Literature DB >> 30136278

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

Katsuyuki Taguchi1, Karl Stierstorfer2, Christoph Polster2,3, Okkyun Lee1, Steffen Kappler2.   

Abstract

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 post-acquisition N × 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 × 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 cross-talk data between 3 × 3 neighboring sub-pixels and calculated the mean, variance, and covariance of output-pixels with each of N × N binning scheme [4 × 4 binning, 2 × 2 binning, and 1 × 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'), 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 variance-to-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 × 4 binning and 1 × 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 × 1 (900 μm)2 binning, 2 × 2 (450 μm)2 binning, and 4 × 4 (225 μm)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 sub-pixels. The difference among various binning and masking methods, however, was typically less than 0.06, which might result in a dose penalty of 13% if the CT system were linear.
© 2018 American Association of Physicists in Medicine.

Entities:  

Keywords:  computed tomography; cross-talk; double-counting; photon counting; spectral distortion; spectral response

Mesh:

Year:  2018        PMID: 30136278     DOI: 10.1002/mp.13146

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  7 in total

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2.  Development of a scanner-specific simulation framework for photon-counting computed tomography.

Authors:  Ehsan Abadi; Brian Harrawood; Jayasai R Rajagopal; Shobhit Sharma; Anuj Kapadia; William Paul Segars; Karl Stierstorfer; Martin Sedlmair; Elizabeth Jones; Ehsan Samei
Journal:  Biomed Phys Eng Express       Date:  2019-08-09

3.  Spectral Photon Counting CT: Imaging Algorithms and Performance Assessment.

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4.  Non-Local Low-Rank Cube-Based Tensor Factorization for Spectral CT Reconstruction.

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Journal:  IEEE Trans Med Imaging       Date:  2018-10-26       Impact factor: 10.048

5.  Assessment of Multienergy Interpixel Coincidence Counters (MEICC) for Charge Sharing Correction or Compensation for Photon Counting Detectors With Boxcar Signals.

Authors:  Katsuyuki Taguchi
Journal:  IEEE Trans Radiat Plasma Med Sci       Date:  2020-06-17

6.  A Clinically Driven Task-Based Comparison of Photon Counting and Conventional Energy Integrating CT for Soft Tissue, Vascular, and High-Resolution Tasks.

Authors:  Jayasai R Rajagopal; Pooyan Sahbaee; Faraz Farhadi; Justin B Solomon; Juan Carlos Ramirez-Giraldo; William F Pritchard; Bradford J Wood; Elizabeth C Jones; Ehsan Samei
Journal:  IEEE Trans Radiat Plasma Med Sci       Date:  2020-08-27

7.  Image-domain Material Decomposition for Spectral CT using a Generalized Dictionary Learning.

Authors:  Weiwen Wu; Peijun Chen; Shaoyu Wang; Varut Vardhanabhuti; Fenglin Liu; Hengyong Yu
Journal:  IEEE Trans Radiat Plasma Med Sci       Date:  2020-05-26
  7 in total

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