9 research outputs found

    Generating spectral dental panoramic images from single energy computed tomography volumes

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    Purpose: To implement a framework generating synthetic spectral panoramic images from single energy CT volumes. Using the framework output to compare the synthetic images against experimental spectral panoramic images for cross-verification. Methods: A simulation framework for generating synthetic spectral panoramic images from CT volumes is described. A cone beam CT scan of an anthropomorphic head phantom is used as input. An experimental spectral panoramic image of the same phantom is acquired. Results: The output of the framework of an anthropomorphic head phantom is compared against an experimental spectral panoramic image of the same phantom. The synthetic and experimental spectral panoramic images resemble each other considerably, especially the bone features. In the soft tissue images, there are some deviations, which are a result of the differences between the experimental and synthetic processing pipelines. Conclusions: It is demonstrated that generating synthetic spectral panoramic images from single energy CT volumes is possible. The synthetic images have many similarities with the experimental results, increasing the confidence in the correctness of the information contained within experimental spectral panoramic images and indicating that the synthetic images could be useful in further research

    Spectral X-ray dark-field signal characterization from dual-energy projection phase-stepping data with a Talbot-Lau interferometer

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    Abstract Material-selective analysis of spectral X-ray imaging data requires prior knowledge of the energy dependence of the observed signal. Contrary to conventional X-ray imaging, where the material-specific attenuation coefficient is usually precisely known, the linear diffusion coefficient of the X-ray dark-field contrast does not only depend on the material and its microstructure, but also on the setup geometry and is difficult to access. Here, we present an optimization approach to retrieve the energy dependence of the X-ray dark-field signal quantitatively on the example of closed-cell foams from projection data without the need for additional hardware to a standard grating-based X-ray dark-field imaging setup. A model for the visibility is used to determine the linear diffusion coefficient with a least-squares optimization. The comparison of the results to spectrometer measurements of the linear diffusion coefficient suggests the proposed method to provide a good estimate for the energydependent dark-field signal

    Quantitative dual-energy micro-CT with a photon-counting detector for material science and non-destructive testing.

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    The recent progress in photon-counting detector technology using high-Z semiconductor sensors provides new possibilities for spectral x-ray imaging. The benefits of the approach to extract spectral information directly from measurements in the projection domain are very advantageous for material science studies with x-rays as polychromatic artifacts like beam-hardening are handled properly. Since related methods require accurate knowledge of all energy-dependent system parameters, we utilize an adapted semi-empirical model, which relies on a simple calibration procedure. The method enables a projection-based decomposition of photon-counting raw-data into basis material projections. The objective of this paper is to investigate the method's performance applied to x-ray micro-CT with special focus on applications in material science and non-destructive testing. Projection-based dual-energy micro-CT is shown to be of good quantitative accuracy regarding material properties such as electron densities and effective atomic numbers. Furthermore, we show that the proposed approach strongly reduces beam-hardening artifacts and improves image contrast at constant measurement time

    Contrast-enhanced spectral mammography with a compact synchrotron source.

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    For early breast cancer detection, mammography is nowadays the commonly used standard imaging approach, offering a valuable clinical tool for visualization of suspicious findings like microcalcifications and tumors within the breast. However, due to the superposition of anatomical structures, the sensitivity of mammography screening is limited. Within the last couple of years, the implementation of contrast-enhanced spectral mammography (CESM) based on K-edge subtraction (KES) imaging helped to improve the identification and classification of uncertain findings. In this study, we introduce another approach for CESM based on a two-material decomposition, with which we expect fundamental improvements compared to the clinical procedure. We demonstrate the potential of our proposed method using the quasi-monochromatic radiation of a compact synchrotron source-the Munich Compact Light Source (MuCLS)-and a modified mammographic accreditation phantom. For direct comparison with the clinical CESM approach, we also performed a standard dual-energy KES at the MuCLS, which outperformed the clinical CESM images in terms of contrast-to-noise ratio (CNR) and spatial resolution. However, the dual-energy-based two-material decomposition approach achieved even higher CNR values. Our experimental results with quasi-monochromatic radiation show a significant improvement of the image quality at lower mean glandular dose (MGD) than the clinical CESM. At the same time, our study indicates the great potential for the material-decomposition instead of clinically used KES to improve the quantitative outcome of CESM

    Dual-energy CT: a phantom comparison of different platforms for abdominal imaging

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    Evaluation of imaging performance across dual-energy CT (DECT) platforms, including dual-layer CT (DLCT), rapid-kVp-switching CT (KVSCT) and dual-source CT (DSCT). A semi-anthropomorphic abdomen phantom was imaged on these DECT systems. Scans were repeated three times for CTDIvol levels of 10 mGy, 20 mGy, 30 mGy and different fat-simulating extension rings. Over the available range of virtual-monoenergetic images (VMI), noise as well as quantitative accuracy of hounsfield units (HU) and iodine concentrations were evaluated. For all VMI levels, HU values could be determined with high accuracy compared to theoretical values. For KVSCT and DSCT, a noise increase was observed towards lower VMI levels. A patient-size dependent increase in the uncertainty of quantitative iodine concentrations is observed for all platforms. For a medium patient size the iodine concentration root-mean-square deviation at 20 mGy is 0.17 mg/ml (DLCT), 0.30 mg/ml (KVSCT) and 0.77mg/ml (DSCT). Noticeable performance differences are observed between investigated DECT systems. Iodine concentrations and VMI HUs are accurately determined across all DECT systems. KVSCT and DLCT deliver slightly more accurate iodine concentration values than DSCT for investigated scenarios. In DLCT, low-noise and high-image contrast at low VMI levels may help to increase diagnostic information in abdominal CT. Current dual-energy CT platforms provide accurate, reliable quantitative information. Dual-energy CT cross-platform evaluation revealed noticeable performance differences between different systems. Dual-layer CT offers constant noise levels over the complete energy range
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