ArticleScientific reports2026
Monte Carlo validation of signal-to-noise improvements in transmission imaging using correlated annihilation photon pairs.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Quantum-Assisted Photon Imaging (QAPI) leverages the correlated photon pairs produced by positron annihilation to overcome the intrinsic noise limitations of classical radiation imaging. In this study, we develop a statistical framework describing the photon-counting behavior of QAPI and compare its predicted signal-to-noise ratio (SNR) performance against classical imaging under both idealized and realistic detector conditions. Analytical derivations demonstrate that QAPI exhibits reduced variance through two mechanisms: elimination of stochastic uncertainty in photon generation via idler detector measurements, and application of binomial rather than Poisson transmission statistics enabled by the high transmission probability of 511 keV photons. To validate these predictions, we performed GATE Monte Carlo simulations using a phantom with variable-depth inserts across a range of exposure times. Under idealized conditions, measured SNRs closely matched theoretical expectations, with QAPI consistently outperforming classical imaging across all transmission probabilities. Minor deviations at extreme transmission values were attributed to finite sampling effects and breakdown of the Poisson approximation. Realistic simulations incorporating CZT detector response revealed additional challenges, particularly coincidence pairing failures due to detector transmission, which we addressed through geometric correction of missing idler events and sensitivity-based normalization. Despite these complications, QAPI retained a substantial SNR advantage approaching [Formula: see text] improvement over classical imaging. These results establish that the statistical advantage of QAPI arises fundamentally from access to idler information and the favorable transmission characteristics of high-energy photons, providing a validated theoretical and computational foundation for quantum-assisted transmission imaging and motivating further experimental development.
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