Speakers

July 12, 2012
 




Michael Miller
Herschel and Ruth Seder Professor of Biomedical Engineering, Professor of Electrical and Computer Engineering, Director, Center for Imaging Science, Gilman Scholar, Johns Hopkins University


Michael Miller is the Herschel and Ruth Seder Professor in the Department of Biomedical Engineering and director of the Center for Imaging Science in the Whiting School. In March 2011, Miller was also named a JHU Gilman Scholar.
The biomedical engineer is a recognized leader and pioneer in areas of image understanding, pattern theory, computer vision, medical imaging/computational anatomy and computational neuroscience. He joined the Johns Hopkins faculty in 1998, returning to the Homewood campus 14 years after completing his doctorate there.

Miller has co-authored more than 100 peer-reviewed archival publications and is the co-author of two textbooks, Random Point Processes in Space and Time and Pattern Theory: From Representation to Inference.

He has received numerous honors for his work, including the national IEEE Biomedical Engineering Thesis Award first prize in 1982, the Johns Hopkins Paul Ehrlich Graduate Student Thesis Award in 1983 and the Presidential Young Investigator Award in 1986. In 2002, he was recognized by ISI Essential Science Indicators for garnering the highest rate of increase in total citations in the field of engineering, and in 2003 he received the International Man of the Year Award from the International Biographical Center in Cambridge, England. 






Louis Collins
Professor, Biomedical Engineering, Neurology & Neurosurgery, and  Medical Physics at McGill University, associate member of the Center for Intelligent Machines at Mcgill and associate member for the McGill Center for studies on aging

Louis Collins a professor in the departments of Biomedical Engineering, Neurology & Neurosurgery, and  Medical Physics at McGill University of Montreal, Canada, associate member of the Center for Intelligent Machines at Mcgill and associate member for the McGill Center for studies on aging. He works at the McConnell Brain Imaging Centre of the Montreal Neurological Institute (MNI) and heads the Image Processing Laboratory at the MNI, with a group of 15-20 people.
His research involves automated anatomical segmentation and atlasing of medical imaging data applied to healthy and unhealthy brains for neurological diseases and in image-guided neurosurgery (IGNS). His group develops computerized image processing techniques such as non-linear image registration, model-based segmentation and appearance-based segmentation to automatically identify, quantify and characterize structures within the human brain. These techniques are applied to large databases of magnetic resonance (MR), computed tomography (CT) and ultrasound (US) data from normal subjects to quantify anatomical variability and to characterize the morphological changes associated with development, aging and disease. The data derived can be used for diagnosis and prognosis and to help study natural history of disease and to improve understanding of disease pathology. In image-guided neurosurgery, these techniques provide the surgeon with computerized tools to assist in interpreting anatomical, functional and vascular image data, permitting the effective planning and execution of minimally invasive neurosurgical procedures. 


                    

 




Kaleem Siddiqi

Professor and Associate Director Research, School of Computer Science, McGill University


Professor Siddiqi's research focuses on visual shape analysis for computer vision, drawing on techniques from singularity theory, partial differential equations and graph theory. He is also interested in the application of curve and surface evolution techniques to problems in image processing and medical image analysis, as well as in the psychophysics of shape perception. His research interests include Computer Vision, Medical Image Analysis, Computer Graphics, Pattern Recognition, and Artificial Intelligence. 





Oleg Michailovich
Assistant Professor, Electrical and Computer Engineering, University of Waterloo

Dr. Michailovich holds a double M.Sc. degree in Electrical Engineering (magna cum laude) and Biomedical Engineering from the Saratov State University (Russian Federation) and the Technion - Israel Institute of Technology (IIT), respectively. He received his Ph.D. degree in Biomedical Engineering (with distinction) from the Technion - IIT in 2003. In the period 2003-2006, Dr. Michailovich was part of Allan Tannebaum's lab (Department of Electrical and Computer Engineering (ECE), Georgia Tech), where he worked on various problems in visual-based control and medical imaging as a post-doctoral fellow. Since 2007, Dr. Michailovich works as an Assistant Professor at the Department of ECE at the University of Waterloo. His research interests include the application of signal and image processing to various problems of image reconstruction, segmentation, inverse problems, non-parametric estimations, approximation theory and multiresolution analysis, with a special emphasis on medical imaging of the brain.

