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.

In this work, different Cadmium Telluride (CdTe) sensor configurations are assessed for the usage in a robot assisted portable gamma camera. In the first part, four CdTe sensors, with thickness of 0.45 mm, 1 mm, 2 mm and 3 mm and pixel sizes of 55 μm and 110 μm, are investigated regarding their spectroscopic performance. The photon counting detector Timepix1 is hereby used. The 3 mm CdTe sensor shows increase in count rate up to a factor of 1.25 compared to a 2 mm CdTe sensor, 1.84 compared to a 1 mm CdTe sensor and up to 2.71 compared to a 0.45 mm CdTe sensor in the case of ¹³⁷Cs. In the second part, the 3 mm CdTe sensor was implemented in a commercially available gamma camera, the iPIX. The system was integrated in the bomb disposal robot and tested in different scenarios. The integrated 3 mm CdTe detector measured 21.5 counts per second emitting from a ⁶⁰Co source with an activity of 2.8 ± 0.07 Gbq in 20 meters distance in an open environment. The acquisition time was 116 seconds. The angular resolution was sufficient for the user to localize the radioactive isotope inside the test structure.

This paper presents our approach for a remotely operated robot-based system to perform analysis tasks of suspicious objects such as luggage, trash cans, and similar items with regards to potential terroristic attacks using C(B)R(N)E (chemical, biological, radioactive, nuclear and explosive) substances in public spaces. To reduce the exposure risk for security forces, an existing robot-based system was equipped with a range of sensors including a high-resolution 3D-RGB scanner, gamma and chemical sensors, additional cameras, and positioning sensors. A flexible and modular sensor framework has been designed and implemented that supports efficient integration of multiple sensors of different kinds. The sensor framework is easily extendable and independent of the sensors, so that new components can be integrated with little effort. Data of all sensors is securely transferred to a base processing unit for fusion and processing. A high-resolution 3D model of the surroundings is enriched by the acquired data of all sensors and visualized to improve the situational awareness during mission operation by better perception of the remote situation.