Element discrimination via spectroscopic X-ray imaging with a CdTe Medipix3RX detector

Abstract

A: X-ray imaging techniques that distinguish radiation in different energy ranges offer the advantage of material differentiation based on the material-specific properties of the object to be examined. One possibility to obtain spectroscopic information is the K-edge approach utilizing energy thresholds. A basic information about the photon energy is needed for this purpose. The Medipix3RX is a photon-counting semiconductor detector which provides multiple energy thresholds in a single recording and so an energy information. It offers up to eight independent energy thresholds per pixel with high spatial and high energy resolution. In order to investigate the possibility of material discrimination by X-ray imaging methods with Medipix3RX detectors, an absorption phantom was fabricated and examined which consists of 8 different materials in various thicknesses. For material separation the K-edge method was used, which exploits the abrupt rise of photo absorption for energies above the ionization energy of electrons in the atomic K-shell. After performing a threshold equalization and a threshold-energy calibration of the detector, X-ray images were taken of the phantom. After evaluation, five of the eight materials of the phantom were successfully separated and identified with the selected settings of the X-ray tube. These include gadolinium and iodine, which are used as contrast agents in oncology. The most reliable material discrimination was achieved for tungsten and gadolinium. Due to their high K-edge energy, they had the greatest influence on the spectrum used. Elements with a low atomic number, however, could be distinguished less confidently due to the low photo absorption in the energy spectrum used and the resulting low effect on the change of the measured total intensity. This article describes the experimental setup of the energy calibration and X-ray image analysis of a Medipix3RX detector with a 1 mm CdTe sensor as well as the performance and evaluation of these and shows first results in material identification with eight energy thresholds in spectroscopic single pixel mode configuration.

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