 

Simon Warfield
Professor of Radiology at Harvard Medical School, Director of Radiology Research, and Director of the Computational Radiology Laboratory (CRL) in the Department of Radiology at Children’s Hospital


Dr. Warfield serves as the Harvard CTSA Imaging Site Director for BCH, and facilitates research imaging across Harvard affiliated hospitals with colleagues at MGH, BWH and BIDMC.
His research interests in the field of medical image computing have focused on the development of innovative algorithms to address the requirements of clinical care and translational research in medicine. A recent research focus has been improved strategies for pediatric image acquisition, including novel sequences that integrate with motion tracking hardware to enable motion-robust acquisitions, and motion robust reconstruction techniques optimized for fetal imaging. Dr. Warfield has developed quantitative analysis approaches for automatic structural MRI segmentation by optimal label fusion, for brain parcellation, and for delineation of lesions. Improved imaging and quantitative analysis approaches have enabled the development of patient-specific models of brain geometry and conductivity, which in turn have enabled improved localization of epileptogenic sources in pediatric epilepsy patients. Novel diffusion imaging and analysis techniques have enabled improved characterization of multiple white matter fascicles, the automated delineation of particular white matter fascicles, and the development of sophisticated approaches for nonrigid registration and atlas construction exploiting multiple white matter fascicle models. Advances in super-resolution MRI have enabled the acquisition of structural MRI and diffusion MRI with unprecedented spatial resolution. The application of this suite of algorithms has enabled the characterization of early brain development, the identification of strategies for improved care in the neonatal intensive care unit, and the characterization of white matter microstructural changes in subjects with autism spectrum disorders.




Dimitri Van De Ville
Tenure-Track Assistant Professor at the University of Geneva (Faculty of Medicine, Department of Radiology) and the EPFL (School of Engineering, Institute of Bioengineering)

Dimitri Van De Ville (M’02) received the M.S. degree in engineering and computer sciences and the Ph.D. degree from Ghent University, Belgium, in 1998, and 2002, respectively. After a post-doctoral stay (2002-2005) at the Biomedical Imaging Group of Prof. Michael Unser at the Ecole Polytechnique Fédérale de Lausanne (EPFL), Switzerland, he became responsible for the Signal Processing Unit at the University Hospital of Geneva, Switzerland, as part of the Centre d’Imagerie Biomédicale (CIBM). In 2009, he has been the recipient of a Swiss National Science Foundation professorship and currently holds a joint position at the University of Geneva, Switzerland, and the EPFL. His research interests include wavelets, sparsity, pattern recognition, and their applications in biomedical imaging, such as functional magnetic resonance imaging. He has received the Pfizer Research Award 2012 in the category Neurosciences for his work on scale-free dynamics of EEG microstates. 
Dr. Van De Ville served as an Associate Editor for the IEEE TRANSACTIONS ON IMAGE PROCESSING from 2006 to 2009 and the IEEE SIGNAL PROCESSING LETTERS from 2004 to 2006. He is currently serving as the Chair of the Bio Imaging and Signal Processing (BISP) TC of the IEEE Signal Processing Society (2012-2013). Since 2003, he has also been an Editor and Webmaster of The Wavelet Digest. He is a Guest Co-Editor of the 2011 Special Issue on Brain Decoding in Pattern Recognition. He is Co-Chair of the biennial Wavelets series conferences since 2007, together with V. Goyal (MIT) and M. Papadakis (UHouston).

