Prof. Nikolas Bourbakis
Wright State University, OH, USA
Dr. Nikolaos Bourbakis (IEEE Fellow) is an OBR Distinguished Professor of IT and the Director of the Assistive Technologies Research Center (ATRC) at Wright State University, OH. He pursues research in Applied AI, Machine Vision, Bioinformatics & Bioengineering, Assistive Technologies, Information Security, and Parallel- Distributed Processing funded by USA and European government and industry. He has published more than 330 articles in refereed International Journals, book-chapters and Conference Proceedings, and 10 books as an author, co-author or editor. He has graduated 16 Ph.Ds and 35 Master students. He is the founder and the EIC of the International Journal on AI Tools, the Editor-in-Charge of a Research Series of Books in AI (WS Publisher), the Founder and General Chair of several International IEEE Computer Society Conferences, Symposia and Workshops, an Associate Editor in several IEEE and International Journals and a Guest Editor in 18 journals special issues. His research work has been internationally recognized and has won several prestigious awards. Some of them are: IBM Author recognition Award 1991, IEEE Computer Society Outstanding Contribution Award 1992, IEEE Outstanding Paper Award ATC 1994, IEEE Computer Society Technical Research Achievement Award 1998, IEEE ICTAI 10 years Research Contribution Award 1999, ASC Award for Assistive Technology 2005, University of Patras Degree of Recognition 2007.
Wireless Capsule Endoscopy: Imaging Techniques and Systems
Nikolaos Bourbakis, ATRC, Wright State University
Abstract:
Wireless Capsule Endoscopy (WCE) is a new technology that allows medical personnel to view the gastrointestinal (GI) mucosa. It is a swallowable camera capsule that transmits thousands of screenshots of the digestive tract to a wearable receiver. When the procedure finishes the video is uploaded to a workstation for viewing. Capsule Endoscopy has been established as a tool to identify various gastrointestinal (GI) conditions such as blood-based abnormalities, polyps, ulcers, Crohn’s disease.
Although the companies (Given Imaging, Olympus, etc) have developed software useful for viewing WCE videos, the viewing process is still a time consuming process (1-2 hours) even for experienced gastroenterologists. Therefore, the need for computer aided detection (CAD) software is clearly obvious. Software research has been carried out on: a) the automatic detection of malignant intestinal features like polyps, bleeding, and abnormal regions (tumors) and b) finding the boundaries of the digestive organs. Our approach to the problem of reducing the examination time has led to the development of ATRC Video Toolbox - ATRC-VT. ATRC-VT incorporates signal processing methods, color and image processing techniques, and artificial intelligence tools to detect blood-based abnormalities, polyps and ulcers in the small intestine.
Thus, this talk will cover a short overview of WCE imaging techniques and systems. The ATRC-VT methodology for detecting abnormalities will be presented. Finally open issues and future directions will be also discussed.
Prof. George D. Sergiadis
Aristotle University of Thessaloniki, Greece
George D. Sergiadis took his diploma in Electrical Engineering from the Aristotle University of Thessaloniki, Greece, in 1978, and his PhD from “Ecole Nationale Supérieure des Télécommunications”, Paris France, in 1982. He worked with Thomson CsF, in France, until 1985, participating in the development of the French Magnetic Resonance Scanner. Since 1985 he is with the Aristotle University of Thessaloniki, Greece, teaching Telecommunications and Biomedical Engineering, now as full Professor. For 3 years he served also as the Director of the Telecommunications Department. He is currently the director of the Signal Processing and Biomedical Engineering Laboratory. He has developed the Hellenic TTS engine “Esopos”, and designed the mobile communications for the Athens Olympic Games in 2004. His current research interests include fuzzy image processing and wireless communications. During the academic year 2004-2005 was a visiting researcher at Media Lab, MIT, Cambridge, USA.Dr. Sergiadis is a member of IEEE,TEE, ATLAS, SMRM, ESMRM, EMBS, and SCIP.
