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Register a new userX-ray dark-field signal reduction due to hardening of the visibility spectrum
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X-ray dark-field imaging enables a spatially-resolved visualization of small-angle X-ray scattering. Using phantom measurements, we demonstrate that a materials effective dark-field signal may be reduced by modification of the visibility spectrum by other dark-field-active objects in the beam. This is the dark-field equivalent of conventional beam-hardening, and is distinct from related, known effects, where the dark-field signal is modified by attenuation or phase shifts. We present a theoretical model for this group of effects and verify it by comparison to the measurements. These findings have significant implications for the interpretation of dark-field signal strength in polychromatic measurements.
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Due to the energy-dependent nature of the attenuation coefficient and the polychromaticity of the X-ray source, beam hardening effect occurs when X-ray photons penetrate through an object, causing a nonlinear projection data. When a linear reconstruction algorithm, such as filtered backprojection, is applied to reconstruct the projection data, beam hardening artifacts which show as cupping and streaks are present in the CT image. The aim of this study was to develop a fast and accurate beam hardening correction method which can deal with beam hardening artifacts induced by multi-materials objects. Based on spectrum estimation, the nonlinear attenuation process of the X-ray projection was modeled by reprojecting a template image with the estimated polychromatic spectrum. The template images were obtained by segmenting the uncorrected into different components using a simple segmentation algorithm. Numerical simulations, experimental phantom data and animal data which were acquired on a modern diagnostic CT scanner (Discovery CT750 HD, GE Healthcare, WI, USA) and a modern C-Arm CT scanner (Artis Zee, Siemens Healthcare, Forchheim, Germany), respectively, were used to evaluate the proposed method. The results show the proposed method significantly reduced both cupping and streak artifacts, and successfully recovered the Hounsfield Units (HU) accuracy.
Fluorine-19 (19F) MRI of injected perfluorocarbon emulsions (PFCs) allows for the non-invasive quantification of inflammation and cell tracking, but suffers from a low signal-to-noise ratio and extended scan time. To address this limitation, we tested the hypothesis that a 19F MRI pulse sequence that combines a specific undersampling regime with signal averaging has increased sensitivity and robustness against motion artifacts compared to a non-averaged fully-sampled dataset, when both are reconstructed with compressed sensing. To this end, numerical simulations and phantom experiments were performed to characterize the point spread function (PSF) of undersampling patterns and the vulnerability to noise of acquisition-reconstruction strategies with paired numbers of x signal averages and acceleration factor x (NAx-AFx). At all investigated noise levels, the DSC of the acquisition-reconstruction strategies strongly depended on the regularization parameters and acceleration factor. In phantoms, motion robustness of an NA8-AF8 undersampling pattern versus NA1-AF1 was evaluated with simulated and real motions. Differences were assessed with Dice similarity coefficients (DSC), and were consistently higher for NA8-AF8 compared to NA1-AF1 strategy, for both simulated and real cyclic motions (P<0.001). Both acquisition-reconstruction strategies were validated in vivo in mice (n=2) injected with perfluoropolyether. These images displayed a sharper delineation of the liver with the NA8-AF8 strategy than with the NA1-AF1 strategy. In conclusion, we validated the hypothesis that in 19F MRI, the combination of undersampling and averaging improves both the sensitivity and the robustness against motion artifacts compared to a non-averaged fully-sampled dataset, when both are reconstructed with compressed sensing.
Crystal defects play a large role in how materials respond to their surroundings, yet there are many uncertainties in how extended defects form, move, and interact deep beneath a materials surface. A newly developed imaging diagnostic, dark-field X-ray microscopy (DFXM) can now visualize the behavior of line defects, known as dislocations, in materials under varying conditions. DFXM images visualize dislocations by imaging the very subtle long-range distortions in the materials crystal lattice, which produce a characteristic adjoined pair of bright and dark regions. Full analysis of how these dislocations evolve can be used to refine material models, however, it requires quantitative characterization of the statistics of their shape, position and motion. In this paper, we present a semi-automated approach to effectively isolate, track, and quantify the behavior of dislocations as composite objects. This analysis drives the statistical characterization of the defects, to include dislocation velocity and orientation in the crystal, for example, and is demonstrated on DFXM images measuring the evolution of defects at 98$%$ of the melting temperature for single-crystal aluminum, collected at the European Synchrotron Radiation Facility.
Knowledge of x-ray attenuation is essential for developing and evaluating x-ray imaging technologies. For instance, techniques to distinguish between cysts and solid tumours at mammography screening would be highly desirable to reduce recalls, but the development requires knowledge of the x-ray attenuation for cysts and tumours. We have previously measured the attenuation of cyst fluid using photon-counting spectral mammography. Data on x-ray attenuation for solid breast lesions are available in the literature, but cover a relatively wide range, likely caused by natural spread between samples, random measurement errors, and different experimental conditions. In this study, we have adapted the previously developed spectral method to measure the linear attenuation of solid breast lesions. A total of 56 malignant and 5 benign lesions were included in the study. The samples were placed in a holder that allowed for thickness measurement. Spectral (energy-resolved) images of the samples were acquired and the image signal was mapped to equivalent thicknesses of two known reference materials, which can be used to derive the x-ray attenuation as a function of energy. The spread in equivalent material thicknesses was relatively large between samples, which is likely to be caused mainly by natural variation and only to a minor extent by random measurement errors and sample inhomogeneity. No significant difference in attenuation was found between benign and malignant solid lesions, or between different types of malignant lesions. The separation between cyst-fluid and tumour attenuation was, however, significant, which suggests it may be possible to distinguish cystic from solid breast lesions, and the results lay the groundwork for a clinical trial. [cropped]
Phase-contrast X-ray imaging can improve the visibility of weakly absorbing objects (e.g. soft tissues) by an order of magnitude or more compared to conventional radiographs. Previously, it has been shown that combining phase retrieval with computed tomography (CT) can increase the signal-to-noise ratio (SNR) by up to two orders of magnitude over conventional CT at the same radiation dose, without loss of image quality. Our experiments reveal that as radiation dose decreases, the relative improvement in SNR increases. We discovered this enhancement can be traded for a reduction in dose greater than the square of the gain in SNR. Upon reducing the dose 300 fold, the phase-retrieved SNR was still almost 10 times larger than the absorption contrast data. This reveals the potential for dose reduction factors in the tens of thousands without loss in image quality, which would have a profound impact on medical and industrial imaging applications.
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