Link: http://miplab.epfl.ch/



July 13, 2012
 



 
Stephen Strother
Professor of Medical Biophysics, University of Toronto

Professor Strother studied Physics and Mathematics at Auckland University, New Zealand, and received a PhD in Electrical Engineering from McGill University, Montreal in 1986. After a fellowship at Memorial Sloan Kettering Cancer Center, New York he joined the VA Medical Center, Minneapolis as senior PET Physicist, and the University of Minnesota where he became Professor of Radiology. In 2004 he moved to Toronto as a senior scientist at the Rotman Research Institute, Baycrest where he is Associate Site Leader in the multi-institutional Centre for Stroke Recovery (CSR), and Professor of Medical Biophysics at the University of Toronto. His research interests include neuroinformatics with a focus on statistical learning techniques for optimization of PET and fMRI neuroimaging pipelines for research and clinical applications applied to the aging brain. He initiated and has led the neuroinformatics developments within CSR and RRI, Baycrest since 2007. He is also a cofounder of Predictek, Inc., and ADMdx in Chicago, medical analysis and diagnostics companies, an Associate Editor for Human Brain Mapping, and a past member of the Neurotechnology Review Committee and a past chairman of an international Neuroinformatics Standards Committee, both at the National Institutes of Health, USA.




 

 
Martin J McKeown
Professor of Medicine (Neurology) & Clinical Director, Pacific Parkinson's Research Centre, Associate Member, Department of Electrical and Computer Engineering Brain Research Centre, University of British Columbia (UBC)

Martin J. McKeown graduated summa cum laude in Engineering Physics from McMaster University in 1986, and subsequently earned his MD degree from the University of Toronto in 1990. From 1990-1994 he specialized in neurology at the University of Western Ontario, and later did a fellowship in clinical electrophysiology. He is Board Certified in neurology in Canada and the US, and has been an examiner for the US Neurology Board certification. From 1995-98, he was a research associate at the Computational Neurobiology Lab, Salk Institute for Biology Studies, San Diego. From 1998-2003 he was an assistant professor of Medicine at Duke University, core faculty at Duke’s Brain Research and Analysis Center, as well as an adjunct professor in Biomedical Engineering and Duke’s Center for Neural Analysis. He is currently a movement disorder specialist and Clinical Director at the Pacific Parkinson’s Research Center, a Professor of Medicine (Neurology), Associate Member of the Department of Electrical and Computer Engineering, and faculty member of the Brain Research Centre at the University of British Columbia. He has been the Principal Investigator (PI) on peer-reviewed grants from the National Institutes of Health (NIH: US), the Whitaker Foundation (US), the National Parkinson’s Foundation (NPF: US), the Canadian Foundation for Innovation (CFI), the Canadian Institute of Health Research (CIHR), the Michael Smith Foundation for Health Research (MSFHR) the National Science and Engineering Research Council (NSERC), the Parkinson’s Society of Canada and the Parkinson’s Society of British Columbia. In addition to his clinical duties, where he sees mostly people with Parkinson’s disease, he supervises graduate students in Neuroscience and co-supervises graduate students in Electrical and Computer Engineering.




 




 
Farouk Nathoo
Associate Professor in the Department of Mathematics and Statistics at the University of Victoria

Farouk Nathoo is Associate Professor in the Department of Mathematics and Statistics at the University of Victoria. He received his B.Sc. (combined honors) in Mathematics and Statistics from the University of British Columbia (1998), an M.Math. in Statistics from the University of Waterloo (2000), and his Ph.D. in Statistics from Simon Fraser University (2005). His research interests lie in the development of statistical methods for spatial and longitudinal data, neuroimaging statistics, disease mapping, and Bayesian methods.



 





Hervé Abdi
Full Professor,
School of Behavioral and Brain Sciences, University of Texas at Dallas, adjunct Professor of Radiology,
University of Texas Southwestern Medical Center at Dallas

