3D-MRI Obstruction and Visualization of Pharyngeal Airway Tract using Open Source Seeded Technique

Abstract: Obstructive Sleep Apnea(OSA) is breathing disorder syndrome in which the airway tract pauses during sleep due to collapse of pharyngeal airway. It is occurred at the sleep time, with fourth dimensional high resolution in airway tract Obstruction in children and adults with OSA. Here, we the operator places the seeds that includes the Oesopharyngeal air tract and found out a threshold for the first frame in order to determine the affected tissues which blocks the patients pharyngeal tract. In this automated segmentation method it shows the process of MRI studies of the pharyngeal air pathway and enable diagnose of obstructive tissues with the collapse tissues. Region growing method results well in Dice Coefficients compared with manual segmentation. It automatically detects 90% of collapse tissues. This approach leads to segment the pharyngeal pathway correctly. It uses long MRI scans in order to diagnosis the collapsed tissues with graph, accurate details and coefficients in a short span of duration

Massively Extended Modular Monitoring and a Second Life for Upper Stages

Launching science and technology experiments to space is expensive. Although commercial spaceflight has resulted in a drop of prices, the cost for a launch is still significant. However, most of theweight that is needed to conduct experiments in space belongs to the spacecraft’s bus and it is responsiblefor power distribution, thermal management, orbital control and communications. An upper stage, on the other hand, includes all the necessary subsystems andhas to be launched in any case. Many upper stages (e.g. ARIANE5) will even stay in orbit for severalyears after their nominal mission with all their subsystems intact but passivated.We proposea compact system based on a protective container and high-performance Commercial-off-the-Shelf (COTS) hardwarethat allows cost-efficient launching oftechnology experiments by reusing the launcher’s upper stage and its subsystems. Addingacquisition channels for various sensors gives the launch provider the ability to exploitthe computational power of the COTS hardwareduring the nominal mission. In contrast to existing systems,intelligent and mission-dependent data selection and compression can beapplied to the sensor data.In this paper, we demonstrate the implementation and qualification of a payload bussystem based on COTScomponentsthat is minimallyinvasive to the launcher(ARIANE5)and its nominal missionwhile offering computational power to both the launch provider and a potential payloaduser. The reliability of the COTS-based system is improvedby radiation hardening techniques and software-based self-test detecting and counteracting faults during the mission

OSIRIS – The scientific camera system onboard Rosetta

The Optical, Spectroscopic, and Infrared Remote Imaging System OSIRIS is the scientific camera system onboard the Rosetta spacecraft (Figure 1). The advanced high performance imaging system will be pivotal for the success of the Rosetta mission. OSIRIS will detect 67P/Churyumov-Gerasimenko from a distance of more than 106 km, characterise the comet shape and volume, its rotational state and find a suitable landing spot for Philae, the Rosetta lander. OSIRIS will observe the nucleus, its activity and surroundings down to a scale of ~2 cm px−1. The observations will begin well before the onset of cometary activity and will extend over months until the comet reaches perihelion. During the rendezvous episode of the Rosetta mission, OSIRIS will provide key information about the nature of cometary nuclei and reveal the physics of cometary activity that leads to the gas and dust coma. OSIRIS comprises a high resolution Narrow Angle Camera (NAC) unit and a Wide Angle Camera (WAC) unit accompanied by three electronics boxes. The NAC is designed to obtain high resolution images of the surface of comet 7P/Churyumov-Gerasimenko through 12 discrete filters over the wavelength range 250–1000 nm at an angular resolution of 18.6 μrad px−1. The WAC is optimised to provide images of the near-nucleus environment in 14 discrete filters at an angular resolution of 101 μrad px−1. The two units use identical shutter, filter wheel, front door, and detector systems. They are operated by a common Data Processing Unit. The OSIRIS instrument has a total mass of 35 kg and is provided by institutes from six European countrie

Survey of FPGA applications in the period 2000 – 2015 (Technical Report)

Romoth J, Porrmann M, Rückert U. Survey of FPGA applications in the period 2000 – 2015 (Technical Report).; 2017.Since their introduction, FPGAs can be seen in more and more different fields of applications. The key advantage is the combination of software-like flexibility with the performance otherwise common to hardware. Nevertheless, every application field introduces special requirements to the used computational architecture. This paper provides an overview of the different topics FPGAs have been used for in the last 15 years of research and why they have been chosen over other processing units like e.g. CPUs

Générateur de coprocesseur pour le traitement de données en flux (vidéo ou similaire) sur FPGA.

