— DeSE 2011 Keynote Speeches —
Recent advances in Electrical Impedance Tomography
Professor Panos Liatsis
City University London, UK
Electrical Impedance Tomography (EIT) belongs to a class of emerging, inverse imaging techniques, characterized by a non-invasive and non-intrusive nature. A current pattern needs to be applied in the periphery of the body, which then interact with the object to be imaged with EIT. Next, voltage measurements are carried out on the boundary, followed by reconstruction of the interior structure of the body based on the boundary data. The entire imaging process can be considered as a sequence of two essential steps. The task of collecting boundary data is called the forward problem and involves estimating the boundary measurements, given a discrete model of the underlying body, excitation patterns and some a-priori knowledge of the passive electromagnetic properties of the subject. The second task of creating an image based on boundary measurements is known as the inverse problem and as it is ill-posed and non-linear is consider as more complex.
In most engineering applications where discrete models based on FEM are used, a coarse model results in a very crude approximation of the final solution, contrary to a fine model resulting in a more accurate one. Due to the given complexity of the EIT problem, recent studies have demonstrated that a coarse model not only produces inaccurate results, but also introduces artifacts in the reconstructed solution. Further, if boundary surface details are not sufficiently encapsulated in the mesh model, degraded images are reported. A significant consideration in real-world applications is the case where the domain shape dynamically evolves. Even with accurate 3D parametrization, mesh misfits are commonly observed and re-meshing is necessary to encapsulate better boundary information. In effect, the procedure should be repeated until the mesh density adequately captures both boundary and solution variations. An additional bottleneck in the pipeline is faced by taking into account that a typical configuration for ET applications involves 1M elements (on average), which practically prevents imaging of objects with non-static boundaries.
The research direction pursued at City University London involves a novel, mesh-free, research approach, which aims to address both the theoretical and computational framework for a system capable of overriding the current limitations and capable of producing real-time higher-resolution images either of fixed- or multi-resolution configuration. The proposed framework makes use of embedded domain methods in conjunction with the properties of multiscale and multiresolution basis functions, i.e., wavelets.
Professor Panos Liatsis has a Diploma in Electrical Engineering from the University of Thrace in Greece and a Ph.D in Electrical Engineering and Electronics from the Control Systems Centre at the University of Manchester (UMIST). He commenced his academic career at the University of Manchester, before joining City University, where he is currently a Professor of Image Processing and the Head of the Information Engineering and Medical Imaging Centre. Panos is the author/co-author of over 130 research publications in international journals, book chapters and conference proceedings. He was the Programme Chair of the 9th International Conference in Systems, Signals and Image Processing, and is involved in the Programme Committees of various IEEE/EURASIP conferences, in the areas of image and signal processing. He has over 15 years expertise in the development of advanced sensors, pattern recognition and intelligent systems, with focus on medical imaging.
Collaborative Virtual Workspaces for Solving Complex Problems
Involving Multifunctional Teams
Professor Terrence Fernando
University of Salford, UK
Due to globalization and the need for bringing range of experts and organizations together for solving global challenges, the importance of sophisticated e-collaboration platforms that can offer problem solving and consensus building environments for multi-functional teams is ever more apparent. This talk will examine the requirements for such e-collaboration platforms in two contrast areas, engineering and sustainable city development, and will present prototype implementation of these two platforms.
The collaboration platform for the engineering sector was developed as a part of an European project involving 22 European partners and was focused in solving collaboration challenges faced by three sectors, namely, aerospace, automotive and construction. The collaboration platform for creating sustainable cities was developed as a part of a nationally funded project involving a range of stakeholders in the city of Manchester in UK. Both projects took a problem-driven approach and worked closely with the stakeholders using real world case studies.
