Spatio-energetic cross talk in photon counting detectors: Detector model and correlated Poisson data generator

• Published in: Medical physics (Lancaster) 2016-12, Vol.43 (12), p.6386-6404
• Main Authors: Taguchi, Katsuyuki, Polster, Christoph, Lee, Okkyun, Stierstorfer, Karl, Kappler, Steffen
• Format: Article
• Language: English
• Subjects: Biological material, e.g. blood, urine; Haemocytometers; Computed tomography; Computer modeling; Computerised tomographs; computerised tomography; correlation; counters; cross talk; double‐counting; Fluorescence; Fluorescence spectra; Measurement of nuclear or x‐radiation; Models, Theoretical; Monte Carlo methods; Monte Carlo simulations; photoelectricity; photon counting; Photons; Poisson Distribution; Poisson's equation; random number generation; Random or pseudo‐random number generators; Rayleigh scattering; spectral distortion; spectral response; Spectrum Analysis; Tubes for determining the presence, intensity, density or energy of radiation or particles; X‐ray detectors; X‐ray effects; X‐ray emission spectra; X‐ray spectra
• ISSN: 0094-2405; 2473-4209
• DOI: 10.1118/1.4966699

Purpose: An x-ray photon interacts with photon counting detectors (PCDs) and generates an electron charge cloud or multiple clouds. The clouds (thus, the photon energy) may be split between two adjacent PCD pixels when the interaction occurs near pixel boundaries, producing a count at both of the pixels. This is called double-counting with charge sharing. (A photoelectric effect with K-shell fluorescence x-ray emission would result in double-counting as well). As a result, PCD data are spatially and energetically correlated, although the output of individual PCD pixels is Poisson distributed. Major problems include the lack of a detector noise model for the spatio-energetic cross talk and lack of a computationally efficient simulation tool for generating correlated Poisson data. A Monte Carlo (MC) simulation can accurately simulate these phenomena and produce noisy data; however, it is not computationally efficient. Methods: In this study, the authors developed a new detector model and implemented it in an efficient software simulator that uses a Poisson random number generator to produce correlated noisy integer counts. The detector model takes the following effects into account: (1) detection efficiency; (2) incomplete charge collection and ballistic effect; (3) interaction with PCDs via photoelectric effect (with or without K-shell fluorescence x-ray emission, which may escape from the PCDs or be reabsorbed); and (4) electronic noise. The correlation was modeled by using these two simplifying assumptions: energy conservation and mutual exclusiveness. The mutual exclusiveness is that no more than two pixels measure energy from one photon. The effect of model parameters has been studied and results were compared with MC simulations. The agreement, with respect to the spectrum, was evaluated using the reduced χ 2 statistics or a weighted sum of squared errors, χ red 2 ( ≥ 1 ) , where χ red 2 = 1 indicates a perfect fit. Results: The model produced spectra with flat field irradiation that qualitatively agree with previous studies. The spectra generated with different model and geometry parameters allowed for understanding the effect of the parameters on the spectrum and the correlation of data. The agreement between the model and MC data was very strong. The mean spectra with 90 keV and 140 kVp agreed exceptionally well: χ red 2 values were 1.049 with 90 keV data and 1.007 with 140 kVp data. The degrees of cross talk (in terms of the relative increase from