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The performance of a Talbot-Lau interferometer depends to a great extent on its visibility. This means, to obtain high quality phase-contrast and dark-field images a high visibility is mandatory. Several parameters influence the visibility of such a system, like for example the x-ray spectrum, the inter-grating distances or the parameters of the three gratings. In this multidimensional space, wave field simulations help to find the optimal combination of the grating specifications to construct a setup with a high visibility while retaining a fixed angular sensitivity. In this work we specifically analyzed the influence of the G1 grating duty cycle in simulations and experiments. We show that there is a lot of room for improvement by varying the duty cycle of the phase-shifting grating G1. As a result, by employing a third-integer duty cycle we can increase the visibility to up to 53 % in a laboratory setup with a polychromatic spectrum. The achieved visibility is more than two times higher compared to the result with a standard-type setup. This visibility gain allows a dose reduction by a factor of 5 preserving the same image quality.

The dark-field image obtained in grating-based x-ray phase-contrast imaging can provide information about the objects' microstructures on a scale smaller than the pixel size even with low geometric magnification. In this publication we demonstrate that the dark-field image quality can be enhanced with an energy-resolving pixel detector. Energy-resolved x-ray dark-field images were acquired with a 16-energy-channel photon-counting pixel detector with a 1 mm thick CdTe sensor in a Talbot-Lau x-ray interferometer. A method for contrast-noise-ratio (CNR) enhancement is proposed and validated experimentally. In measurements, a CNR improvement by a factor of 1.14 was obtained. This is equivalent to a possible radiation dose reduction of 23%.

A simulation framework for coherent X-ray imaging, based on scalar diffraction theory, is presented. It contains a core C++ library and an additional Python interface. A workflow is presented to include contributions of inelastic scattering obtained with Monte-Carlo methods. X-ray Talbot-Lau interferometry is the primary focus of the framework. Simulations are in agreement with measurements obtained with such an interferometer. Especially, the dark-field signal of densely packed PMMA microspheres is predicted. A realistic modeling of the microsphere distribution, which is necessary for correct results, is presented. The framework can be used for both setup design and optimization but also to test and improve reconstruction methods.

During the last decades, multi-pixel detectors have been developed capable of registering single photons. The newly developed hybrid photon detector camera has a remarkable property that it has not only spatial but also temporal resolution. In this work, we apply this device to the detection of non-classical light from spontaneous parametric down-conversion and use two-photon correlations for the absolute calibration of its quantum efficiency.

We have carried out grating-based x-ray differential phase-contrast measurements with a hybrid pixel detector in 16 energy channels simultaneously. A method for combining the energy resolved phase-contrast images based on energy weighting is presented. An improvement in contrast-to-noise ratio by 58.2% with respect to an emulated integrating detector could be observed in the final image. The same image quality could thus be achieved with this detector and with energy weighting at 60.0% reduced dose compared to an integrating detector. The benefit of the method depends on the object, spectrum, interferometer design and the detector efficiency.

Over the recent years X-ray differential phase-contrast imaging was developed for the hard X-ray regime as produced from laboratory X-ray sources. The technique uses a grating-based Talbot-Lau interferometer and was shown to yield image contrast gain, which makes it very interesting to the fields of medical imaging and non-destructive testing, respectively. In addition to X-ray attenuation contrast, the differential phase-contrast and dark-field images provide different structural information about a specimen. For the dark-field even at length scales much smaller than the spatial resolution of the imaging system. Physical interpretation of the dark-field information as present in radiographic and tomographic (CT) images requires a detailed look onto the geometric orientation between specimen and the setup. During phase-stepping the drop in intensity modulation, due to local scattering effects within the specimen is reproduced in the dark-field signal. This signal shows strong dependencies on micro-porosity and micro-fibers if these are numerous enough in the object. Since a grating-interferometer using a common unidirectional line grating is sensitive to X-ray scattering in one plane only, the dark-field image is influenced by the fiber orientations with respect to the grating bars, which can be exploited to obtain anisotropic structural information. With this contribution, we attempt to extend existing models for 2D projections to 3D data by analyzing dark-field contrast tomography of anisotropically structured materials such as carbon fiber reinforced carbon (CFRC).

A novel information retrieval algorithm for X-ray grating-based phase-contrast imaging based on the deconvolution of the object and the reference phase stepping curve (PSC) as proposed by Modregger et al. was investigated in this paper. We applied the method for the first time on data obtained with a polychromatic spectrum and compared the results to those, received by applying the commonly used method, based on a Fourier analysis. We confirmed the expectation, that both methods deliver the same results for the absorption and the differential phase image. For the darkfield image, a mean contrast-to-noise ratio (CNR) increase by a factor of 1.17 using the new method was found. Furthermore, the dose saving potential was estimated for the deconvolution method experimentally. It is found, that for the conventional method a dose which is higher by a factor of 1.66 is needed to obtain a similar CNR value compared to the novel method. A further analysis of the data revealed, that the improvement in CNR and dose efficiency is due to the superior background noise properties of the deconvolution method, but at the cost of comparability between measurements at different applied dose values, as the mean value becomes dependent on the photon statistics used.