Extension of x-ray imaging linear systems analysis to detectors with energy discrimination capability

On the influence of noise correlations in measurement data on basis image noise in dual-energylike x-ray imaging

In conventional dual-energy systems, two transmission measurements with distinct spectral characteristics are performed. These measurements are used to obtain the line integrals of two basis material densities. Usually, the measurement process is such that the two measured signals can be treated as independent and therefore uncorrelated. Recently, however, a readout system for x-ray detectors has been introduced for which this is no longer the case. The readout electronics is designed to obtain simultaneous measurements of the total number of photons N and the total energy E they deposit in the sensor material. Practically, this is realized by a signal replication and separate counting and integrating processing units. Since the quantities N and E are (electronically) derived from one and the same physical sensor signal, they are statistically correlated. Nevertheless, the pair N and E can be used to perform a dual-energy processing following the well-known approach by Alvarez and Macovski. Formally, this means that N is to be identified with the first dual-energy measurement M1 and E with the second measurement M2. In the presence of input correlations between M1 = N and M2 = E, however, the corresponding analytic expressions for the basis image noise have to be modified. The main observation made in this paper is that for positively correlated data, as is the case for the simultaneous counting and integrating device mentioned above, the basis image noise is suppressed through the influence of the covariance between the two signals. We extend the previously published relations for the basis image noise to the case where the original measurements are not independent and illustrate the importance of the input correlations by comparing dual-energy basis image noise resulting from the device mentioned above and a device measuring the photon numbers and the deposited energies consecutively.

Properties of preprocessed sinogram data in x-ray computed tomography

The accurate determination of x-ray signal properties is important to several computed tomography (CT) research and development areas, notably for statistical reconstruction algorithms and dose-reduction simulation. The most commonly used model of CT signal formation, assuming monoenergetic x-ray sources with quantum counting detectors obeying simple Poisson statistics, does not reflect the actual physics of CT acquisition. This paper describes a more accurate model, taking into account the energy-integrating detection process, nonuniform flux profiles, and data-conditioning processes. Methods are developed to experimentally measure and theoretically calculate statistical distributions, as well as techniques to analyze CT signal properties. Results indicate the limitations of current models and suggest improvements for the description of CT signal properties.