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Published on: January 5, 2024
Frequency-dependent signal and noise in spectroscopic x-ray imaging
Jesse Tanguay1, Jinwoo Kim2, Ho Kyung Kim2
1Department of Physics, Ryerson University, Toronto, Ontario, M5B 2K3, Canada.
Purpose:
We present a new framework for theoretical analysis of the noise power spectrum (NPS) of photon-counting x-ray detectors, including simple photon-counting detectors (SPCDs) and spectroscopic x-ray detectors (SXDs), the latter of which use multiple energy thresholds to discriminate photon energies.
Methods:
We show that the NPS of SPCDs and SXDs, including spatio-energetic noise correlations, is determined by the joint probability density function (PDF) of deposited photon energies, which describes the probability of recording two photons of two different energies in two different elements following a single-photon interaction. We present an analytic expression for this joint PDF and calculate the presampling and digital NPS of CdTe SPCDs and SXDs. We calibrate our charge sharing model using the energy response of a cadmium zinc telluride (CZT) spectroscopic x-ray detector and compare theoretical results with Monte Carlo simulations.
Results:
Our analysis shows that charge sharing increases pixel signal-to-noise ratio (SNR), but degrades the zero-frequency signal-to-noise performance of SPCDs and SXDs. In all cases considered, this degradation was greater than 10%. Comparing the presampling NPS with the sampled NPS showed that degradation in zero-frequency performance is due to zero-frequency noise aliasing induced by charge sharing.
Conclusions:
Noise performance, including spatial and energy correlations between elements and energy bins, are described by the joint PDF of deposited energies which provides a method of determining the photon-counting NPS, including noise-aliasing effects and spatio-energetic effects in spectral imaging. Our approach enables separating noise due to x-ray interactions from that associated with sampling, consistent with cascaded systems analysis of energy-integrating systems. Our methods can be incorporated into task-based assessment of image quality for the design and optimization of spectroscopic x-ray detectors.
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