Speaker
Description
In this work, we present a novel energy-dispersive X-ray Fluorescence Computed Tomography (ED-XFCT)
system based on a Micro-Pattern Gaseous Detector (MPGD), exploring its potential as a flexible and cost-effective
alternative for 3D energy-resolved imaging.
The system integrates an X-ray tube source, a motorized rotation stage, and a 2D-THCOBRA detector operating
in single-photon counting mode.
The 2D-THCOBRA [1] detector is one of the concepts of Micro-Pattern Gaseous Detectors (MPGDs) and is a
hole-type electron multiplier that combines GEM-like and MHSP-like amplification mechanisms within a single
structure. The THCOBRA consists of a perforated insulating substrate with metallic electrodes on both faces,
enabling a two-stage multiplication process: primary electron amplification occurs inside the holes, followed by a
secondary amplification and charge transfer along patterned electrodes on the anode side. Two-dimensional event
localization is achieved through a resistive charge division readout using orthogonal resistive lines, allowing eventby-
event position reconstruction.
This detector provides intrinsic energy and position sensitivity, with an energy resolution of ≈18% (FWHM)@5.9
keV and a spatial resolution of ≈1 mm. The detector operates in a sealed gaseous environment using pure argon and
Ar–Xe mixtures (up to 5% Xe).
Tomographic data acquisition is performed over a full 360° rotation using a 9° angular step, enabling the
reconstruction of element-selective projection datasets. Image reconstruction is carried out using the TIGRE
toolbox, combining filtered back-projection and iterative algorithms to obtain 2D sinograms and 3D elemental
distributions.
The system was experimentally validated using different samples including biological ones. The results will be
shown demonstrating the feasibility of the 2D-THCOBRA-based ED-XFCT system for resolving elemental
distributions of 3D samples.
This work establishes a proof-of-concept for MPGD-based XFCT and identifies key performance trade-offs,
supporting its further development toward scalable and cost-effective 3D elemental imaging platforms.
The present study was developed in the scope of the Project “Agenda ILLIANCE” [C644919832-00000035 | Project nº 46], financed by PRR – Plano de Recuperação e Resiliência under the Next Generation EU from the European Union. This work was partially financed from Project COMPETE2030-FEDER-00785100, funded through the COMPETE 2030 programme (Portugal 2030) and co-funded by the FEDER.