Theodoros Arvanitis is a Reader in Biomedical Informatics, Signals and Systems and Head of the homonymous research laboratory at the School of Electronic, Electrical & Computer Engineering.
Theo has a substantial academic publication record including 1 Book, 4 Book Chapters, 2 Patent filings, 74 publications in refereed journals, 124 publications in refereed conference proceedings, 30 publications/keynote talks at un-refereed conferences and events, 11 guest editorials in journals, 17 published research reports and newsletters. He currently has 646 citations and an h-index of 14.
He has received research funding from national (EPSRC, MRC, BBSRC, NERC, MOD/DSTL, DERA, JISC), European (CEC, EU Parliament STOA, EU FP5, FP6 and FP7) and international governmental (NIH) funding agencies, charities (CRUK, Wellcome Trust, Leverhulme Trust, Birmingham Children’s Hospital Research Foundation) and industry (BT, Kodak, Nortel Networks, Microsoft Ltd., TRW-Konekt).
He is a strong proponent of health informatics translational research, especially in the areas of cancer imaging informatics and primary care informatics.
Reader in Biomedical Informatics, Signals and Systems:
• Fellow of the Royal Society of Medicine 2008
• Chartered Engineer, Institute of Engineering and Technology 2003
• DPhil in Biomedical Engineering 1997
• Ptychion (BSc equiv.) in Medical Radiologic Technology 1990
Theodoros N. Arvanitis was born in Athens, Greece, in 1968 and he currently holds a UK citizenship (dual UK-Greek National). He received his RT (BSc) degree (medical radiological technology) in 1990, from the Technological Educational Institute of Athens, Greece, and his DPhil (biomedical engineering) in 1997 from the University of Sussex, UK.
His postdoctoral work at the University of Sussex included a lab director/research fellow post at the Trafford Centre for Medical Research (1995) and a full-time lectureship in the School of Cognitive and Computer Sciences (1995-1998). In 1998, he joined the School of Electronic, Electrical & Computer Engineering, University of Birmingham, UK, as a full-time Lecturer and he progressed to the level of Senior lecturer thereafter.
He is currently holding the post of Reader in Biomedical Informatics, Signals and Systems, leading the homonymous research laboratory at the same academic School. He is also the Director of the Centre for Learning, Innovation and Collaboration at the University of Birmingham, UK (until September 2011).
He also holds an Honorary Research Scientist’s post at the Institute of Child Health, Birmingham Children’s Hospital, working with the Paediatric Oncology Research Group.
His research interests include biomedical imaging and spectroscopy, biomedical informatics, e-health and telemedicine, systems biology, complex adaptive systems and intelligent agents, communication and computer networks, human factors and systems engineering. His teaching is within the disciplines of software engineering and medical informatics.
• UG Electronic and Electrical Engineering degrees
• UG Communications Systems Engineering degrees
• UG Computer Engineering degrees.
• MSc degrees
Theo is interested in supervising doctoral research students in the following areas:
Clinical information systems for decision support, e-health training, the electronic healthcare record, communication technologies in healthcare, e-trials applications, technology enhanced evidence-based medicine applications, biomedical imaging (MRI and MRS), computational support for metabolomics, computational support for neuroscience, networks science and distributed systems, intelligent agents & complex adaptive systems.
If you are interesting in studying any of these subject areas please contact Theo Arvanitis on the contact details above, or for any general doctoral research enquiries, please email: email@example.com or call +44 (0)121 414 4288.
For a full list of available Doctoral Research opportunities, please visit our Doctoral Research programme listings.
Health Informatics and e-health: clinical information systems for decision support, e-health training, the electronic healthcare record, communication technologies in healthcare, e-trials applications, technology enhanced evidence-based medicine applications, systems engineering approaches in both biological and medical applications (systems and synthetic biology), biomedical image and signal processing and data standardisation, biomedical imaging (MRI and MRS), computational support for metabolomics, computational support for neuroscience.
Systems Engineering: Networks science and distributed systems, intelligent agents & complex adaptive systems, human factors and interactive systems software design.
CURRENT RESEARCH ACTIVITY
Development and evaluation of MR based functional imaging for the enhanced management of childhood cancer – a Children’s Cancer and Leukaemia Group initiative (2009-2014)
Cancer is the most common cause of death from disease in children, with most cancers being solid tumours. Conventional MRI is an essential part of clinical management but provides limited, mainly anatomical, information. Magnetic resonance spectroscopy (MRS), diffusion and perfusion MRI probe tissue metabolism and physical and vascular structure forming part of a genre of methods termed functional imaging. Clinical studies show they have the potential to improve cancer patient management, but their routine multi-centre clinical use is hampered by technical difficulties of translation and standardisation. Multicentre evaluation is essential for paediatric cancer studies due to the small numbers of cases in any one centre. The Children’s Cancer and Leukaemia Group (CCLG) lead UK multi-centre clinical trials for paediatric cancers. The CCLG have formed a FI Group (FIG) to develop and evaluate functional imaging for diagnosis, management and understanding childhood cancer, with trials underway using 1H MRS MRS in brain tumours. A CRUK/EPSRC Funded program grant expands the current activities of the FIG to other MR methods and to extracranial tumours.
