Improving knowledge management through the support of image examination and data annotation using DICOM structured reporting

[EN] An important effort has been invested on improving the image diagnosis process in different medical areas using information technologies. The field of medical imaging involves two main data types: medical imaging and reports. Developments based on the DICOM standard have demonstrated to be a convenient and widespread solution among the medical community. The main objective of this work is to design a Web application prototype that will be able to improve diagnosis and follow-on of breast cancer patients. It is based on TRENCADIS middleware, which provides a knowledge-oriented storage model composed by federated repositories of DICOM image studies and DICOM-SR medical reports. The full structure and contents of the diagnosis reports are used as metadata for indexing images. The TRENCADIS infrastructure takes full advantage of Grid technologies by deploying multi-resource grid services that enable multiple views (reports schemes) of the knowledge database. The paper presents a real deployment of such Web application prototype in the Dr. Peset Hospital providing radiologists with a tool to create, store and search diagnostic reports based on breast cancer explorations (mammography, magnetic resonance, ultrasound, pre-surgery biopsy and post-surgery biopsy), improving support for diagnostics decisions. A technical details for use cases (outlining enhanced multi-resource grid services communication and processing steps) and interactions between actors and the deployed prototype are described. As a result, information is more structured, the logic is clearer, network messages have been reduced and, in general, the system is more resistant to failures.The authors wish to thank the financial support received from The Spanish Ministry of Education and Science to develop the project "CodeCloud", with reference TIN2010-17804.Salavert Torres, J.; Segrelles Quilis, JD.; Blanquer Espert, I.; Hernández García, V. (2012). Improving knowledge management through the support of image examination and data annotation using DICOM structured reporting. Journal of Biomedical Informatics. 45(6):1066-1074. https://doi.org/10.1016/j.jbi.2012.07.004S1066107445

NetJobs: A new approach to network monitoring for the Grid using Grid jobs

With grid computing, the far-fl�ung and disparate IT resources act as a single "virtual datacenter". Grid computing interfaces heterogeneous IT resources so they are available when and where we need them. Grid allows us to provision applications and allocate capacity among research and business groups that are geographically and organizationally dispersed. Building a high availability Grid is hold as the next goal to achieve: protecting against computer failures and site failures to avoid downtime of resource and honor Service Level Agreements. Network monitoring has a key role in this challenge. This work is concerning the design and the prototypal implementation of a new approach to Network monitoring for the Grid based on the usage of Grid scheduled jobs. This work was carried out within the Network Support task (SA2) of the Enabling Grids for E-sciencE (EGEE) project. This thesis is organized as follows: Chapter 1: Grid Computing From the origins of Grid Computing to the latest projects. Conceptual framework and main features characterizing many kind of popular grids will be presented. Chapter 2: The EGEE and EGI projects This chapter describes the Enabling Grids for E-sciencE (EGEE) project and the European Grid Infrastructure (EGI). EGEE project (2004-2010) was the�flagship Grid infrastructure project of the EU. The third and last two-year phase of the project (started on 1 May 2008) was financed with a total budget of around 47 million euro, with a further estimated 50 million euro worth of computing resources contributed by the partners. A total manpower of 9,000 Person Months, of which over 4,500 Person Months has been contributed by the partners from their own funding sources. At its close, EGEE represented a worldwide infrastructure of approximately to 200,000 CPU cores, collaboratively hosted by more than 300 centres around the world. By the end of the project, around 13 million jobs were executed on the EGEE grid each month. The new organization, EGI.eu, has then been created to continue the coordination and evolution of the European Grid Infrastructure (EGI) based on EGEE Grid. Chapter3: gLite Middleware Chapter three gives an overview on the gLite Grid Middleware. gLite is the middleware stack for grid computing used by the EGEE and EGI projects with in a very large variety of scientifi�c domains. Born from the collaborative efforts of more than 80 people in 12 different academic and industrial research centers as part of the EGEE Project, gLite provides a complete set of services for building a production grid infrastructure. gLite provides a framework for building grid applications tapping into the power of distributed computing and storage resources across the Internet. The gLite services are currently adopted by more than 250 Computing Centres and used by more than 15000 researchers in Europe and around the world. Chapter 4: Network Activity in EGEE/EGI Grid infrastructures are distributed by nature, involving many sites, normally in different administrative domains. Individual sites are connected together by a network, which is therefore a critical part of the whole Grid infrastructure; without the network there is no Grid. Monitoring is a key component for the successful operation of any infrastructure, helping in the discovery and diagnosis of any problem which may arise. Network monitoring is able to contribute to the day-to-day operations of the Grid by helping to provide answers to specific questions from users and site administrators. This chapter will discuss all the effort lavished by EGEE and EGI in the Grid Network domain. Chapter 5: Grid Network Monitoring based on Grid Jobs Net Jobs is a prototype of a light weight solution for the Grid network monitoring. A job-based approach has been used in order to prove the feasibility of this non intrusive solution. It is currently configured to monitor eight production sites spread from Italy to France but this method could be applied to the vast majority of Grid sites. The prototype provides coherent RTT, MTU, number of hops and TCP achievable bandwidth tests