Dr. Ioannis S. Gousias
ICL, University College (London) UK
Dr. Ioannis Spyridon Gousias, first in rank graduate student of the Experimental High School of Anavryta and holder of a Diploma in Electrical and Computer Engineering from the National Technical University of Athens, completed his postgraduate studies in Neuroscience in Imperial College London (MSc in Integrative Neuroscience) with Outstanding Distinction and ranked first among all the postgraduate students. He completed his PhD in Medicine in ICL, in collaboration with the MRC Clinical Sciences Centre and the Department of Pediatrics in Hammersmith Hospital, the Department of Computing in ICL and the Institute of Child Health in the University College London, funded by the Arnaoutis Foundation, the Engineering and Physical Sciences Research Council UK (EPSRC) and the Medical Research Council UK (MRC). Dr Gousias works on anatomical modeling and brain mapping of premature infants, infants of normal gestational period and children up to the age of 6 years, implementing, improving and developing the algorithms and methods he has already established and has been using for adult brain mapping and probabilistic anatomical brain atlasing. Also, combining brain atlasing with probabilistic tractography and networks theory, he monitors the development of the “network” of the brain and its components. Basic aim of his research is the linkage between anatomical findings and clinical and neuropsychological examinations, the combination of anatomical and functional brain imaging, as well as the monitoring of the normal or abnormal development of the brain from the age of birth till adulthood, based on clinical, qualitative and quantitative data. He continues his postdoctoral research as a research fellow in ICL, winning a very competitive grant from the organization Action Medical Research. He won the first prize during the Young Scientist’s Day in London for 2007. He was awarded as Neuroscientist of the Year in the United Kingdom for 2007. Ηe was the official representative of the United Kingdom in the annual meeting of the Nobel Laureates with the world’s most talented and ingenious young scientists, after national selection and final world judgment by the Council of the Nobel Laureates. He was awarded as New Investigator in the Annual World Conference on Paediatrics of 2007. His research was on the front cover of the scientific journal NeuroImage in April 2008. In 2009 he won the “NOBELini” prize. He is an advanced violin player, speaks five languages and has served as President in the European Youth Parliament.
Prof. W. Yang
University of Manchester, UK
Professor Wuqiang Yang is a Fellow of IET (formerly IEE) and a Senior Member of IEEE. He graduated from Tsinghua University in Beijing, and received BEng (with Distinction) in instrumentation and process control in 1982, MSc and PhD (with Distinction) in navigation and control in 1985 and 1988, respectively. He was a Lecturer at Tsinghua University from 1988 to 1991. Since then, he has been working with The University of Manchester (formerly UMIST), which is highly ranked in the 2008 Research Assessment Exercise in the UK. In 2006, he took sabbatical leave at MIT as a visiting professor. He has published over 200 papers. His main research interests include industrial process tomography, especially electrical capacitance tomography (ECT), image reconstruction algorithms, sensing and data acquisition systems, electronic circuit design, instrumentation and multiphase measurement.
Professor Yang is a Chartered Engineer, referee for 30 professional journals and book publishers, science advisor to Chinese Academy of Sciences, guest/visiting professor at Tsinghua University Graduate School in Shenzhen, Tianjin University, ShangQiu Normal University and North University of China, editorial board member of Sensor Review journal and Sensors, Transducers journal and Journal of Measurement Science and Instrumentation, Guest Editor of Measurement Science and Technology journal and IET Image Processing journal, and panel member of Natural Science Foundation of China (NSFC). He received 1997 IEE/NPL Wheatstone Measurement Prize, 1997 Honeywell Prize from the Institute of Measurement and Control, 2000 IEE Ayrton Premium, Global Research Award from the Royal Academy of Engineering in 2006, and 2009 Highly Commended for IET Innovation Award. His biography has been included in Who’s Who in the World, Who’s Who in America, and Who’s Who in Science and Engineering since 2002.
Prof. Yon Yan
University of Kent, UK.
