Improving model–data mismatch for photon-counting detector model using global and local model parameters

Donghyeon Lee, Xiaohui Zhan, W. Yang Tai, Wojciech Zbijewski, Katsuyuki Taguchi

Research output: Contribution to journalArticlepeer-review

Abstract

Background: An energy-discriminating capability of a photon counting detector (PCD) can provide many clinical advantages, but several factors, such as charge sharing (CS) and pulse pileup (PP), degrade the capability by distorting the measured x-ray spectrum. To fully exploit the merits of PCDs, it is important to characterize the output of PCDs. Previously proposed PCD output models showed decent agreement with physical PCDs; however, there were still scopes to be improved: a global model–data mismatch and pixel-to-pixel variations. Purposes: In this study, we improve a PCD model by using count-rate-dependent model parameters to address the issues and evaluate agreement against physical PCDs. Methods: The proposed model is based on the cascaded model, and we made model parameters condition-dependent and pixel-specific to deal with the global model–data mismatch and the pixel-to-pixel variation. The parameters are determined by a procedure for model parameter estimation with data acquired from different thicknesses of water or aluminum at different x-ray tube currents. To analyze the effects of having proposed model parameters, we compared three setups of our model: a model with default parameters, a model with global parameters, and a model with global-and-local parameters. For experimental validation, we used CdZnTe-based PCDs, and assessed the performance of the models by calculating the mean absolute percentage errors (MAPEs) between the model outputs and the actual measurements from low count-rates to high count-rates, which have deadtime losses of up to 24%. Results: The outputs of the proposed model visually matched well with the PCD measurements for all test data. For the test data, the MAPEs averaged over all the bins were 49.2–51.1% for a model with default parameters, 8.0–9.8% for a model with the global parameters, and 1.2–2.7% for a model with the global-and-local parameters. Conclusion: The proposed model can estimate the outputs of physical PCDs with high accuracy from low to high count-rates. We expect that our model will be actively utilized in applications where the pixel-by-pixel accuracy of a PCD model is important.

Original languageEnglish (US)
Pages (from-to)964-977
Number of pages14
JournalMedical physics
Volume51
Issue number2
DOIs
StatePublished - Feb 2024

Keywords

  • charge sharing
  • computed tomography
  • photon counting detectors
  • pulse pileup

ASJC Scopus subject areas

  • Biophysics
  • Radiology Nuclear Medicine and imaging

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