detectors (CdTe/CdZnTe), due to charge sharing and cross-talk effects (k-escape, scatter), different ASG designs also change the detector spectral response by masking different detector areas. In this study, we will evaluate a CdZnTe based photon counting CT performance with various ASG designs at the low flux condition through simulations. The detector spectral responses with 2 different detector pixel sizes (250 um and 500um anode size) are generated by our internal simulation tool, using no ASG, 1-D and 2-D ASGs respectively. The scattered radiation is generated by GATE, a Geant4 based Monte Carlo simulation tool, using a large (33 cm diameter) cylindrical water phantom with concentric iodine/calcium inserts, and then added to the simulated phantom energy bin count measurements. The impact of the residual scatter with 1-D and 2-D ASGs in the basis and mono-energetic images will be evaluated and compared.
Different from Monte Carlo (MC) methods, radiative transfer equation (RTE) can precisely simulate single and multiple scattered photon distribution without simulated statistical noise in X-ray computed tomography. The simulated scattered photon distribution on the detectors can be used for scatter correction to reduce the artifacts and improve CT HU number accuracy. We have developed an integral spherical harmonics algorithm to solve the RTE and achieved good accuracy compared to MC methods. Here, we proposed a physical model-based scatter correction method with the developed RTE solution. The method includes the following steps: (1) The CT images are reconstructed from fast analytical method with scatter-contaminated projections and are segmented with HU threshold method; (2) Sparse-view scattered photon distribution is simulated with the developed RTE solver on segmented CT images; (3) Multiplicative scatter correction method makes use of interpolated full-view scattered photon distribution to remove scattering flux from measured projections; (4) The final CT images are reconstructed with corrected projections. Compared to hardware-based scattered photon rejection method with anti-scatter grid, the results show that scatter-induced artifacts are significantly reduced and HU uniformity is improved, demonstrating the efficiency of the proposed method.
Photon counting detectors are an appealing approach to spectral computed tomography for their theoretical benefits over conventional detectors. Detailed modeling and simulation is important for capturing the critical aspects of the counting and spectral performance of the detector. An approach to photon counting detector simulation is presented using a custom developed software program. The software consists of Monte-Carlo energy deposition, physics-based charge transport and current induction, and SPICE electronic simulation. It utilizes behind-the-scenes Gate for the photon interactions and energy deposition and ngspice for the SPICE electronic simulations. Various sensor geometries and definitions can be defined to simulation individual detector pixels or entire anode arrays for large-scale simulations. The simulation requires the specification of x-ray planar sources and can be specified on a per-channel basis with an energy distribution and flux. Given a sensor definition and a series of x-ray sources, the program calculates the energy-bin count read-out from each anode in the sensor array. The program can be used to study the detector response of various sensor and system geometries, including in the presence of anti-scatter grids, the performance of anti-charge sharing implementations, material decomposition algorithms, etc.
Cone-beam artifact may be observed in the images reconstructed from circular trajectory data by use of the FDK algorithm or its variants for an imaged subject with longitudinally strong contrast variation in advanced diagnostic CT with a large number of detector rows. Existing algorithms have limited success in correcting for the effect of the cone-beam artifacts especially on the reconstruction of low-contrast soft-tissue. In the work, we investigate and develop optimization-based reconstruction algorithms to compensate for the cone-beam artifacts in the reconstruction of low-contrast anatomies. Specifically, we investigate the impact of optimization-based reconstruction design based upon different data-fidelity terms on the artifact correction by using the Chambolle- Pock (CP) algorithm tailored to each of the specific data-fidelity terms considered. We performed numerical studies with real data collected with the 320-slice Canon Medical System CT scanner, demonstrated the effectiveness of the optimization-based reconstruction design, and identified the optimization-based reconstruction that corrects most effectively for the cone-beam artifacts.
Scatter is an important problem in computed tomography especially with the increase of X-ray illumination coverage in one single view. Poor scatter correction results in CT HU number inaccuracy, degrades low contrast detectability, and introduces artifacts. Hardware method can be used to handle scatter problem. However, hardware design optimization and scatter correction improvement require an efficient scatter simulation tool. Although Monte Carlo (MC) method can perform precise scatter simulation, simulated noise due to its statistical nature affects the simulation results. In this paper, a deterministic scatter simulation method with radiative transfer equation (RTE) is proposed. Compared to MC method, the deterministic RTE method is free from statistical noise. In order to solve the RTE, a novel iterative spherical harmonics integral formula is developed. Compared to MC method, the results show the accuracy of the proposed method.
We model the scatter radiation from the dose compensator in computed tomography (CT) using Monte Carlo (MC)
simulation. Dose compensator reduces the patient radiation dose but also adds some scatter radiation which can reach
detectors and degrade image quality. This scattered radiation impacts high contrast edges such as bone-soft tissue and
tissue-air interfaces, similar to the well known off-focal radiation from the X-ray tube. To the best of our knowledge, this
is the first study that uses MC simulation to model and investigate the compensator scatter radiation. Since detectors are
far from the scatter source and have small solid angle, traditional MC is not computationally efficient. We have
implemented variance reduction technique called forced detection (FD) to improve the computational efficiency, and
achieved an improvement factor of 42,800. The simulated scatter to primary ratio (SPR) ranges from a few percent to
11% across the detectors. Simulations of water phantoms indicate that such scatter can lead to significant effects along
edges as large as 20-30 HU, necessitating the need for correction. We demonstrate a correction in FBP reconstruction,
somewhat similar to off-focal correction, and show that it significantly reduces the level of the artifact along the edge of
the phantom.
This paper describes the image quality improvements achieved by developing a new fully physical imaging chain.
The key enablers for this imaging chain are a new scatter correction technique and an analytic computation of
the beam hardening correction for each detector. The new scatter correction technique uses off-line Monte Carlo
simulations to compute a large database of scatter kernels representative of a large variety of patient shapes
and an on-line combination of those based on the attenuation profile of the patient in the measured projections.
In addition, profiles of scatter originating from the wedge are estimated and subtracted. The beam hardening
coefficients are computed using analytic simulations of the full beam path of each individual ray through the
scanner. Due to the new approach, scatter and beam hardening are computed from first principles with no
further tuning factors, and are thus straight forward to adapt to any patient and scan geometry. Using the new
fully physical imaging chain unprecedented image quality was achieved. This is demonstrated with a special
scatter phantom. With current image correction techniques this phantom typically shows position dependent
inhomogeneity and streak artifacts resulting from the impact of scattered radiation. With the new imaging
chain these artifacts are almost completely eliminated, independent of position and scanning mode (kV). Further
preliminary patient studies show that in addition to fully guaranteeing an absolute Hounsfield scale in arbitrary
imaging conditions, the new technique also strongly sharpens object boundaries such as the edges of the liver.
A convolution model of scatter that is adaptable to rapid simulation and correction algorithms is tested against the measured scatter profiles. In the simple case of a uniform acrylic sheet, the convolution approach yields about 10% absolute agreement with the measured scatter profile. However, significant qualitative differences are demonstrated for phantoms with non-uniform thickness or composition. For example, the scatter profile is dependent on a bone's vertical position in the phantom whereas the primary is unchanged. Similarly, a cusp shape in the scatter profile observed near the abrupt edge of an acrylic sheet is not produced in the convolution model. An alternate approach that calculates the scatter as a 3D integral over the object volume can reproduce this behavior.
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