Study on dark-field imaging with a laboratory x-ray source: Random stress variation analysis based on x-ray grating interferometry

Pixel-wise beam-hardening correction for dark-field signal in X-ray dual-phase grating interferometry

The dark-field signal provided by X-ray grating interferometry is an invaluable tool for providing structural information beyond the direct spatial resolution and their variations on a macroscopic scale. However, when using a polychromatic source, the beam-hardening effect in the dark-field signal makes the quantitative sub-resolution structural information inaccessible. Especially, the beam-hardening effect in dual-phase grating interferometry varies with spatial location, inter-grating distance, and diffraction order. In this work, we propose a beam-hardening correction algorithm, taking into account all these factors. The accuracy and robustness of the algorithm are then validated by experimental results. This work contributes a necessary step toward accessing small-angle scattering structural information in dual-phase grating interferometry.

Precise wavefront characterization of x-ray optical elements using a laboratory source

Improvements in x-ray optics critically depend on the measurement of their optical performance. The knowledge of wavefront aberrations, for example, can be used to improve the fabrication of optical elements or to design phase correctors to compensate for these errors. At present, the characterization of such optics is made using intense x-ray sources, such as synchrotrons. However, the limited access to these facilities can substantially slow down the development process. Improvements in the brightness of lab-based x-ray micro-sources in combination with the development of new metrology methods, particularly ptychographic x-ray speckle tracking, enable characterization of x-ray optics in the lab with a precision and sensitivity not possible before. Here, we present a laboratory setup that utilizes a commercially available x-ray source and can be used to characterize different types of x-ray optics. The setup is used in our laboratory on a routine basis to characterize multilayer Laue lenses of high numerical aperture and other optical elements. This typically includes measurements of the wavefront distortions, optimum operating photon energy, and focal length of the lens. To check the sensitivity and accuracy of this laboratory setup, we compared the results to those obtained at the synchrotron and saw no significant difference. To illustrate the feedback of measurements on performance, we demonstrated the correction of the phase errors of a particular multilayer Laue lens using a 3D printed compound refractive phase plate.

Phase retrieval based on deep learning in grating interferometer

Grating interferometry is a promising technique to obtain differential phase contrast images with illumination source of low intrinsic transverse coherence. However, retrieving the phase contrast image from the differential phase contrast image is difficult due to the accumulated noise and artifacts from the differential phase contrast image (DPCI) reconstruction. In this paper, we implemented a deep learning-based phase retrieval method to suppress these artifacts. Conventional deep learning based denoising requires noise/clean image pair, but it is not feasible to obtain sufficient number of clean images for grating interferometry. In this paper, we apply a recently developed neural network called Noise2Noise (N2N) that uses noise/noise image pairs for training. We obtained many DPCIs through combination of phase stepping images, and these were used as input/target pairs for N2N training. The application of the N2N network to simulated and measured DPCI showed that the phase contrast images were retrieved with strongly suppressed phase retrieval artifacts. These results can be used in grating interferometer applications which uses phase stepping method.