Professor Terrence Fernando is the Director of the ThinkLab at the University of Salford. ThinkLab combines both physical and virtual spaces to provide and innovative collaborative workspaces for innovation. Professor Fernando has a broad background in conducting multi-disciplinary research programmes involving large number of research teams in areas such as distributed virtual engineering, virtual building construction, driving simulations, virtual prototyping, urban simulation, and maintenance simulation. During 2001 and 2004, he led a regional research centre on advanced virtual prototyping, involving the Universities of Salford, Manchester and Lancaster. This EPSRC/OST funded (£1.7m) project brought together the key research teams in the region to develop visualisation and simulation technologies for product design. Furthermore as a part of the EU funded Future_Workspaces roadmap project and the MOSAIC project, Prof. Fernando brought together over 100 companies and research centres from areas such as aerospace, automotive, building construction, multi-modal interfaces, system architecture, networking, human factors to define a 10 year European vision for future collaborative engineering workspaces and mobile workspaces. This work resulted in receiving 12MEuro from EU for a project called CoSpaces IP to implement a innovative collaborative technology platform for aerospace, automotive and construction industries, involving 22 European partners. Prof. Fernando was the technical manager for the CoSpaces project leading the scientific workpackages and collaboration between the scientific teams and the industrialists. He was also a core member of the INTUITION Network of Excellence project (5MEuro) involving over 50 research centres across Europe to develop coordinated research activities on VR. This work resulted in an European Association for Virtual Reality for promoting advanced VR research in Europe. Further funding has recently been received from EU through VisonAir project to strengthen the VR infrastructure and research within Europe involving over 25 key VR centres across Europe. As a part of the EPSRC funded Vivacity project, he led the development of a collaborative urban planning environment in collaboration with the Black Country Consortium and Ordnance Survey. This work is now being further developed to support regeneration projects within Salford, involving a range of stakeholders including City Council, Police, PCT, Environment Agency. He is also leading the development of a future Command and Control system in collaboration with the Greater Manchester Police which exploiting the power of collaborative virtual environments, media streaming, tracking and advanced user interfaces. At present Prof. Fernando is also leading Virtual Futures theme within the EPSRC funded FIRM project with the view to creating new media platforms for media professionals and citizens.
Healthcare in the Information Age – Modelling Influence
Pathways for Efficient Health Interventions
Professor Paulo Lisboa
Liverpool John Moores University, UK
Healthcare delivery in the 21st century will take a radically new shape. Following the significant advances in clinical care made possible by progress in biomedicine and biomedical engineering, future emphasis will be on out-of-hospital care, with a strong participatory component. The overarching priority is to reduce costs especially from lifestyle related conditions, by investing in preventive care and personalised therapies and so minimize acute care costs, and by stopping progression to chronic illness through pro-active interventions. This talk discusses how target setting for care providers can be guided by quantitative modelling of data intelligence from healthcare observatories and hospital records, to generate insights about pathways that influence health outcomes, and to build predictive models that focus multi-sectoral interventions interfacing between public health, social care and clinical medicine. It highlights one of several related developments aimed at moving the point of care from the clinic to the individual patient, as the critical factor in the deployment of a coherent and sustainable healthcare delivery system.
Professor Paulo Lisboa is Professor in Industrial Mathematics at Liverpool John Moores University, where he heads the department of Mathematics & Statistics and also the Statistics & Neural Computation Research Group. He holds cross-Faculty positions as chair of the executive committee of the Centre for Health and Social Care Informatics and co-lead of the Medicine and Therapeutics network in the Institute for Health Research, and is Visiting Professor in the Centre for Public Health. He has over 200 refereed publications and 4 edited books. Since 2001 the research group has secured over £1.25m from the Research Councils, European Commission and industrial contracts.
