Signal and noise transfer in spatiotemporal quantum-based imaging systems

Abstract

Fourier-based transfer theory is extended into the temporal domain to describe both spatial and temporal noise processes in quantum-based medical imaging systems. Lag is represented as a temporal scatter in which the release of image quanta is delayed according to a probability density function. Expressions describing transfer of the spatiotemporal Wiener noise power spectrum through quantum gain and scatter processes are derived. Lag introduces noise correlations in the temporal domain in proportion to the correlated noise component only. The effect of lag is therefore dependent on both spatial and temporal physical processes. A simple model of a fluoroscopic system shows that image noise is reduced by a factor that is similar to Wagner's information bandwidth integral, which depends on the temporal modulation transfer function.

Cascaded‐systems analyses and the detective quantum efficiency of single‐Z x‐ray detectors including photoelectric, coherent and incoherent interactions

“…The resulting new signal and noise transfer relationships are developed in the Appendix using stochastic point-process theory. 15,21,30 The mean number of generated secondaries is given by…”

Normalization of the modulation transfer function: The open‐field approach

“…In the context of standardized DQE-measurement protocols and comparisons, it is important that these potential errors be well understood. In addition, metrics that depend on the MTF-squared integral ͑such as Wagner's bandwidth integral 19,20 or recent work on temporal MTF properties of fluoroscopic systems [21][22][23][24] ͒ are very sensitive to systematic biases and normalization errors in the MTF.…”

The detective quantum efficiency of photon‐counting x‐ray detectors using cascaded‐systems analyses

“…Over the past several years, a cascaded-systems approach has been developed to describe how these considerations affect the DQE of conventional energy-integrating detectors. By propagating metrics of signal and noise through a cascade of fundamental image-forming processes [21][22][23][24][25][26][27][28] the DQE (Ref. 29) of a complex cascade is given by 30…”