Grating-based differential phase-contrast imaging has proven to be feasible with conventional X-ray sources. The polychromatic spectrum generally limits the performance of the interferometer but benefit can be gained with an energy-sensitive detector. In the presented work, we employ the energy-discrimination capability to correct for phase-wrapping artefacts. We propose to use the phase shifts, which are measured in distinct energy bins, to estimate the optimal phase shift in the sense of maximum likelihood. We demonstrate that our method is able to correct for phase-wrapping artefacts, to improve the contrast-to-noise ratio and to reduce beam hardening due to the modelled energy dependency. The method is evaluated on experimental data which are measured with a laboratory Talbot-Lau interferometer equipped with a conventional polychromatic X-ray source and an energy-sensitive photon-counting pixel detector. Our work shows, that spectral imaging is an important step to move differential phase-contrast imaging closer to pre-clinical and clinical applications, where phase wrapping is particularly problematic.
We present a spectral phase unwrapping approach for grating-based differential phase-contrast data where the unwrapped interferometer phase shift is estimated from energy discriminated measurements using maximum likelihood principles. We demonstrate the method on tomographic data sets of a test specimen taken at different x-ray energies using synchrotron radiation. The proposed unwrapping technique was demonstrated to successfully correct the data set for phase wrapping.
Recent advances in single-photon-counting detectors are enabling the development of novel approaches to reach micrometer-scale resolution in x-ray imaging. One example of such a technology are the MEDIPIX3RX-based detectors, such as the LAMBDA which can be operated with a small pixel size in combination with real-time on-chip charge-sharing correction. This characteristic results in a close to ideal, box-like point spread function which we made use of in this study. The proposed method is based on raster-scanning the sample with sub-pixel sized steps in front of the detector. Subsequently, a deconvolution algorithm is employed to compensate for blurring introduced by the overlap of pixels with a well defined point spread function during the raster-scanning. The presented approach utilizes standard laboratory x-ray equipment while we report resolutions close to 10 μm. The achieved resolution is shown to follow the relationship [Formula: see text] with the pixel-size p of the detector and the number of raster-scanning steps n.
X-ray computed tomography (CT) reconstruction suffers from beam-hardening artefacts caused by the polychromaticity of virtually all lab-based X-ray sources. A method to correct for beam-hardening is a direct, pixel-wise signal-to-thickness calibration (STC). We compare reconstructions of conventionally flat-field corrected as well as STC preprocessed measurements of various samples performed on a commercial microCT device based on a flat-panel detector. We show that a good estimate between the transmission signal and the respective material thickness can be given by multiple exponential functions. We further compare the exponential interpolation approach to a hyperbolic model, which reduces the number of necessary calibration measurements significantly. Our method shows that typical beam-hardening artefacts like cupping and filling can be almost completely suppressed and a significant contrast increase is gained. The method can be applied with little additional calibration and computation effort and allows shorter acquisition times since beam filtration can be reduced or omitted.
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