Hervé Abdi received an M.S. in Psychology from the University of Franche-Comté (France) in 1975, an M.S. (D.E.A.) in Economics from the University of Clermond-Ferrand (France) in 1976, an M.S. (D.E.A.) in Neurology from the University Louis Pasteur in Strasbourg (France) in 1977, and a Ph.D. in Mathematical Psychology from the University of Aix-en-Provence (France) in 1980. He was an assistant professor in the University of Franche-Comté (France) in 1979, an associate professor in the University of Bourgogne at Dijon (France) in 1983, a full professor in the University of Bourgogne at Dijon (France) in 1988. He is currently a full professor in the School of Behavioral and Brain Sciences at the University of Texas at Dallas and an adjunct professor of radiology at the University of Texas Southwestern Medical Center at Dallas. He was twice a Fulbright scholar.  He has been also a visiting scientist or professor in Brown University, the Rotman Institute (Toronto, CA),  the ``Conservatoire des Arts et Métiers” (CNAM, Paris), and in the Universities of Chuo (Japan), Dijon (France), Geneva (Switzerland), Nice Sophia-Antipolis (France), Paris Ouest (Nanterre), and Paris 13 (France). His recent work is concerned with brain imaging and genomics methodology and with face and person perception and memory, odor perception, and with computational modeling of these processes. He is also developing statistical techniques to analyze the structure of large data sets as found, for example, in brain imaging, genetic studies, and sensory evaluation (e.g., pls-regression, statis, discriminant correspondence analysis, multiple factor analysis, additive tree representations,...). He has published over 200 papers (plus eleven books and six edited volumes) on these topics. He teaches or has taught classes in cognition, computational modeling, experimental design, multivariate statistics, and the analysis of brain imaging data. 

 




 
Jean-Baptiste Poline

Researcher at CEA-Neurospin and UC Berkeley


Jean-Baptiste Poline obtained an Engineering degree in computer science and electronics in 1989, and a master degree in Biomathematics in 1990 (University Paris Diderot). During his PhD, he worked on the detection of brain activation in Positron Emission Tomography images in Orsay, SHFJ, and graduated in 1993. From 1994 to 1997, he was a post-doctoral fellow at the Hammersmith hospital and then the Functional Imaging Laboratory in London, working with R. Frakowiack and K. Friston. He returned to Orsay and then move to Neurospin in 2006 to work on fMRI data analyses and on imaging genetics. He was elected Secretary General of the Organisation of the Human Brain Mapping conference in 2009-2011 and is currently a member of the Governing board of the International Neuroinformatics Coordinating Facility and co-leading the neuroimaging datasharing task force. He has authored or co-authored more than 100 publications. He is currently spending a year at UC Berkeley Brain Imaging Center.
 

Chief Executive Officer and Director of Image Analysis and MR Research at the Mind Research Network and Professor in the Departments of Electrical and Computer Engineering (primary), Neurosciences, Psychiatry and Computer Science at the University of New Mexico

Vince Calhoun received a bachelor’s degree in Electrical Engineering from the University of Kansas, Lawrence, Kansas, in 1991, master’s degrees in Biomedical Engineering and Information Systems from Johns Hopkins University, Baltimore, in 1993 and 1996, respectively, and the Ph.D. degree in electrical engineering from the University of Maryland Baltimore County, Baltimore, in 2002. He worked as a research engineer at the psychiatric neuroimaging laboratory at Johns Hopkins from 1993 until 2002. He then served as the director of medical image analysis at the Olin Neuropsychiatry Research Center and as an associate professor at Yale University.

Dr. Calhoun is currently Chief Executive Officer and Director of Image Analysis and MR Research at the Mind Research Network and is a Professor in the Departments of Electrical and Computer Engineering (primary), Neurosciences, Psychiatry and Computer Science at the University of New Mexico. He is the author of more than 220 full journal articles and over 350 technical reports, abstracts and conference proceedings. Much of his career has been spent on the development of data driven approaches for the analysis of brain imaging data. He has won over $18 million in NSF and NIH grants on the incorporation of prior information into independent component analysis (ICA) for functional magnetic resonance imaging, data fusion of multimodal imaging and genetics data, and the identification of biomarkers for disease.
Dr. Calhoun is a senior member of the IEEE, the Organization for Human Brain Mapping, the International Society for Magnetic Resonance in Medicine, and the American College of Neuropsychopharmacology. He is a chartered grant reviewer for NIH. He has organized workshops and special sessions at multiple conferences. He is currently serving on the IEEE Machine Learning for Signal Processing (MLSP) technical committee and previous served as the general chair of the 2005 meeting. He is a reviewer for many journals is on the editorial board of the Brain Connectivity, Neuroimage journals and serves as Associate Editor for several other journals. 
   

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