Tomographic phase and attenuation extraction for a sample composed of unknown materials using x-ray propagation-based phase-contrast imaging

Robust quantitative X-ray phase diagnostic for carbon composite characterisation in the context of lightning induced risk

Getting complementary physical information from a single image acquisition is particularly valuable for materials analysis. Grating based X-ray Phase Contrast Imaging (XPCI) methods allow decoupling attenuation, phase and scattering information. However, the phase and scattering extraction processes can easily suffer from artefacts, which is detrimental to implement this imaging technique in societal applications. In this paper, we demonstrate that grating based XPCI can provide a robust phase measurement in complex materials such as damaged composites. The technique allows the phase to be analysed using a self-assessment method that first identifies the artefacts from the imaging setup, and then can be used as an indicator to interpret the signal from a material. We focus on carbon fibre reinforced polymers which we subjected to laboratory-controlled lightning strikes. We evidence that the combined information from phase and attenuation allow identifying the type of defect induced by the lightning current. The phase information is converted into relative mass density variation within the sample and depicts areas with a loss in density up to 40%. We ensure that these results are valid by comparing them with an X-ray attenuation contrast tomographic reconstruction.

Phase-contrast neutron imaging compared with wave propagation and McStas simulations

Propagation-based phase contrast, for example in the form of edge enhancement contrast, is well established within X-ray imaging but is not widely used in neutron imaging. This technique can help increase the contrast of low-attenuation samples but may confuse quantitative absorption measurements. Therefore, it is important to understand the experimental parameters that cause and amplify or dampen this effect in order to optimize future experiments properly. Two simulation approaches have been investigated, a wave-based simulation and a particle-based simulation conducted in McStas [Willendrup & Lefmann (2020). J. Neutron Res. 22, 1-16], and they are compared with experimental data. The experiment was done on a sample of metal foils with weakly and strongly neutron absorbing layers, which were measured while varying the rotation angle and propagation distance from the sample. The experimental data show multiple signals: attenuation, phase contrast and reflection. The wave model reproduces the sample attenuation and the phase peaks but it does not reproduce the behavior of these peaks as a function of rotation angle. The McStas simulation agrees better with the experimental data, as it reproduces attenuation, phase peaks and reflection, as well as the change in these signals as a function of rotation angle and distance. This suggests that the McStas simulation approach, where the particle description of the neutron facilitates the incorporation of multiple effects, is the most convenient way of modeling edge enhancement in neutron imaging.

Framework to optimize fixed-length micro-CT systems for propagation-based phase-contrast imaging

A laboratory X-ray imaging system with a setup that closely resembles commercial micro-CT systems with a fixed source-to-detector distance of ∼90 cm is investigated for single distance propagation-based phase-contrast imaging and computed tomography (CT). The system had a constant source-to-detector distance, and the sample positions were optimized. Initially, a PTFE wire was imaged, both in 2D and 3D, to characterize fringe contrast and spatial resolution for different X-ray source settings and source-to-sample distances. The results were compared to calculated values based on theoretical models and to simulated (wave-optics based) results, with good agreement being found. The optimization of the imaging system is discussed. CT scans of two biological samples, a tissue-engineered esophageal scaffold and a rat heart, were then acquired at the optimum parameters, demonstrating that significant image quality improvements can be obtained with widely available components placed inside fixed-length cabinets through proper optimization of propagation-based phase-contrast.

Polychromatic neutron phase-contrast imaging of weakly absorbing samples enabled by phase retrieval

The use of a phase-retrieval technique for propagation-based phase-contrast neutron imaging with a polychromatic beam is demonstrated. This enables imaging of samples with low absorption contrast and/or improving the signal-to-noise ratio to facilitate e.g. time-resolved measurements. A metal sample, designed to be close to a phase pure object, and a bone sample with canals partially filled with D2O were used for demonstrating the technique. These samples were imaged with a polychromatic neutron beam followed by phase retrieval. For both samples the signal-to-noise ratios were significantly improved and, in the case of the bone sample, the phase retrieval allowed for separation of bone and D2O, which is important for example for in situ flow experiments. The use of deuteration contrast avoids the use of chemical contrast enhancement and makes neutron imaging an interesting complementary method to X-ray imaging of bone.

Nonlinear primal-dual algorithm for the phase and absorption retrieval from a single phase contrast image

We propose a nonlinear primal-dual algorithm for the retrieval of phase shift and absorption from a single x ray in-line phase contrast, or Fresnel diffraction, image. The algorithm permits us to regularize phase and absorption separately. We demonstrate that taking into account the nonlinearity in the reconstruction improves reconstruction compared with linear methods. We also demonstrate that choosing different regularizers for absorption and phase can improve the reconstructions. The use of the total variation and its generalization in a primal-dual approach allows us to exploit the sparsity of the investigated sample. On both simulated and real datasets, the proposed nonlinear primal-dual hybrid gradient (NL-PDHG) method yields reconstructions with considerably fewer artifacts and improved the normalized mean squared error compared with its linearized version.