(Thursday, 8/2/2018) 10:00 AM - 12:00 PM
Room: Room 207
Purpose: Anti-charge sharing (ACS) technologies of photon counting detectors (PCDs) help to mitigate the problem of charge sharing to improve energy resolution and impact other performance characteristics of the PCD such as detective quantum efficiency (DQE). The intrinsically nonlinear nature of ACS technologies makes it highly nontrivial to quantitatively model ACS. The purpose of this work was to develop and experimentally validate a cascaded model to quantify the impact of ACS on the zero frequency DQE of PCD systems.
Methods: A parallel cascaded model was developed and a system analysis was conducted to incorporate not only the generation and scattering effects of secondary quanta, but also the reabsorption and escape of secondary photons. The effect of ACS was modeled as a modified version of the conventional single-pixel (non-ACS) mode with reduced spreading radii of secondary quanta and reduced K-fluorescence travel distances (i.e., the two major problems associated with charge sharing). The parameters in the cascaded model were experimentally determined using a gamma-ray source (Am-241 isotope) and a CdTe-based PCD system (XCounter, Sweden). The cascaded model was then validated using four different polychromatic beams generated with a rotating-anode diagnostic x-ray tube. Validation experiments were performed with 10-20 energy thresholds for each spectrum; both ACS and single pixel modes were studied.
Results: From the Am-241 experiments, the distance reduction factor associated with the ACS was determined to be 0.40. For 90% of the data points, differences between theoretical DQE(0) and experimental ones were within ±0.05. Both theoretical and experimental results showed that ACS always improved DQE(0). The largest improvement was achieved with a detector threshold approximately 2/3 of the tube potential.
Conclusion: A quantitative model was introduced for PCD systems to understand its impact on zero-frequency DQE. Experimental studies were performed which demonstrated good agreement with the results from cascaded model analysis.
Funding Support, Disclosures, and Conflict of Interest: The work is partially supported by an NIH grant R01EB020521 and a DOD Breakthrough Award W81XWH-16-1-0031.
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