At the third TechEvent this year Dr. med. Thomas Baumann and Dr. med. et phil. Stefan Essig have shown us how telemedicine can support pediatricians when diagnosing hip dysplasia.

 

SVUPP is the Swiss association for pediatric ultra sound applications. Thanks to the new SVUPP Exchange Portal, the vision for telemedicine, designed for practicing pediatricians in Switzerland in the area of ultrasound, has become a reality. The digitalization of the imagery exchange leads to a fast and high-quality ultrasound examination of newborns.

 

 

 

 

The original idea for the SVUPP Exchange Portal stems from an assistance project in Mongolia, which has been supported by Switzerland and runs an evidence-based prevention program for hip dysplasia, a common development disorder in newborns.

 

 

 

Applied Technologies: Angular, TypeScript, Microsoft .NET Core, Event Store, MongoDB, OAuth 2

SVUPP – Schweizerische Vereinigung für Ultraschall in der Pädiatrie
SMPOPP – SwissMongolian Pediatric Project

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In der Schweiz besteht ein grosses Energieeffizienzpotential in Gebäuden. Bestehende Heizungsanlagen in Gebäuden sind heute oft nicht ideal eingestellt, weisen Mängel auf oder sind gar dysfunktional. Zur Detektion dieser Mängel soll ein Prototyp eines automatisierten Anamnese-Systems aufgebaut werden, welches aufgrund von sensorischen Messgrössen (primär Temperaturfühler) die Anlage erstens identifiziert, zweitens auf Fehler analysiert und drittens eine Liste von Handlungsempfehlungen generiert, um das System zu verbessern. Continue reading “Automatisierte Anamnese von Heizungen und Gebäudeenergieanlagen”

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OverviewTechnical maintenance on ticket vending machines requires a high level of expertise. Technicians usually need many weeks to get a good understanding of the vending machines, under the tight supervision of their mentor. The goal of the present study is to design and implement an AR (Augmented Reality) system that will facilitate the work of the technicians and reduce their apprenticeship time. In fact, this AR solution will provide in real-time the necessary information with the corresponding documentation of the component that needs maintenance. For instance, a technician will be able to immediately scan the different components in the TVM and determine which are the cables that must be connected between them. Continue reading “Facilitated Maintenance with Augmented Reality”

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In this work, flexible test equipment for Ethernet network hardware and firmware shall be evaluate and commissioned. The goal is to model and characterize an Ethernet network based on BroadR-Reach with ring topology and HSR protocol for its real-time behavior.The test equipment could be based on devices available at netfpga.org. Extensions may be developed to further improve functionality. Continue reading “Flexible FPGA-based Test Equipment to Model and Characterize the Real-Time Behavior of an Ethernet Ring”

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Alle aktuellen SDR Softwarepakete haben Einschränkungen. Es gibt GNU Radio, welches kompliziert und schwierig zu bedienen ist, und es gibt verschiedene SDR GUIs, welche jedoch nicht einfach erweiterbar sind. Das Ziel ist eine einfach zu bedienende Software zu erstellen, welche es ermöglicht, Radiosignale zu analysieren und Algorithmen auszuprobieren. Fertige Abläufe sollen dann auf Knopfdruck in eine C-Datei exportiert werden können, um eine Integration in Embedded Systeme so leicht wie möglich zu gestalten. Continue reading “Software-Architecture for SDR”
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eVoting is an unsolved problem, mainly because of security concerns connected to centralized IT systems. Blockchain technology enables new ways to solve IT problems in a transparent, tamper-proof and decentralized way. However, scalability of such solutions is still unsatisfactory and there’s still no solution that provides privacy of the single voter and transparency of the overall voting process at the same time.This master thesis aims at implementing a voting solution that scales to Swiss national votes. The technologies to be used could include zero knowledge proofs (zk-SNARKS), homomorphic encryption and smart contracts on a public blockchain (i.e. ethereum). Different layer-two technologies shall be evaluated to provide scalability for this use case.

Continue reading “Decentralized Ledger eVoting System”

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A large part of the medical imaging data available today is available in 3D. This is true for example for magnetic resonance imaging data, computed tomography scan data and many other techniques. This is advantageous as it allows drawing conclusions based not only on single images but taking into account more information. Many medical images have to be further processed by segmenting different objects in the images such as bones or tissue layers. In the past years, the analysis of 2D medical images with Deep Learning methods has become a standard in research. With more and more computing power available, the focus is moving towards 3D analysis to profit from more spatial context.

Continue reading “Extend Machine- and Deep Learning into 3D – Enabling volumetric Analysis of Medical Image Data”

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Die wachsende Transparenz im Niederspannungsnetz ermöglicht es unter anderem transiente Vorgänge hochauflösend aufzuzeichnen. Somit wird es denkbar, mit geeigneten Algorithmen die Fehlerstelle im Störungsfall zu lokalisieren, wie es heute nur auf höheren Spannungsebenen gemacht wird. Die Kosten für die Suche nach der Fehlerstelle und die Interventionszeiten der Netzbetreiber könnten somit gesenkt werden und damit wird ein Mehrwert geschaffen.Im ersten Schritt soll der Student im Rahmen seiner Arbeit die bestehenden Fehlerortungsalgorithmen auf deren Anwendbarkeit im Niederspannungsnetz untersuchen und eine Evaluation vornehmen. Im zweiten Schritt soll ein geeigneter Algorithmus implementiert und mittels simulierter Daten getestet werden. Zudem sollen Versuche im ewz Labor durchgeführt werden, um echte Messdaten zu gewinnen.

Continue reading “Fehlerlokalisierung im Niederspannungsnetz”

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Today’s Machine Learning algorithms rely on large data sets of ground truth. Especially for medical use cases the lack of appropriate data for training can be a limiting factor for successful Deep Learning. For some imaging problems, the creation of synthetic ground truth can effectively overcome the lack of original ground truth and enable successful learning.In this work we aim to explore the potential of synthetic ground truth for tumor segmentation in medical imagery of eyes. The student will work with 3D stacks of optical coherence tomography (OCT) images. The currently implemented Convolutional Neural Networks (CNNs, e.g. U-net) shall be extended to segment tumors using both synthetic ground truth data and state-of-art CNNs.

Continue reading “Generation of synthetic ground truth for Machine Learning”

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Pediatricians and general practitioners use ultrasound for diagnostic purposes in their office. Ultrasound is fast, reliable, safe, and is seen as the visual stethoscope of the 21st century. Standardized, high-quality examinations depend on the exact position of the transducer for transmitting and receiving the ultrasound beam. However, the correct plane defining the image cross section obtained from the patient is often difficult to achieve.Advanced technology might support physicians with feedback based on automated analyses of examinations by ultrasound. We will use the example of ultrasound-based diagnosis of developmental dysplasia of the hip (DDH) in newborns to suggest such an approach using Neural Networks.

Continue reading “Learning Angles from Ultrasonography Imagery with Machine Learning and Deep Learning”