Web-based Stereoscopic Collaboration for Medical Visualization

Medizinische Volumenvisualisierung ist ein wertvolles Werkzeug zur Betrachtung von Volumen- daten in der medizinischen Praxis und Lehre. Eine interaktive, stereoskopische und kollaborative Darstellung in Echtzeit ist notwendig, um die Daten vollständig und im Detail verstehen zu können. Solche Visualisierung von hochauflösenden Daten ist jedoch wegen hoher Hardware- Anforderungen fast nur an speziellen Visualisierungssystemen möglich. Remote-Visualisierung wird verwendet, um solche Visualisierung peripher nutzen zu können. Dies benötigt jedoch fast immer komplexe Software-Deployments, wodurch eine universelle ad-hoc Nutzbarkeit erschwert wird. Aus diesem Sachverhalt ergibt sich folgende Hypothese: Ein hoch performantes Remote- Visualisierungssystem, welches für Stereoskopie und einfache Benutzbarkeit spezialisiert ist, kann für interaktive, stereoskopische und kollaborative medizinische Volumenvisualisierung genutzt werden. Die neueste Literatur über Remote-Visualisierung beschreibt Anwendungen, welche nur reine Webbrowser benötigen. Allerdings wird bei diesen kein besonderer Schwerpunkt auf die perfor- mante Nutzbarkeit von jedem Teilnehmer gesetzt, noch die notwendige Funktion bereitgestellt, um mehrere stereoskopische Präsentationssysteme zu bedienen. Durch die Bekanntheit von Web- browsern, deren einfach Nutzbarkeit und weite Verbreitung hat sich folgende spezifische Frage ergeben: Können wir ein System entwickeln, welches alle Aspekte unterstützt, aber nur einen reinen Webbrowser ohne zusätzliche Software als Client benötigt? Ein Proof of Concept wurde durchgeführt um die Hypothese zu verifizieren. Dazu gehörte eine Prototyp-Entwicklung, deren praktische Anwendung, deren Performanzmessung und -vergleich. Der resultierende Prototyp (CoWebViz) ist eines der ersten Webbrowser basierten Systeme, welches flüssige und interaktive Remote-Visualisierung in Realzeit und ohne zusätzliche Soft- ware ermöglicht. Tests und Vergleiche zeigen, dass der Ansatz eine bessere Performanz hat als andere ähnliche getestete Systeme. Die simultane Nutzung verschiedener stereoskopischer Präsen- tationssysteme mit so einem einfachen Remote-Visualisierungssystem ist zur Zeit einzigartig. Die Nutzung für die normalerweise sehr ressourcen-intensive stereoskopische und kollaborative Anatomieausbildung, gemeinsam mit interkontinentalen Teilnehmern, zeigt die Machbarkeit und den vereinfachenden Charakter des Ansatzes. Die Machbarkeit des Ansatzes wurde auch durch die erfolgreiche Nutzung für andere Anwendungsfälle gezeigt, wie z.B. im Grid-computing und in der Chirurgie

Helmholtz Portfolio Theme Large-Scale Data Management and Analysis (LSDMA)

The Helmholtz Association funded the "Large-Scale Data Management and Analysis" portfolio theme from 2012-2016. Four Helmholtz centres, six universities and another research institution in Germany joined to enable data-intensive science by optimising data life cycles in selected scientific communities. In our Data Life cycle Labs, data experts performed joint R&D together with scientific communities. The Data Services Integration Team focused on generic solutions applied by several communities

CONVR 2011 : Proceedings of the 11th International Conference on Construction Applications of Virtual Reality

Proceedings of the 11th International Conference on Construction Applications of Virtual Realit

A formal architecture-centric and model driven approach for the engineering of science gateways

From n-Tier client/server applications, to more complex academic Grids, or even the most recent and promising industrial Clouds, the last decade has witnessed significant developments in distributed computing. In spite of this conceptual heterogeneity, Service-Oriented Architecture (SOA) seems to have emerged as the common and underlying abstraction paradigm, even though different standards and technologies are applied across application domains. Suitable access to data and algorithms resident in SOAs via so-called ‘Science Gateways’ has thus become a pressing need in order to realize the benefits of distributed computing infrastructures.In an attempt to inform service-oriented systems design and developments in Grid-based biomedical research infrastructures, the applicant has consolidated work from three complementary experiences in European projects, which have developed and deployed large-scale production quality infrastructures and more recently Science Gateways to support research in breast cancer, pediatric diseases and neurodegenerative pathologies respectively. In analyzing the requirements from these biomedical applications the applicant was able to elaborate on commonly faced issues in Grid development and deployment, while proposing an adapted and extensible engineering framework. Grids implement a number of protocols, applications, standards and attempt to virtualize and harmonize accesses to them. Most Grid implementations therefore are instantiated as superposed software layers, often resulting in a low quality of services and quality of applications, thus making design and development increasingly complex, and rendering classical software engineering approaches unsuitable for Grid developments.The applicant proposes the application of a formal Model-Driven Engineering (MDE) approach to service-oriented developments, making it possible to define Grid-based architectures and Science Gateways that satisfy quality of service requirements, execution platform and distribution criteria at design time. An novel investigation is thus presented on the applicability of the resulting grid MDE (gMDE) to specific examples and conclusions are drawn on the benefits of this approach and its possible application to other areas, in particular that of Distributed Computing Infrastructures (DCI) interoperability, Science Gateways and Cloud architectures developments

Experimental Evaluation of Growing and Pruning Hyper Basis Function Neural Networks Trained with Extended Information Filter

In this paper we test Extended Information Filter (EIF) for sequential training of Hyper Basis Function Neural Networks with growing and pruning ability (HBF-GP). The HBF neuron allows different scaling of input dimensions to provide better generalization property when dealing with complex nonlinear problems in engineering practice. The main intuition behind HBF is in generalization of Gaussian type of neuron that applies Mahalanobis-like distance as a distance metrics between input training sample and prototype vector. We exploit concept of neuron’s significance and allow growing and pruning of HBF neurons during sequential learning process. From engineer’s perspective, EIF is attractive for training of neural networks because it allows a designer to have scarce initial knowledge of the system/problem. Extensive experimental study shows that HBF neural network trained with EIF achieves same prediction error and compactness of network topology when compared to EKF, but without the need to know initial state uncertainty, which is its main advantage over EKF

Remote Sensing and Geosciences for Archaeology

This book collects more than 20 papers, written by renowned experts and scientists from across the globe, that showcase the state-of-the-art and forefront research in archaeological remote sensing and the use of geoscientific techniques to investigate archaeological records and cultural heritage. Very high resolution satellite images from optical and radar space-borne sensors, airborne multi-spectral images, ground penetrating radar, terrestrial laser scanning, 3D modelling, Geographyc Information Systems (GIS) are among the techniques used in the archaeological studies published in this book. The reader can learn how to use these instruments and sensors, also in combination, to investigate cultural landscapes, discover new sites, reconstruct paleo-landscapes, augment the knowledge of monuments, and assess the condition of heritage at risk. Case studies scattered across Europe, Asia and America are presented: from the World UNESCO World Heritage Site of Lines and Geoglyphs of Nasca and Palpa to heritage under threat in the Middle East and North Africa, from coastal heritage in the intertidal flats of the German North Sea to Early and Neolithic settlements in Thessaly. Beginners will learn robust research methodologies and take inspiration; mature scholars will for sure derive inputs for new research and applications