Materials Separation via the Matrix Method Employing Energy-Discriminating X-ray Detection

The majority of lab-based X-ray sources are polychromatic and are not easily tunable, which can make the 3D quantitative analysis of multi-component samples challenging. The lack of effective materials separation when using conventional X-ray tube sources has motivated the development of a number of potential solutions including the application of dual-energy X-ray computed tomography (CT) as well as the use of X-ray filters. Here, we demonstrate the simultaneous decomposition of two low-density materials via inversion of the linear attenuation matrices using data from the energy-discriminating PiXirad detector. A key application for this method is soft-tissue differentiation which is widely used in biological and medical imaging. We assess the effectiveness of this approach using both simulation and experiment noting that none of the materials investigated here incorporate any contrast enhancing agents. By exploiting the energy discriminating properties of the detector, narrow energy bands are created resulting in multiple quasi-monochromatic images being formed using a broadband polychromatic source. Optimization of the key parameters for materials separation is first demonstrated in simulation followed by experimental validation using a phantom test sample in 2D and a small-animal model in 3D.