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The detective quantum efficiency of photon‐counting x‐ray detectors using cascaded‐systems analyses
Author(s) -
Tanguay Jesse,
Yun Seungman,
Kim Ho Kyung,
Cunningham Ian A.
Publication year - 2013
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.4794499
Subject(s) - detective quantum efficiency , monte carlo method , quantum noise , detector , photon , optical transfer function , image quality , optics , photon counting , physics , noise (video) , x ray detector , quantum , mathematics , image (mathematics) , computer science , statistics , artificial intelligence , quantum mechanics
Purpose: Single‐photon counting (SPC) x‐ray imaging has the potential to improve image quality and enable new advanced energy‐dependent methods. The purpose of this study is to extend cascaded‐systems analyses (CSA) to the description of image quality and the detective quantum efficiency (DQE) of SPC systems.Methods: Point‐process theory is used to develop a method of propagating the mean signal and Wiener noise‐power spectrum through a thresholding stage (required to identify x‐ray interaction events). The new transfer relationships are used to describe the zero‐frequency DQE of a hypothetical SPC detector including the effects of stochastic conversion of incident photons to secondary quanta, secondary quantum sinks, additive noise, and threshold level. Theoretical results are compared with Monte Carlo calculations assuming the same detector model.Results: Under certain conditions, the CSA approach can be applied to SPC systems with the additional requirement of propagating the probability density function describing the total number of image‐forming quanta through each stage of a cascaded model. Theoretical results including DQE show excellent agreement with Monte Carlo calculations under all conditions considered.Conclusions: Application of the CSA method shows that false counts due to additive electronic noise results in both a nonlinear image signal and increased image noise. There is a window of allowable threshold values to achieve a high DQE that depends on conversion gain, secondary quantum sinks, and additive noise.