Using Field Programmable Gate Arrays (FPGA) is one of the very few solution for real time processingdata flows of several hundreds of Msamples/second. However, using such componentsis technically challenging beyond the need to become familiar with a new kind of dedicateddescription language and ways of describing algorithms, understanding the hardware behaviouris mandatory for implementing efficient processing solutions. In order to circumvent these difficulties,past researches have focused on providing solutions which, starting from a description ofan algorithm in a high-abstraction level language, generetes a description appropriate for FPGAconfiguration. Our contribution, following the strategy of block assembly based on the skeletonmethod, aimed at providing a software environment called CoGen for assembling various implementationsof readily available and validated processing blocks. The resulting processing chainis optimized by including FPGA hardware characteristics, and input and output bandwidths ofeach block in order to provide solution fitting best the requirements and constraints. Each processingblock implementation is either generated automatically or manually, but must complywith some constraints in order to be usable by our tool. In addition, each block developer mustprovide a standardized description of the block including required resources and data processingbandwidth limitations. CoGen then provides to the less experienced user the means to assemblethese blocks ensuring synchronism and consistency of data flow as well as the ability to synthesizethe processing chain in the available hardware resources. This working method has beenapplied to video data flow processing (threshold, contour detection and tuning fork eigenmodesanalysis) and on radiofrequency data flow (wireless interrogation of sensors through a RADARsystem, software processing of a frequency modulated stream, software defined radio).L’utilisation de matrice de portes logiques reconfigurables (FPGA) est une des seules solutionspour traiter des flux de plusieurs 100 MÉchantillons/seconde en temps-réel. Toutefois, ce typede composant présente une grande difficulté de mise en oeuvre : au delà d’un type langage spécifique,c’est tout un environnement matériel et une certaine expérience qui sont requis pourobtenir les traitements les plus efficaces. Afin de contourner cette difficulté, de nombreux travauxont été réalisés dans le but de proposer des solutions qui, partant d’un code écrit dans unlangage de haut-niveau, vont produire un code dans un langage dédié aux FPGAs. Nos travaux,suivant l’approche d’assemblage de blocs et en suivant la méthode du skeleton, ont visé à mettreen place un logiciel, nommé CoGen, permettant, à partir de codes déjà développés et validés,de construire des chaînes de traitements en tenant compte des caractéristiques du FPGA cible,du débit entrant et sortant de chaque bloc pour garantir l’obtention d’une solution la plus adaptéepossible aux besoins et contraintes. Les implémentations des blocs de traitements sont soitgénérés automatiquement soit manuellement. Les entrées-sorties de chaque bloc doivent respecterune norme pour être exploitable dans l’outil. Le développeur doit fournir une descriptionconcernant les ressources nécessaires et les limitations du débit de données pouvant être traitées.CoGen fournit à l’utilisateur moins expérimenté une méthode d’assemblage de ces blocsgarantissant le synchronisme et cohérence des flux de données ainsi que la capacité à synthétiserle code sur les ressources matérielles accessibles. Cette méthodologie de travail est appliquéeà des traitements sur des flux vidéos (seuillage, détection de contours et analyse des modespropres d’un diapason) et sur des flux radio-fréquences (interrogation d’un capteur sans-fils parméthode RADAR, réception d’un flux modulé en fréquence, et finalement implémentation deblocs de bases pour déporter le maximum de traitements en numérique)