He chairs the Task Force on Medical Data Analysis of the IEEE Computational Intelligence Society Data Mining Technical Committee and co-chairs the International Neural Network Society’s Special Interest Group on Computational Intelligence for the Analysis of Biopatterns, following his leadership of the Cancer track of a European Network of Excellence. He is associate editor for Neural Networks, IET-Science Measurement and Technology, Neural Computing Applications, Applied Soft Computing and Source Code for Biology and Medicine. He has chaired the Healthcare Technologies Professional Network of the IET and served in the Royal Academy of Engineering’s UK Focus for Biomedical Engineering. He is an expert evaluator for the European Community DG-INFSO and senior consultant with global organisations in clinical research and computational marketing. After completing a PhD in Theoretical Particle Physics at Liverpool University in 1983, he was a postdoctoral fellow at Bristol University before joining the electricity generation industry to research into process control, which he taught at Liverpool University from 1987. In 1996 he was appointed to the chair of Industrial Mathematics at Liverpool John Moores University. He was Head of the Graduate School during 2002-7 with institutional responsibility for academic standards in postgraduate research degree programmes across the University.
Liver Disease Classification Using Ultrasound Images
Professor Vinod Kumar
Indian Institute of Technology Roorkee, India
Liver diseases constitute an important public health issue having very high incidence in Asian countries. These are broadly categorized as diffuse and focal liver diseases. Diffuse diseases spread in entire liver lobe or in both the lobes; whereas focal diseases are localized volume patches that breaks typically the normal liver tissue periodicity. Medical imaging modalities that do not penetrate the skin physically are noninvasive. In diagnosis, noninvasive imaging techniques are used for detection of a disease during mass screening and to gather important information about the disease. Ultrasound imaging is the most preferred imaging on account of its widespread availability and low cost. The visualization of focal liver lesions is not an easy task with B-mode ultrasound because of their small size and small contrast with the liver tissue. Moreover, overlapping characteristics of sonographic visual information of different focal lesions puzzles the radiologists to distinguish them. A radiologist analyzing a large number of US images can have visual fatigue, which makes lesion harder to locate and distinguish, resulting in the possibilities of inaccurate results. Therefore, there is a need to develop a computer assisted classification system that can be used by the radiologists as a non-invasive diagnostic tool to support their observations based on characteristic visual appearance of focal liver lesions on US images.
Professor Vinod Kumar is Head of Electrical Engineering Department of Indian Institute of Technology Roorkee, INDIA. He received his school education at Ludhaina, Engineering degree from Punjab Engineering College, Chandigarh, M.Tech. & Ph.D. from IIT Roorkee (erstwhile University of Roorkee), India. He has many academic awards, distinctions and scholarships to his credit including the Khosla Research Awards of University of Roorkee, Ist IETE-R S Khandpur Medical Instrumentation Gold Medal in recognition of life time achievements and outstanding contribution in the field of Biomedical Instrumentation 2006, Railways Board Award for the best paper on vibration analysis by IE(I) 2006, KS Krishna Memorial Award of IETE, The Brij Mohanlal Award of IE (I), best paper certificates of Awards of IE (I), The Corps of Engineers Prize of IR(I) etc. He has been recognized as excellent performer for the last eight years of IIT Roorkee after University of Roorkee has been converted to IIT Roorkee.
He is the best teacher awardees of IIT Roorkee. Prof. Vinod Kumar has about 150 research papers to his credit in the area of Medical Instrumentation and Signal Processing. He has guided 22 Ph.D.s, 90 M.Tech. dissertations and more than 150 B.Tech. Projects in the area of medical instrumentation and digital signal & image processing. He has held many positions in IIT Roorkee administration i.e., Professor & Head Continuing Education Centre, Coordinator QIP Centre, Head, Information Super Highway Centre, Associate Dean Academic, Chairperson of many Committees and is member of academic committees of many educational institutions and councils in India. He has completed more than 80 assignments as consultant in diverse fields which includes development of instruments, signal processing packages, residual life assessment of power plants, e-governance and development of Virtual Labs. Presently he is involved in developing VIRTUAL Biomedical Instrumentation, Bioelectrical Signals & Image Processing, Digital Signal Processing Labs for the Undergraduate/Graduate level engineering students under the initiatives of Ministry of Human Resources Department of Government of India. He has 36 years of rich experience of teaching & research. He is a life fellow of IETE and IE(I) and is a senior member of IEEE. His areas of interest are Medical Instrumentation, Digital Signal & Image Processing..