Multidimensional Data Processing Methods for Material Discrimination Using an Ideal X-Ray Spectrometric Photon Counting Detector

摘要

Pixelated X-ray CdTe/CZT detectors have been adapted to improve counting abilities, photon energy discrimination, and energy resolution for fast digital imaging solutions, in particular through work performed at LETI. This study aims to quantify how photon counting technologies associated with new data processing methods can enhance recognition of material by radiography for homeland security applications. An ideal spectrometric detector was initially simulated and its ability to identify millimetric thicknesses of three homogeneous plastics with similar chemical properties was investigated. Data processing methods presented in this study provide spectral data condensed into a set of $N$ coefficients, where $N$ is user-adjustable. The performance of counting technology was compared to that of an ideal pixelated integrating detector with scintillator architecture. Counting detectors, with data condensed into two coefficients $(N=2)$ improve identification by over 50% compared to integrating detectors. Increasing the number of coefficients enhances material identification further. Using $N=90$ (one coefficient per channel of 1 keV width) ensures a gain of 80% relative to scintillator performances. The effect of a realistic response function of the detector on identification was also analyzed in simulations.