Invited Speakers

Bruce R. Rosen, M.D. Ph.D.

Professor of Radiology and Health Sciences & Technology, Harvard Medical School & Massachusetts General Hospital

Talk Title: Advances in Functional Neuroimaging

By enabling visualization of physiological processes, functional imaging has dramatically enhanced our ability to explore and thus better understand human diseases. The evolution of functional MRI (fMRI) in the early 1990s revolutionized the neuroimaging field, enabling dynamic measurement of the neurovascular changes coupled to changes in brain activity through high spatial resolution tomographic imaging. In the nearly 20 years since the landmark experiments were first reported, functional imaging research has grown phenomenally, and fMRI has become the keystone of a broad array of functional imaging methods that are revealing the links between brain and behavior. Very high strength gradients, phased-array coils, and other advances at 3T and 7T enable ultra-high resolution MRI and fMRI; Positron emission tomography (PET) imaging provides the means to map neurochemical events with exquisite sensitivity – when integrated directly with MR, it should enable entirely new classes of experiments in neurochemical dynamics; tomographic optical imaging increase resolution and physiological range in vivo and in vitro; and densely sampled whole-head magnetoencepholography permits high temporal resolution mapping of brain activity. These techniques have bridged a critical gap between the spatiotemporal resolution of systems-level tomographic imaging and circuit-level mechanistic neural models, allowing direct visualization of the organization of animal and human neural systems, from the systems level to the columnar level (<100 micron), with temporal resolution from seconds down to tens of milliseconds.

In more recent years, the integration of imaging modalities—multimodal imaging—has advanced neuroimaging further still. Used in combination, the individual strengths of different modalities can inform one another to yield new insights that expand the types of physiological information that can be gained through in vivo imaging, and thus also expand the impact of human health by enlarging the window of anatomical size, time scales, resolution, sensitivity, and specificity of detection. Engendered by the capabilities of multimodal imaging, and as clinicians and researchers increasing seek to understand the mechanisms of disease, multimodal functional imaging has grown at a particularly rapid rate in recent years, redefining the types of questions that can be asked in vivo, and permitting examination of physiological and pathological functions in living cells, tissues, and organs at their most basic level.

Biography:

Dr. Rosen is Professor of Radiology at Harvard Medical School and Professor of Health Sciences and Technology at the Harvard Medical School-Massachusetts Institute of Technology Division of Health Sciences and Technology. He is Director of the Athinoula A. Martinos Center for Biomedical Imaging at Massachusetts General Hospital, MIT, and the Harvard Medical School. He received his PhD in medical physics from MIT and his MD from the Hahnemann Medical College in Philadelphia, and is board certified in radiology.

Dr. Rosen’s research over the past thirty years has focused on the development and application of physiological and functional NMR techniques. His recent work has focused on the fusion of fMRI data with information from other modalities, including very high temporal resolution signals using magnetoencephalography (MEG) and non-invasive optical imaging. By using fMRI tools to evaluate the linkage between neuronal and physiological (metabolic and hemodynamic) events during periods of increased neuronal activity, his studies are allowing researchers to better interpret fMRI signal changes and develop new ways to probe brain function; for instance, through “event related” fMRI studies.

Dr. Rosen leads the activities of several large interdisciplinary and inter-institutional research and training programs that focus on the development of novel biomedical imaging technologies and their application to diverse programs of basic and clinical research. These programs include the NIH/NCRR Regional Resource Center, the Center for Functional Neuroimaging Technologies (CFNT), the Biomedical Informatics Research Network (BIRN), and others.

A Gold Medal winner and Fellow of the International Society of Magnetic Resonance in Medicine, Dr. Rosen is author or coauthor of more than 250 peer-reviewed articles, book chapters, and reviews. He has mentored dozens of graduate students and research fellows through the years.

Richard M. Leahy, Ph.D.

Professor, Signal and Image Processing Institute, Department of Electrical Engineering, University of Southern California

Talk Title: Electrophysiological Mapping of Function and Connectivity: Opportunities and Challenges

The fine temporal resolution of EEG and MEG provides an essential complement to functional MRI’s ability to map brain function with increasingly high spatial resolution but hemodynamically limited temporal resolution. This is particularly the case when mapping the large scale cortical interactions that are characterized by dynamic or transient oscillatory coupling. To detect these interactions and draw inferences about cortical networks, we need to be able to observe signals at the oscillatory frequencies at which this coupling occurs. EEG/MEG is currently our best non-invasive window on these processes. Unfortunately the limited spatial resolution implicit in the number of measured EEG/MEG channels and in the underlying physics of signal propagation confounds our ability not only to accurately localize neural activation, but also to reliably detect interactions between different cortical areas. In this talk I will discuss the current status of research into EEG/MEG source localization and interaction modeling. I will close with thoughts on problems that might be important in developing new ways of imaging brain networks and approaches that might be pursued to more reliably extract useful functional information from electrophysiological data.

