Improved visualization of X-ray phase contrast volumetric data through artifact-free integrated differential images

Artifacts arising when differential phase images are integrated is a common problem to several X-ray phase-based experimental techniques. The combination of noise and insufficient sampling of the high-frequency differential phase signal leads to the formation of streak artifacts in the projections, translating into poor image quality in the tomography slices. In this work, we apply a non-iterative integration algorithm proven to reduce streak artifacts in planar (2D) images to a differential phase tomography scan. We report on how the reduction of streak artifacts in the projections improves the quality of the tomography slices, especially in the directions different from the reconstruction plane. Importantly, the method is compatible with large tomography datasets in terms of computation time

A multi-layer edge-on single photon counting silicon microstrip detector for innovative techniques in diagnostic radiology

A three-layer detector prototype, obtained by stacking three edge-on single photon counting silicon microstrip detectors, has been developed and widely tested. This was done in the framework of the Synchrotron Radiation for Medical Physics/Frontier Radiology (SYRMEP/FRONTRAD) collaboration activities, whose aim is to improve the quality of mammographic examinations operating both on the source and on the detector side. The active surface of the device has been fully characterized making use of an edge-scanning technique and of a well-collimated laminar synchrotron radiation beam. The obtained data (interlayer distances, channel correspondence, etc.) have then been used to combine information coming from each detector layer, without causing any loss in spatial and contrast resolution of the device. Contrast and spatial resolution have also been separately evaluated for each detector layer. Moreover, imaging techniques (phase contrast, refraction, and scatter imaging), resulting in an increased visibility of low absorbing details, have been implemented, and their effectiveness has been tested on a biological sample. Finally, the possibility of simultaneously acquiring different kind of images with the different detector layers is discussed. This would result in maximizing the information extracted from the sample, while at the same time the high absorption efficiency of the detector device would allow a low dose delivery

Source detection using a 3D sparse representation: application to the Fermi gamma-ray space telescope

The multiscale variance stabilization Transform (MSVST) has recently been proposed for Poisson data denoising. This procedure, which is nonparametric, is based on thresholding wavelet coefficients. We present in this paper an extension of the MSVST to 3D data (in fact 2D-1D data) when the third dimension is not a spatial dimension, but the wavelength, the energy, or the time. We show that the MSVST can be used for detecting and characterizing astrophysical sources of high-energy gamma rays, using realistic simulated observations with the Large Area Telescope (LAT). The LAT was launched in June 2008 on the Fermi Gamma-ray Space Telescope mission. The MSVST algorithm is very fast relative to traditional likelihood model fitting, and permits efficient detection across the time dimension and immediate estimation of spectral properties. Astrophysical sources of gamma rays, especially active galaxies, are typically quite variable, and our current work may lead to a reliable method to quickly characterize the flaring properties of newly-detected sources.Comment: Accepted. Full paper will figures available at http://jstarck.free.fr/aa08_msvst.pd

Dynamic Multicontrast X-Ray Imaging Method Applied to Additive Manufacturing

We present a dynamic implementation of the beam-tracking x-ray imaging method providing absorption, phase, and ultrasmall angle scattering signals with microscopic resolution and high frame rate. We demonstrate the method’s ability to capture dynamic processes with 22-ms time resolution by investigating the melting of metals in laser additive manufacturing, which has so far been limited to single-modality synchrotron radiography. The simultaneous availability of three contrast channels enables earlier segmentation of droplets, tracking of powder dynamic, and estimation of unfused powder amounts, demonstrating that the method can provide additional information on melting processes

Monochromatic Propagation-Based Phase-Contrast Microscale Computed-Tomography System with a Rotating-Anode Source

We present an experimental setup for monochromatic propagation-based x-ray phase-contrast imaging based on a conventional rotating-copper-anode source, capable of an integrated flux up to 108 photons/s at 8 keV. In our study, the system is characterized in terms of spatial coherence, resolution, contrast sensitivity, and stability. Its quantitativeness is demonstrated by comparing theoretical predictions with experimental data on simple wire phantoms both in planar and computerized-tomography-scan geometries. Application to two biological samples of medical interest shows the potential for bioimaging on the millimeter scale with spatial resolution of the order of 10 \u3bcm and contrast resolution below 1%. All the scans are performed within laboratory-compatible exposure times, from 10 min to a few hours, and trade-offs between scan time and image quality are discussed

Mindfulness-based interventions for young offenders: a scoping review

Youth offending is a problem worldwide. Young people in the criminal justice system have frequently experienced adverse childhood circumstances, mental health problems, difficulties regulating emotions and poor quality of life. Mindfulness-based interventions can help people manage problems resulting from these experiences, but their usefulness for youth offending populations is not clear. This review evaluated existing evidence for mindfulness-based interventions among such populations. To be included, each study used an intervention with at least one of the three core components of mindfulness-based stress reduction (breath awareness, body awareness, mindful movement) that was delivered to young people in prison or community rehabilitation programs. No restrictions were placed on methods used. Thirteen studies were included: three randomized controlled trials, one controlled trial, three pre-post study designs, three mixed-methods approaches and three qualitative studies. Pooled numbers (n = 842) comprised 99% males aged between 14 and 23. Interventions varied so it was not possible to identify an optimal approach in terms of content, dose or intensity. Studies found some improvement in various measures of mental health, self-regulation, problematic behaviour, substance use, quality of life and criminal propensity. In those studies measuring mindfulness, changes did not reach statistical significance. Qualitative studies reported participants feeling less stressed, better able to concentrate, manage emotions and behaviour, improved social skills and that the interventions were acceptable. Generally low study quality limits the generalizability of these findings. Greater clarity on intervention components and robust mixed-methods evaluation would improve clarity of reporting and better guide future youth offending prevention programs

Applying the ROBINS-I tool to natural experiments: an example from public health

Background: A new tool to assess Risk of Bias In Non-randomised Studies of Interventions (ROBINS-I) was published in Autumn 2016. ROBINS-I uses the Cochrane-approved risk of bias (RoB) approach and focusses on internal validity. As such, ROBINS-I represents an important development for those conducting systematic reviews which include non-randomised studies (NRS), including public health researchers. We aimed to establish the applicability of ROBINS-I using a group of NRS which have evaluated non-clinical public health natural experiments. Methods: Five researchers, all experienced in critical appraisal of non-randomised studies, used ROBINS-I to independently assess risk of bias in five studies which had assessed the health impacts of a domestic energy efficiency intervention. ROBINS-I assessments for each study were entered into a database and checked for consensus across the group. Group discussions were used to identify reasons underpinning lack of consensus for specific questions and bias domains. Results: ROBINS-I helped to systematically articulate sources of bias in NRS. However, the lack of consensus in assessments for all seven bias domains raised questions about ROBINS-I’s reliability and applicability for natural experiment studies. The two RoB domains with least consensus were selection (Domain 2) and performance (Domain 4). Underlying the lack of consensus were difficulties in applying an intention to treat or per protocol effect of interest to the studies. This was linked to difficulties in determining whether the intervention status was classified retrospectively at follow-up, i.e. post hoc. The overall risk of bias ranged from moderate to critical; this was most closely linked to the assessment of confounders. Conclusion: The ROBINS-I tool is a conceptually rigorous tool which focusses on risk of bias due to the counterfactual. Difficulties in applying ROBINS-I may be due to poor design and reporting of evaluations of natural experiments. While the quality of reporting may improve in the future, improved guidance on applying ROBINS-I is needed to enable existing evidence from natural experiments to be assessed appropriately and consistently. We hope future refinements to ROBINS-I will address some of the issues raised here to allow wider use of the tool