Cascaded models and the DQE of flat-panel imagers: Noise aliasing, secondary quantum noise and reabsorption

Theoretical models of the detective quantum efficiency (DQE) provide insight into fundamental performance limitations and standards to which particular systems can be compared. Over the past several years, cascaded models have been developed to describe the DQE of several flat panel detectors. This article summarizes the governing principles of cascaded models, and conditions that must be satisfied to prevent misuse. It is shown how to incorporate: a) poly-energetic x rays; b) Swank noise; c) the Lubberts effect; d) reabsorption of K x rays from photo-electric interactions; e) secondary quantum noise; and, f) noise aliasing. Cascaded models involve cascading theoretical expressions of the noise-power spectrum (NPS) through multiple stages. Most expressions involve two or three terms, requiring the manipulation of algebraic expressions consisting of hundreds of terms. This practical limitation is alleviated using MATLAB's Simulink programming environment and symbolic math manipulations. It is shown that even for an "indirect" detector, noise aliasing reduces the DQE by up to 50% at the cut-off frequency. Secondary quantum noise is generally a small effect, but reabsorption can reduce the DQE by 20-25% over a wide range of spatial frequencies.