Spatio‐energetic cross‐talk in photon counting detectors: Numerical detector model (Pc<scp>TK</scp>) and workflow for <scp>CT</scp> image quality assessment

Taguchi, Katsuyuki; Stierstorfer, Karl; Polster, Christoph; Lee, Okkyun; Kappler, S.

doi:10.1002/mp.12863

Cited by 63 publications

(50 citation statements)

References 28 publications

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“…Two other models described in the literature include a small sphere with radius 15 lm at 70 keV, where the radius grows as a cube root of the energy, 29 and a larger sphere with radius 50 lm at 60 keV that linearly increases to a radius of 75 lm at 120 keV, 30 but other models also exist. 25 An experimental study found the best fit with a Gaussian charge cloud with r = 30 lm, which is slightly better than our choice of 40 lm. 24 All of these models are simplifications.…”

Section: B Monte Carlo Simulationsmentioning

confidence: 60%

“…While we chose to use in-house Monte Carlo codes for this work, an open-source toolkit that implements a similar approach has recently been made available. 25 Alternatives to Monte Carlo have also been demonstrated that may improve the computational efficiency of simulation. 26 Cascaded systems analysis, in particular, is an efficient method that can also generate theoretical insights on the limiting contributors to dose efficiency.…”

Section: B Monte Carlo Simulationsmentioning

confidence: 99%

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Digital count summing vs analog charge summing for photon counting detectors: A performance simulation study

Hsieh

Sjölin

2018

Medical Physics

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Section: B Monte Carlo Simulationsmentioning

confidence: 60%

Section: B Monte Carlo Simulationsmentioning

confidence: 99%

Digital count summing vs analog charge summing for photon counting detectors: A performance simulation study

Hsieh

Sjölin

2018

Medical Physics

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“…Almost all of n-tuple counting does not involve neighboring pixels because (a) the probability of triple-and quadruple-counting is less than 1.5% (see Table I of Ref. [12]); and (b) the probability of triple-and quadruple-counting at a pixel boundary is even smaller. Thus, most of spill-in events produce one count at the output-pixel-of-interest, while producing another count at a neighboring pixel.…”

Section: Discussionmentioning

confidence: 99%

“…The PcTK has been extensively evaluated by a Monte Carlo simulator in Ref. [12], while the agreement between the Monte Carlo simulator and an actual PCD has been evaluated in Ref. [13].…”

Section: A Normalized Covariance Matrix Of Neighboring 3 3 3 Pixelsmentioning

confidence: 99%

“…The factors included in the study were N 9 N sub-pixel binning, sub-pixel masking, and n-tuple-counting. We used the Photon Counting Toolkit (PcTK) software package (pctk.jhu.edu), which was developed based on the spatio-energetic cross-talk model version 3.2 among PCD sub-pixels 12 and made available to academic researchers. This paper is organized as follows.…”

Section: Introductionmentioning

confidence: 99%

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Spatio-energetic cross-talk in photon counting detectors: N×N binning and sub-pixel masking

Taguchi

Stierstorfer

Polster

et al. 2018

Medical Imaging 2018: Physics of Medical Imaging

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Purpose: Smaller pixel sizes of x-ray photon counting detectors (PCDs) benefit count rate capabilities but increase cross-talk and "double-counting" between neighboring PCD pixels. When an x-ray photon produces multiple (n) counts at neighboring (sub-)pixels and they are added during postacquisition N 9 N binning process, the variance of the final PCD output-pixel will be larger than its mean. In the meantime, anti-scatter grids are placed at the pixel boundaries in most of x-ray CT systems and will decrease cross-talk between sub-pixels because the grids mask sub-pixels underneath them, block the primary x-rays, and increase the separation distance between active sub-pixels. The aim of this paper was, first, to study the PCD statistics with various N 9 N binning schemes and three different masking methods in the presence of cross-talks, and second, to assess one of the most fundamental performances of x-ray CT: soft tissue contrast visibility. Methods: We used a PCD cross-talk model (Photon counting toolkit, PcTK) and produced crosstalk data between 3 9 3 neighboring sub-pixels and calculated the mean, variance, and covariance of output-pixels with each of N 9 N binning scheme [4 9 4 binning, 2 9 2 binning, and 1 9 1 binning (i.e., no binning)] and three different sub-pixel masking methods (no mask, 1-D mask, and 2-D mask). We then set up simulation to evaluate the soft tissue contrast visibility. X-rays of 120 kVp were attenuated by 10-40 cm-thick water, with the right side of PCDs having 0.5 cm thicker water than the left side. A pair of output-pixels across the left-right boundary were used to assess the sensitivity index (SI or d 0 ), which typically ranges 0-1 and is a generalized signal-to-noise ratio and a statistics used in signal detection theory. Results: Binning a larger number of sub-pixels resulted in larger mean counts and larger varianceto-mean ratio when the lower threshold of the energy window was lower than the half of the incident energy. Mean counts are in the order of no mask (the largest), 1-D mask, and 2-D mask but the difference in variance-to-mean ratio was small. For a given sub-pixel size and masking method, binning more sub-pixels degraded the normalized SI values but the difference between 4 9 4 binning and 1 9 1 binning was typically less than 0.06. 1-D mask provided better normalized SI values than no mask and 2-D mask for side-by-side case and the improvements were larger with fewer binnings, although the difference was less than 0.10. 2-D mask was the best for embedded case. The normalized SI values of combined binning, sub-pixel size, and masking were in the order of 1 9 1 (900 lm) 2 binning, 2 9 2 (450 lm) 2 binning, and 4 9 4 (225 lm) 2 binning for a given masking method but the difference between each of them were typically 0.02-0.05. Conclusion: We have evaluated the effect of double-counting between PCD sub-pixels with various binning and masking methods. SI values were better with fewer number of binning and larger subpixels. The difference among various binning and maskin...

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Spatio‐energetic cross‐talk in photon counting detectors: N × N binning and sub‐pixel masking

et al. 2018

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Spatio‐energetic cross‐talk in photon counting detectors: Numerical detector model (PcTK) and workflow for CT image quality assessment

Cited by 63 publications

References 28 publications

Digital count summing vs analog charge summing for photon counting detectors: A performance simulation study

Digital count summing vs analog charge summing for photon counting detectors: A performance simulation study

Spatio-energetic cross-talk in photon counting detectors: N×N binning and sub-pixel masking

Spatio‐energetic cross‐talk in photon counting detectors: N × N binning and sub‐pixel masking

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