Metal Artifact Reduction in Spectral X-ray CT Using Spectral Deep Learning.

Spectral X-ray computed tomography (SCT) is an emerging method for non-destructive imaging of the inner structure of materials. Compared with the conventional X-ray CT, this technique provides spectral photon energy resolution in a finite number of energy channels, adding a new dimension to the reconstructed volumes and images. While this mitigates energy-dependent distortions such as beam hardening, metal artifacts due to photon starvation effects are still present, especially for low-energy channels where the attenuation coefficients are higher. We present a correction method for metal artifact reduction in SCT that is based on spectral deep learning. The correction efficiently reduces streaking artifacts in all the energy channels measured. We show that the additional information in the energy domain provides relevance for restoring the quality of low-energy reconstruction affected by metal artifacts. The correction method is parameter free and only takes around 15 ms per energy channel, satisfying near-real time requirement of industrial scanners.

Global Modeled Sinking Characteristics of Biofouled Microplastic.

Microplastic debris ending up at the sea surface has become a known major environmental issue. However, how microplastic particles move and when they sink in the ocean remains largely unknown. Here, we model microplastic subject to biofouling (algal growth on a substrate) to estimate sinking timescales and the time to reach the depth where particles stop sinking. We combine NEMO-MEDUSA 2.0 output, that represents hydrodynamic and biological properties of seawater, with a particle-tracking framework. Different sizes and densities of particles (for different types of plastic) are simulated, showing that the global distribution of sinking timescales is largely size-dependent as opposed to density-dependent. The smallest particles we simulate (0.1 µm) start sinking almost immediately around the globe and their trajectories take the longest time to reach their first sinking depth (relative to larger particles). In oligotrophic subtropical gyres with low algal concentrations, particles between 1 and 0.01 mm do not sink within the simulation time of 90 days. This suggests that in addition to the comparatively well-known physical processes, biological processes might also contribute to the accumulation of floating plastic (of 1-0.01 mm) in subtropical gyres. Particles of 1 µm in the gyres start sinking largely due to vertical advection, whereas in the equatorial Pacific they are more dependent on biofouling. The qualitative impacts of seasonality on sinking timescales are small, however, localized sooner sinking due to spring algal blooms is seen. This study maps processes that affect the sinking of virtual microplastic globally, which could ultimately impact the ocean plastic budget.

An interactive simulation and visualization tool for flood analysis usable for practitioners.

Developing strategies to mitigate or to adapt to the threats of floods is an important topic in the context of climate changes. Many of the world's cities are endangered due to rising ocean levels and changing precipitation patterns. It is therefore crucial to develop analytical tools that allow us to evaluate the threats of floods and to investigate the influence of mitigation and adaptation measures, such as stronger dikes, adaptive spatial planning, and flood disaster plans. Up until the present, analytical tools have only been accessible to domain experts, as the involved simulation processes are complex and rely on computational and data-intensive models. Outputs of these analytical tools are presented to practitioners (i.e., policy analysts and political decision-makers) on maps or in graphical user interfaces. In practice, this output is only used in limited measure because practitioners often have different information requirements or do not trust the direct outcome. Nonetheless, literature indicates that a closer collaboration between domain experts and practitioners can ensure that the information requirements of practitioners are better aligned with the opportunities and limitations of analytical tools. The objective of our work is to present a step forward in the effort to make analytical tools in flood management accessible for practitioners to support this collaboration between domain experts and practitioners. Our system allows the user to interactively control the simulation process (addition of water sources or influence of rainfall), while a realistic visualization allows the user to mentally map the results onto the real world. We have developed several novel algorithms to present and interact with flood data. We explain the technologies, discuss their necessity alongside test cases, and introduce a user study to analyze the reactions of practitioners to our system. We conclude that, despite the complexity of flood simulation models and the size of the involved data sets, our system is accessible for practitioners of flood management so that they can carry out flood simulations together with domain experts in interactive work sessions. Therefore, this work has the potential to significantly change the decision-making process and may become an important asset in choosing sustainable flood mitigations and adaptation strategies.

Accuracy of prehospital diagnosis and triage of a Swiss helicopter emergency medical service.

BACKGROUND: Helicopter emergency medical services (HEMSs) have become a standard element of modern prehospital emergency medicine. This study determines the percentage of injured HEMS patients whose injuries were correctly recognized by HEMS physicians. METHODS: A retrospective level III evidence prognostic study using data from the largest Swiss HEMS, REGA (Rettungsflugwacht/Guarde Aérienne), on adult patients with trauma transported to a Level I trauma center (January 2006-December 2007). National Advisory Committee on Aeronautics (NACA) scores and the Injury Severity Score (ISS) were assessed to identify severely injured patients. Injured body regions diagnosed by REGA physicians were compared with emergency department discharge diagnoses. RESULTS: Four hundred thirty-three patients were analyzed. Median age was 42.1 years (interquartile range, 25.5-57.9). Three hundred twenty-three (74.6%) were men. Patients were severely injured, with an in-hospital NACA score of 4 or higher in 88.7% of patients and median ISS of 13. REGA physicians correctly recognized injuries to the head in 92.9%, to the femur in 90.5%, and to the tibia/fibula in 83.8% of patients. Injuries to these body regions were overdiagnosed in less than 30%. Abdominal injuries were missed in 56.1%, pelvic injuries in 51.8%, spinal injuries in 40.1%, and chest injuries in 31.2% of patients. CONCLUSION: This study shows that patients are adequately triaged by REGA physicians reflected by a NACA score 4 or higher in 88.7% of patients and a median ISS of 13. However, recognition of injured body regions seems to be challenging in the prehospital setting. Prospective studies on specific training of HEMS physicians for recognition of these injuries (e.g., portable ultrasonography, telemedicine) might help in the future. LEVEL OF EVIDENCE: Prognostic study, level III.