Translational Research and Patient Safety in Europe TRANSFoRm (2010-2015)
TRANSFoRm develops rigorous, generic methods for the integration of Primary Care clinical and research activities, to support patient safety and clinical research via:
1. Rich capture of clinical data, including symptoms and signs rather than just a single diagnosis. A generic, dynamic interface, with potential to operate with any electronic health record (eHR), will facilitate both diagnostic decision support and identification of patients eligible for research, thus enhancing patient safety.
2. Distributed interoperability of eHR data and other data sources that maintain provenance, confidentiality and security. This will enable large-scale phenotype-genotype association studies and follow up of trials.
3. Software tools and services to enable use of controlled vocabulary and standardised data elements in clinical research. This will enable integration and reuse of clinical data.
Multi-modal imaging techniques at CNCR
Developing procedures for multi-modal imaging, combining the time course of EEG with spatial resolution of MRI, and combined MRI and Trans-cranial Magnetic Stimulation to provide improved analyses of neurological disorders and ageing. The research focus is in the fusion of fMRI, EEG, diffusion tensor imaging and magnetic resonance spectroscopy (MRS), applied to understanding cognition after brain injury, epilepsy, in adults and children.
• Member of various Scientific Conference Committees in the areas of e-health, e-learning and software engineering
• Member of the EPSRC College (2003 - 2005) and (2010 – today)
• Sir William Siemens National Medal Programme, University of Birmingham’s participation co-ordinator (1998 – today)
• Fellow of the Society for the Internet in Medicine (1995 -2009)
• National Institutes of Health (NIH - USA) Roadmap Programme Interoperability Working Group Member (2005 –2008).
1. M. Wilson, G. Reynolds, R. A. Kauppinen, T. N. Arvanitis, and A. C. Peet (2011), A constrained least-squares approach to the automated quantitation of in vivo 1H magnetic resonance spectroscopy data, Magnetic Resonance in Medicine, 65: 1–12.
2. M. Wilson, N. P. Davies, Y. Sun, K. Natarajan, T. N. Arvanitis, R. A. Kauppinen and A. C. Peet (2010), A comparison between simulated and experimental basis sets for assessing short-TE in vivo1H MRS data at 1.5 T, NMR in Biomedicine, 23: 1117–1126.
3. J. M Easton, L. M Harris, M. R Viant, A. C Peet and T. N Arvanitis (2010)Linked Metabolites: A Tool for the Construction of Directed Metabolic Graphs, Computers in Biology and Medicine, 40(3): 340-349.
4. N. P. Davies, M. Wilson, K. Natarajan, Y. Sun, L. MacPherson, M-A. Brundler, T. N. Arvanitis, R. G. Grundy and A. C. Peet (2010), Non-invasive Detection of Glycine as a Biomarker of Malignancy in Childhood Brain Tumours Using In-Vivo 1H MRS at 1.5 Tesla and Ex-Vivo High-Resolution Magic-Angle Spinning NMR, NMR in Biomedicine, 23(1): 80-87.
5. R. Kunz, E. Nagy, S. F.P.J. Coppus, J. I. Emparanza, J. Hadley, R. Kulier, S. Weinbrenner, T. N. Arvanitis, A. Burls, J. B. Cabello, T. Decsi, A. R. Horvath, J. Walzak, M. P. Kaczor, G. Zanrei, K. Pierer, R. Schaffler, K. Suter, B. W.J. Mol and Khalid S (2009). Khan, How far did we get? How far to go? A European survey on post-graduate courses in evidence-based medicine, Journal of Evaluation in Clinical Practice, 15(6): 1196-1204.
6. J. Hao, X. Zou, M. P. Wilson, N. P. Davies, Y. Sun, A. C. Peet and T. N. Arvanitis (2009), A Comparative Study of Feature Extraction and Blind Source Separation of Independent Component Analysis (ICA) on Childhood Brain Tumour 1H Magnetic Resonance Spectra, NMR in Biomedicine, 22(8): 809-818.
7. S. Thangaratinam, G. Barnfield, S. Weinbrenner, B. Meyerrose, T.N. Arvanitis, A. R. Horvath, G. Zanrei, R. Kunz, K. Suter, J. Walczak, A. Kaleta, K. Oude Rengerink, H. Gee, B.W.J. Mol and K.S. Khan (2009), Teaching trainers to incorporate evidence-based medicine (EBM) teaching in clinical practice: the EU-EBM project, BMC Medical Education, 9: 59.
8. H. González-Vélez, M. Mier, M. Julià-Sapé, T. N. Arvanitis, J. M. García-Gómez, M. Robles, P. H. Lewis, S. Dasmahapatra, D. Dupplaw, A. Peet, C. Arús, B. Celda, S. Van Huffel and M. Lluch-Ariet (2009), HealthAgents: distributed multi-agent brain tumor diagnosis and prognosis, Applied Intelligence, 30(3): 191-202.
9. T. G. Payne, A. D. Southam, T. N. Arvanitis, and M. R. Viant (2009), A Signal Filtering Method for Improved Quantification and Noise Discrimination in Fourier Transform Ion Cyclotron Resonance Mass Spectrometry-Based Metabolomics Data, Journal of the American Society for Mass Spectrometry, 20(6): 1087-1095.
10. N. S. Taylor, R. J. M. Weber, A. D. Southam, T. G. Payne, O. Hrydziuszko, T. N. Arvanitis and M. R. Viant (2009), A New Approach to Toxicity Testing in Daphnia Magna: application of high throughput FT-ICR mass spectrometry metabolomics, Metabolomics, 5(1): 44-58.