ABSTRACT
DEXTER (detection of explosives and firearms to counter terrorism) is a project funded by NATO's Science for Peace and Security (SPS) program with the goal of developing an integrated system capable of remotely and accurately detecting explosives and firearms in public places without impeding the flow of pedestrians. While body scanner systems in secure areas of public places are becoming more and more efficient, the attack at Brussels airport on 22 March 2016, upstream of these systems, in the middle of the crowd of passengers, demonstrated the lack of discreet and real-time security against threats of mass terrorism. The NATO-SPS international and multi-year DEXTER project aims to provide new technical and strategic solutions to fill this gap. This project is based on multi-sensor coordination and fusion, from hyperspectral remote laser to smart glasses, artificial algorithms, and suspect identification and tracking. One of these sensors is dedicated to threat detection (large weapon or explosive belt) using the clothing of pedestrians by means of an active microwave component. This project is referred to as MIC (Microwave Imaging Curtain), also supported by the French SGDSN (General Secretariat of Defense and National Security), and utilizes a radar system capable of generating 3D images in real-time to address non-checkpoint detection of explosives and firearms. The project, led by ONERA (France), is based on a radar imaging system developed by the Fraunhofer FHR institute, using a MIMO architecture with an Ultra-Wide Band waveform. Although high-resolution 3D microwave imaging is already being used in expensive body scanners to detect firearms concealed under clothing, MIC's innovative approach lies in utilizing a high-resolution 3D imaging device that can detect larger dangerous objects carried by moving individuals at a longer range, in addition to providing discrete detection in pedestrian flow. Automatic detection and classification of these dangerous objects is carried out on 3D radar images using a deep-learning network. This paper will outline the project's objectives and constraints, as well as the design, architecture, and performance of the final system. Additionally, it will present real-time imaging results obtained during a live demonstration in a relevant environment.
ABSTRACT
PURPOSE: To analyze structural and vascular changes of the retina and choroid in pediatric patients with coronavirus disease 2019 (COVID-19) using optical coherence tomography (OCT)/OCT angiography (OCTA). METHODS: This comparative cross-sectional study consists of the COVID-19 group including pediatric COVID-19 patients and the control group including healthy children. Vessel density (VD), central macular thickness,, and choroidal thickness (ChT) measurements were performed using swept-source OCT/OCTA 12 weeks after the recovery from COVID-19. RESULTS: The mean VD measurements in the central fovea and nasal quadrants of all three retinal layers and choriocapillaris showed insignificantly lower values in the COVID-19 group when compared to the control group (0:002 < p < 0:05 for all). Similar to VD measurements, insignificant lower ChT measurements were obtained in the central fovea and nasal points in the COVID-19 group. CONCLUSION: OCTA can be used as a non-invasive and valid biomarker in the assessment of early microvascular dysfunction associated with COVID-19.