Professor Yong Yan is Head of Instrumentation, Control and Embedded Systems Research Group and the Director of Research at the School of Engineering, the University of Kent, UK. He received the B.Eng. and M.Sc. in instrumentation and control engineering from Tsinghua University, China in 1985 and 1988, respectively, and the Ph.D. degree in flow measurement from the University of Teesside, UK in 1992. Prof. Yan started his academic career in 1988 as an Assistant Lecturer at Tsinghua University. In 1989 he joined the University of Teesside as a Research Assistant. After a short period of postdoctoral research, he worked initially as a lecturer at Teesside during 1993-1996, and then as a senior lecturer, reader and professor, respectively, with the University of Greenwich, UK during 1996-2004. He has published in excess of 250 research papers in addition to 12 research monographs. He serves as a member of editorial boards for Flow Measurement and Instrumentation and Chinese Journal of Scientific Instruments and has been a guest editor for Measurement Science and Technology on several occasions. Prof. Yan is a Fellow of the Institution of Engineering and Technology (formerly IEE), the Institute of Physics, and the Institute of Measurement and Control, UK. He is a member of the Innovation R&D Metrology Working Group and the Engineering & Flow Working Group of the UK National Measurement Office. He was appointed as Kuang-Piu Guest Professor at Zhejiang University and Yangtzi Scholar Professor at Tianjin University, China in 2005 and 2006, respectively. In recognition of his contributions in particle flow measurement and combustion flame imaging, he was awarded the Achievement Medal by the IEE in 2003, the global Engineering Innovation Prize by the IET in 2006, and Rushlight Commendation Award in 2009. His contribution in engineering education was recognized by a national award from the Royal Academy of Engineering in 2007.
Dr. G. Zentai
Varian Medical Systems, USA
George Zentai joined Varian Medical Systems’ Ginzton Research Center (Mountain View, California) in 1998. He is a Senior Scientist and has been working as R&D Program Manager of Direct X-ray Sensor Development Projects. His team developed x-ray imagers both for medical and security applications, which went into production at Varian.
He gave many conference presentations; some of them invited ones, wrote several publications, and have many patents in the X-ray imaging field. He has also been involved in the development of low noise readout electronics, ASICs for flat panel digital imagers and special electronic testing methods. He has many years experience in photoconductor based imagers.
He has a Masters Degree in Electronics and a Ph.D. in Amorphous Semiconductors.
Previously he was Manager of Flat Panel X-ray Sensor Development at OIS (Optical Imaging Systems) and a visiting scientist at Argonne National Laboratory.
He is member of SPIE, and he became IEEE Fellow in January 2010 for his contributions to the advancement of digital X-ray imagers. He is member of organizing and technical committees and co-chair of SPIE and IEEE conferences and reviewer of several IEEE journals.
Prof. M. Pastorino
University of Genoa, Italy
Hybrid Reconstruction Techniques for Microwave
Imaging Systems
M. Pastorino
Abstract:
Short-range microwave imaging systems are used to inspect dielectric and conducting scatterers by using interrogating waves in the microwave range. The target to be inspected is illuminated by an incident field produced by a transmitting antenna. The incident wave interacts with the target under test and produces a scattered field. Samples of the scattered field are collected by one or more receiving antennas, often moving around the target in order to collect multiview information (tomography). The properties of the body to be inspected and the scattered field are related by a couple of well known integral equations. Consequently, one of the key aspects of microwave imaging systems is the "inversion" of those relationships.
Several different approaches have been proposed for solving this inverse problem, which is quite complex due to the ill-posedness and nonlinearity of the involved equations. Unfortunately, efficient "general purpose" microwave imaging techniques cannot be developed. Consequently, the need for specific application-oriented methods is widely recognized. The key idea is to combine different imaging modalities in order to take profit from the specific features of the different methods and improve the effectiveness of the inspection. In this framework, the present paper is aimed at discussing hybrid reconstruction techniques that have been recently proposed for microwave imaging.
The category of hybrid methods could include, for example, two-step procedures in which fast qualitative algorithms (e.g., the Linear Sampling Method) are combined with quantitative methods (e.g., the Gauss-Newton method) in order to first derive the supports of the unknown scatterers and successively retrieve the distributions of their dielectric parameters. Other approaches can mix different quantitative procedures. For example, deterministic and stochastic algorithms can be combined in order to speed up the convergence of slow and computationally expensive stochastic methods near the global solution. The simplest way to implement this strategy is just to start the local search when the stochastic method (e.g., a Genetic Algorithm) has reached a reasonably basin of attraction, i.e. a region of the space solution where the global minimum is likely included. The same basic idea is applied in the so-called Memetic Algorithm, which is a stochastic population-based method, in which the elements of the populations are local minima obtained by a deterministic procedure (e.g., a conjugate gradient method).
Although the definition of a hybrid method is quite an arbitrary task, some examples are reported in the paper with reference to applications in the field of industrial and civil engineering, buried object detection, and medical diagnostics.