Grid: From EGEE to EGI and from INFN-GRID to IGI

In the last fifteen years the approach of the “computational Grid” has changed the way to use computing resources. Grid computing has raised interest worldwide in academia, industry, and government with fast development cycles. Great efforts, huge funding and resources have been made available through national, regional and international initiatives aiming at providing Grid infrastructures, Grid core technologies, Grid middleware and Grid applications. The Grid software layers reflect the architecture of the services developed so far by the most important European and international projects. In this paper Grid e-Infrastructure story is given, detailing European, Italian and international projects such as EGEE, INFN-Grid and NAREGI. In addition the sustainability issue in the long-term perspective is described providing plans by European and Italian communities with EGI and IGI

Next Generation Internet of Things – Distributed Intelligence at the Edge and Human-Machine Interactions

This book provides an overview of the next generation Internet of Things (IoT), ranging from research, innovation, development priorities, to enabling technologies in a global context. It is intended as a standalone in a series covering the activities of the Internet of Things European Research Cluster (IERC), including research, technological innovation, validation, and deployment.The following chapters build on the ideas put forward by the European Research Cluster, the IoT European Platform Initiative (IoT–EPI), the IoT European Large-Scale Pilots Programme and the IoT European Security and Privacy Projects, presenting global views and state-of-the-art results regarding the next generation of IoT research, innovation, development, and deployment.The IoT and Industrial Internet of Things (IIoT) are evolving towards the next generation of Tactile IoT/IIoT, bringing together hyperconnectivity (5G and beyond), edge computing, Distributed Ledger Technologies (DLTs), virtual/ andaugmented reality (VR/AR), and artificial intelligence (AI) transformation.Following the wider adoption of consumer IoT, the next generation of IoT/IIoT innovation for business is driven by industries, addressing interoperability issues and providing new end-to-end security solutions to face continuous treats.The advances of AI technology in vision, speech recognition, natural language processing and dialog are enabling the development of end-to-end intelligent systems encapsulating multiple technologies, delivering services in real-time using limited resources. These developments are focusing on designing and delivering embedded and hierarchical AI solutions in IoT/IIoT, edge computing, using distributed architectures, DLTs platforms and distributed end-to-end security, which provide real-time decisions using less data and computational resources, while accessing each type of resource in a way that enhances the accuracy and performance of models in the various IoT/IIoT applications.The convergence and combination of IoT, AI and other related technologies to derive insights, decisions and revenue from sensor data provide new business models and sources of monetization. Meanwhile, scalable, IoT-enabled applications have become part of larger business objectives, enabling digital transformation with a focus on new services and applications.Serving the next generation of Tactile IoT/IIoT real-time use cases over 5G and Network Slicing technology is essential for consumer and industrial applications and support reducing operational costs, increasing efficiency and leveraging additional capabilities for real-time autonomous systems.New IoT distributed architectures, combined with system-level architectures for edge/fog computing, are evolving IoT platforms, including AI and DLTs, with embedded intelligence into the hyperconnectivity infrastructure.The next generation of IoT/IIoT technologies are highly transformational, enabling innovation at scale, and autonomous decision-making in various application domains such as healthcare, smart homes, smart buildings, smart cities, energy, agriculture, transportation and autonomous vehicles, the military, logistics and supply chain, retail and wholesale, manufacturing, mining and oil and gas

Grid Analysis of Radiological Data

IGI-Global Medical Information Science Discoveries Research Award 2009International audienceGrid technologies and infrastructures can contribute to harnessing the full power of computer-aided image analysis into clinical research and practice. Given the volume of data, the sensitivity of medical information, and the joint complexity of medical datasets and computations expected in clinical practice, the challenge is to fill the gap between the grid middleware and the requirements of clinical applications. This chapter reports on the goals, achievements and lessons learned from the AGIR (Grid Analysis of Radiological Data) project. AGIR addresses this challenge through a combined approach. On one hand, leveraging the grid middleware through core grid medical services (data management, responsiveness, compression, and workflows) targets the requirements of medical data processing applications. On the other hand, grid-enabling a panel of applications ranging from algorithmic research to clinical use cases both exploits and drives the development of the services

Next Generation Internet of Things – Distributed Intelligence at the Edge and Human-Machine Interactions

