Impacts of pulse pileup, charge sharing, and anti-charge sharing on the noise power spectra of photon counting detectors: theoretical analysis and experimental demonstrations (Conference Presentation)

2020 ◽  
Author(s):  
Ke Li ◽  
Xu Ji ◽  
Ran Zhang
Keyword(s):  
Theoretical Analysis ◽  
Photon Counting ◽  
Power Spectra ◽  
Noise Power ◽  
Charge Sharing ◽  
Pulse Pileup ◽  
Photon Counting Detectors

scholarly journals Polychromatic Iterative Statistical Material Image Reconstruction for Photon-Counting Computed Tomography

2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Thomas Weidinger ◽  
Thorsten M. Buzug ◽  
Thomas Flohr ◽  
Steffen Kappler ◽  
Karl Stierstorfer
Keyword(s):  
Computed Tomography ◽  
Probability Function ◽  
Photon Counting ◽  
Charge Sharing ◽  
Material Decomposition ◽  
Beam Hardening ◽  
Pulse Pileup ◽  
Local Approximations ◽  
Photon Counting Detectors ◽  
Image Pixels

This work proposes a dedicated statistical algorithm to perform a direct reconstruction of material-decomposed images from data acquired with photon-counting detectors (PCDs) in computed tomography. It is based on local approximations (surrogates) of the negative logarithmic Poisson probability function. Exploiting the convexity of this function allows for parallel updates of all image pixels. Parallel updates can compensate for the rather slow convergence that is intrinsic to statistical algorithms. We investigate the accuracy of the algorithm for ideal photon-counting detectors. Complementarily, we apply the algorithm to simulation data of a realistic PCD with its spectral resolution limited by K-escape, charge sharing, and pulse-pileup. For data from both an ideal and realistic PCD, the proposed algorithm is able to correct beam-hardening artifacts and quantitatively determine the material fractions of the chosen basis materials. Via regularization we were able to achieve a reduction of image noise for the realistic PCD that is up to 90% lower compared to material images form a linear, image-based material decomposition using FBP images. Additionally, we find a dependence of the algorithms convergence speed on the threshold selection within the PCD.

scholarly journals CdTe Based Energy Resolving, X-ray Photon Counting Detector Performance Assessment: The Effects of Charge Sharing Correction Algorithm Choice

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6093
Author(s):  
Oliver L. P. Pickford Scienti ◽  
Jeffrey C. Bamber ◽  
Dimitra G. Darambara
Keyword(s):  
Detection Efficiency ◽  
Photon Counting ◽  
Charge Sharing ◽  
Correction Algorithm ◽  
Detector Performance ◽  
Photon Counting Detector ◽  
Photon Counting Detectors ◽  
The Difference ◽  
Pixel Pitch ◽  
Made In

Most modern energy resolving, photon counting detectors employ small (sub 1 mm) pixels for high spatial resolution and low per pixel count rate requirements. These small pixels can suffer from a range of charge sharing effects (CSEs) that degrade both spectral analysis and imaging metrics. A range of charge sharing correction algorithms (CSCAs) have been proposed and validated by different groups to reduce CSEs, however their performance is often compared solely to the same system when no such corrections are made. In this paper, a combination of Monte Carlo and finite element methods are used to compare six different CSCAs with the case where no CSCA is employed, with respect to four different metrics: absolute detection efficiency, photopeak detection efficiency, relative coincidence counts, and binned spectral efficiency. The performance of the various CSCAs is explored when running on systems with pixel pitches ranging from 100 µm to 600µm, in 50 µm increments, and fluxes from 106 to 108 photons mm−2 s−1 are considered. Novel mechanistic explanations for the difference in performance of the various CSCAs are proposed and supported. This work represents a subset of a larger project in which pixel pitch, thickness, flux, and CSCA are all varied systematically.

Modeling photon-counting detectors for x-ray CT: spectral response and pulse-pileup effects and evaluation using real data

2013 ◽  
Author(s):  
J. Cammin ◽  
J. Xu ◽  
William C. Barber ◽  
J. S. Iwanczyk ◽  
N. E. Hartsough ◽  
...  
Keyword(s):  
Spectral Response ◽  
Photon Counting ◽  
Real Data ◽  
X Ray ◽  
Pulse Pileup ◽  
Photon Counting Detectors
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