Simulation and experimental results on monolithic CdZnTe gamma-ray detectors

d’Aillon, Eric Gros; Gentet, Marie-Claude; Montémont, G.; Rustique, J.; Verger, J.M.

doi:10.1109/nssmic.2004.1466873

Cited by 8 publications

(3 citation statements)

References 17 publications

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“…Thanks to the CZT detector characteristics and an electronically-based 3D positioning, two complementary pieces of information can be taken advantage of to recover the spatial resolution: the Depth Of Interaction (DOl) information and the fine pixelization. First, the DOl information, obtained using the rise time of the signal or the cathode to anode pulse height ratio (available on biparametric spectra) [6][7], allows us to divide the CZT detector in several virtual layers (with an accuracy <1 mm). Distinct images (Le.…”

Section: A Backgroundmentioning

confidence: 99%

Simulation-based and experimental evaluation of HiSens, a new CdZnTe gamma-camera architecture

Robert

Montémont

Rebuffel

et al. 2008

2008 IEEE Nuclear Science Symposium Conference Record

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The performances of standard gamma-cameras are limited by the well-known trade-off between spatial resolution and sensitivity resulting from the collimator. To overcome this limitation, we have previously proposed a new approach named HiSens, which consists in the association of a pixelated CZT detector, new collimation geometry and dedicated reconstruction algorithms. Two maj or characteristics of the CZT detector are taken advantage of in this architecture: the availability of the depth of interaction (DOl) information and the fine pixelization.In this paper, we consider a configuration using a high sensitivity collimator: the septa height· of the collimator is reduced to ensure a gain in efficiency by a factor of five compared with the Anger Camera (10-4 efficiency). Using DOl information, CZT detector is divided in several virtual layers providing distinct images, which can be combined within a dedicated OSEM reconstruction scheme. Moreover, two possible pixelizations of the CZT detector are studied: one and four pixels per collimator hole. The ultimate aim of this study is to increase the global system efficiency while preserving the spatial resol ution.A complete evaluation of the performance of this architecture has been performed, based on a simple analytical model, on Monte Carlo simulations of the system, and on experimental data.Simulation results show that CZT detector over-pixelization improves the contrast without introducing additional noise. They are confirmed by the experimental validation: contribution of the detector over-pixelization is crucial for improved image quality.

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Section: A Backgroundmentioning

confidence: 99%

Simulation-based and experimental evaluation of HiSens, a new CdZnTe gamma-camera architecture

Robert

Montémont

Rebuffel

et al. 2008

2008 IEEE Nuclear Science Symposium Conference Record

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“…Instead of further decreasing the initially emitted radiation dose, if we just maintain the same photon number as in a conventional CT imaging, the channel‐wise dose collected by PCD is actually a small fraction of the total dose. Besides, the PCD is still premature in technical support and manufacturing process, and it suffers from pulse pileup, charge sharing, fluorescent x‐ray escape, inconsistent response, and dead pixels 14,27–30 . These barriers lead to energy spectral distortion and poor scan data quality, which further limit the attainable accuracy and precision in practical applications 31 …”

Section: Introductionmentioning

confidence: 99%

Locally linear transform based three‐dimensional gradient ‐norm minimization for spectral CT reconstruction

Wang

Deng

et al. 2020

Medical Physics

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Purpose: Spectral computed tomography (CT) is proposed by extending the conventional CT along the energy dimension. One newly implementation is to employ an energy-discriminating photon counting detector (PCD), which can distinguish photon energy and divide a whole x-ray spectrum into several energy bins with appropriate post-processing steps. The state-of-the-art PCD-based spectral CT has superior energy resolution and material distinguishability, and it further has a great potential in both medical and industrial applications. To improve the reconstruction quality and decomposition accuracy, in this work, we propose an optimization-based spectral CT reconstruction method with an innovational sparsity constraint. Methods: We first employ a locally linear transform to the reconstructed channel images, and the structural similarity along the spectral dimension is effectively converted to a one-dimensional (1D) gradient sparsity. Then, combining the prior knowledge of piecewise constant in the spatial domain (e.g., a two-dimensional (2D) gradient sparsity feature), we unify both spectral and spatial dimensions and establish a joint three-dimensional (3D) gradient sparsity. In addition, we use the L 0-norm to measure the proposed sparsity and incorporate it as a smoothness constraint to concretize a general optimization framework. Furthermore, we develop the corresponding iterative algorithm to solve the optimization problem. Results: Both visual results and quantitative indexes of numerical simulations and phantom experiments demonstrate the proposed method outperform the conventional filtered backprojection (FBP), total variation (TV), 2D L 0-norm (L 0), and TV with low rank (TVLR)-based methods. From the image and ROI comparisons, we find the proposed method performs well in noise suppression, detail maintenance, and decomposition accuracy. However, the FBP suffers severe noise, the TV and L 0 are difficult to work consistently among different energy bins, and the TVLR fails to avoid gray value shift. The image quality assessments, such as peak signal-to-noise ratio (PSNR), normal mean absolute deviation (NMAD). and structural similarity (SSIM), also consistently indicate the proposed method can effectively removing noise and keeping fine structures in both channel-wise reconstructions and material decompositions. Conclusions: By employing a locally linear transform, the structural similarity among spectral channel images is converted to a 1D gradient sparsity and the gray value shift is effectively avoided when the difference measurement is minimized. The 3D L 0-norm jointly and uniformly measures the gradient sparsity in both spectral and spatial dimensions. The cooperation of locally linear transform and 3D L 0-norm well reinforces the global sparse features and keeps the correlation along spectral dimension without bringing gray-value distortions. The corresponding constraint optimization model is fast and stably solved by using an alternative direction technique. Both numerical simulations and phantom experi...

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“…Due to these properties, fabricating pixellated semiconductor detectors using CZT results in low noise operations in room temperature [1]. One important factor in CZT detector's performance is weighting potential cross-talk between pixels that depends on the geometric characteristics of the detector, such as electrode size, pixel size, and detector thickness [2]. In other words, detector's performance including image resolution is related to these physical parameters.…”

Section: Introductionmentioning

confidence: 99%

Fine localization of photons on the pixellated detectors based on the analytical model

2010

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In this paper, an analytical model for evaluating the charge induction on pixels of the pixellated CdZnTe (CZT) detector is proposed. According to this model, the cross-talk between pixels increases while the pixel size decreases. We also propose a method for determining the position of charges more accurately by exploiting the charge sharing between the neighboring pixels. Conventionally to increase the resolution of the image, the pixel size is decreased that results in an increase in the amount of cross-talk. With our proposed method, the resolution of the image is effectively increased without the need for decreasing the pixel size.

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Simulation and experimental results on monolithic CdZnTe gamma-ray detectors

Cited by 8 publications

References 17 publications

Simulation-based and experimental evaluation of HiSens, a new CdZnTe gamma-camera architecture

Simulation-based and experimental evaluation of HiSens, a new CdZnTe gamma-camera architecture

Locally linear transform based three‐dimensional gradient ‐norm minimization for spectral CT reconstruction

Fine localization of photons on the pixellated detectors based on the analytical model

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