This book provides an overview of the next generation Internet of Things (IoT), ranging from research, innovation, development priorities, to enabling technologies in a global context. It is intended as a standalone in a series covering the activities of the Internet of Things European Research Cluster (IERC), including research, technological innovation, validation, and deployment.The following chapters build on the ideas put forward by the European Research Cluster, the IoT European Platform Initiative (IoT–EPI), the IoT European Large-Scale Pilots Programme and the IoT European Security and Privacy Projects, presenting global views and state-of-the-art results regarding the next generation of IoT research, innovation, development, and deployment.The IoT and Industrial Internet of Things (IIoT) are evolving towards the next generation of Tactile IoT/IIoT, bringing together hyperconnectivity (5G and beyond), edge computing, Distributed Ledger Technologies (DLTs), virtual/ andaugmented reality (VR/AR), and artificial intelligence (AI) transformation.Following the wider adoption of consumer IoT, the next generation of IoT/IIoT innovation for business is driven by industries, addressing interoperability issues and providing new end-to-end security solutions to face continuous treats.The advances of AI technology in vision, speech recognition, natural language processing and dialog are enabling the development of end-to-end intelligent systems encapsulating multiple technologies, delivering services in real-time using limited resources. These developments are focusing on designing and delivering embedded and hierarchical AI solutions in IoT/IIoT, edge computing, using distributed architectures, DLTs platforms and distributed end-to-end security, which provide real-time decisions using less data and computational resources, while accessing each type of resource in a way that enhances the accuracy and performance of models in the various IoT/IIoT applications.The convergence and combination of IoT, AI and other related technologies to derive insights, decisions and revenue from sensor data provide new business models and sources of monetization. Meanwhile, scalable, IoT-enabled applications have become part of larger business objectives, enabling digital transformation with a focus on new services and applications.Serving the next generation of Tactile IoT/IIoT real-time use cases over 5G and Network Slicing technology is essential for consumer and industrial applications and support reducing operational costs, increasing efficiency and leveraging additional capabilities for real-time autonomous systems.New IoT distributed architectures, combined with system-level architectures for edge/fog computing, are evolving IoT platforms, including AI and DLTs, with embedded intelligence into the hyperconnectivity infrastructure.The next generation of IoT/IIoT technologies are highly transformational, enabling innovation at scale, and autonomous decision-making in various application domains such as healthcare, smart homes, smart buildings, smart cities, energy, agriculture, transportation and autonomous vehicles, the military, logistics and supply chain, retail and wholesale, manufacturing, mining and oil and gas

Satellite Networks: Architectures, Applications, and Technologies

Since global satellite networks are moving to the forefront in enhancing the national and global information infrastructures due to communication satellites' unique networking characteristics, a workshop was organized to assess the progress made to date and chart the future. This workshop provided the forum to assess the current state-of-the-art, identify key issues, and highlight the emerging trends in the next-generation architectures, data protocol development, communication interoperability, and applications. Presentations on overview, state-of-the-art in research, development, deployment and applications and future trends on satellite networks are assembled

Technological Leap, Statutory Gap, and Constitutional Abyss: Remote Biometric Identification Comes of Age

Federal interest in using facial recognition technology (“FRT”) to collect, analyze, and use biometric information is rapidly growing. Despite the swift movement of agencies and contractors into this realm, however, Congress has been virtually silent on the current and potential uses of FRT. No laws directly address facial recognition—much less the pairing of facial recognition with video surveillance—in criminal law. Limits placed on the collection of personally identifiable information, moreover, do not apply. The absence of a statutory framework is a cause for concern. FRT represents the first of a series of next generation biometrics, such as hand geometry, iris, vascular patterns, hormones, and gait, which, when paired with surveillance of public space, give rise to novel questions of law and policy. These technologies constitute what can be termed Remote Biometric Identification (“RBI”). That is, they give the government the ability to ascertain the identity (1) of multiple people, (2) at a distance, (3) in public space, (4) absent notice and consent, and (5) in a continuous and on-going manner. RBI fundamentally differs from what can be understood as Immediate Biometric Identification (“IBI”)--i.e., the use of biometrics to determine identity at the point of arrest, following conviction, or in conjunction with access to secure facilities. IBI, in contrast, tends to be focused (1) on a single individual, (2) close-up, (3) in relation either to custodial detention or in the context of a specific physical area related to government activity, (4) in a manner often involving notice and often consent, and (5) is a one-time or limited occurrence. The types of legal and policy questions raised by RBI significantly differ from those accompanying IBI. In the absence of a statutory framework, we are driven to Constitutional considerations, where the Court’s jurisprudence proves inadequate as a way of addressing the concerns that present in the realm of RBI. The Fourth Amendment’s guarantee to protection against unreasonable search and seizure and the probable cause requirement for the issuance of warrants; the Fifth Amendment’s right against self-incrimination; the First Amendment’s protection of speech and assembly; and the Fifth and Fourteenth Amendments’ due process protections fail to account for the way in which such measures fundamentally challenge the current norms. The article calls for Congressional action and a judicial framing commensurate with the threat posed by these new and emerging technologies