Biography:

Dr. Richard Leahy is a Professor of Electrical Engineering, Biomedical Engineering, and Radiology at the University of Southern California and a former Director of the USC Signal and Image Processing Institute. Dr. Leahy is a Fellow of the Institute of Electrical and Electronic Engineers (IEEE) and the recipient of the 2010 Hoffman Medical Imaging Scientist Award from the IEEE Nuclear and Plasma Sciences Society. He was general chair of IEEE’s International Symposium on Biomedical Imaging (ISBI) in 2004 and Information Processing in Medical Imaging (IPMI) in 2001 and will be general chair of the Fully 3D Image Reconstruction meeting in Lake Tahoe in 2013. He is also an editor of Neuroimage. Dr. Leahy has published more than 200 papers in the field of biomedical signal and image processing. His research interests lie in the application of signal and image processing theory to biomedical imaging problems. His research involves the development of methods for anatomical and functional imaging with applications in neuroimaging and molecular imaging using PET, MRI and EEG/MEG.

Vince D. Calhoun, Ph.D.

Chief Technology Officer & Director, Image Analysis and MR Research, The Mind Research Network and Professor Electrical and Computer Engineering at University of New Mexico

Talk Title: Are we looking in the right haystack? The search for multimodal imaging biomarkers

The development of various neuroimaging techniques is rapidly improving the measurements of brain function/structure as well as their genetic underpinning. Though strong evidence exists for functional, structural and genetic abnormalities in multiple brain-based diseases, there is yet no replicable finding which has proven accurate enough for clinical decision making. Despite improvements in individual modalities, it is likely in part that the lack of consistent findings is because most models favor only one data type or do not combine data from different imaging modalities effectively, thus missing potentially important differences which are only partially detected by each modality. This is a complicated endeavor that must be approached carefully and efficient methods should be developed to draw generalized and valid conclusions from high dimensional data with a limited number of subjects. It is becoming increasingly clear that multi-modal fusion, a technique which takes advantage of the fact that each modality provides a limited view of the disease and may uncover hidden relationships, is an important tool for unraveling the mystery of complex illnesses such as schizophrenia. In this talk, we survey a number of multimodal fusion applications which enable us to study functional, structural and genetic aspects and may help us understand the impact of disease on these areas in a more comprehensive and integrated manner.

Biography:

Dr. Vince D. 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 PhD degree in electrical engineering from the University of Maryland Baltimore County, Baltimore, in 2002. He worked as a senior 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 200 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 among others. He is a reviewer for many journals and is on the editorial board of the Human Brain Mapping and Neuroimage journals.

Bin He, Ph.D

Distinguished McKnight University Professor of Neuro-Engineering at University of Minnesota

Talk Title: Electrophysiological Neuroimaging of Brain Activity

Brain activity is distributed over the three-dimensional volume and evolves in time. It is of importance to image dynamic brain activity with high resolution in space and time domains. We will discuss the merits and challenges of electrophysiological neuroimaging integrating EEG with MRI, and review our recent efforts in developing source mapping and imaging methods to localize the epileptogenic brain in patients with partial epilepsy. We will review our work to integrate EEG/MEG source imaging with effective connectivity mapping to localize primary epilepsy sources. We will present our development of an oscillatory source imaging methodology, which promises to noninvasively image oscillatory seizure sources and may have important applications to imaging other spontaneous brain activities. Our work suggests that the electrophysiological source imaging may have important clinical applications to aid pre-surgical planning in epilepsy patients. We will also review the merits and challenges of multi-modal functional neuroimaging, by integrating electrophysiological and hemodynamic measurements. Our recent work indicates that, the BOLD functional MRI and electrophysiological data can be integrated in a principled way, leading to substantially enhanced spatio-temporal resolution for functional imaging of dynamic brain activation.

Biography:

Dr. Bin He is a Distinguished McKnight University Professor of Biomedical Engineering at the University of Minnesota, where he also serves as Associate Director for Research of Institute for Engineering in Medicine, Director of Center for Neuroengineering, Director of NSF IGERT Training Program in Neuroengineering, and Director of NIH Training Program in Neuroimaging. Dr. He’s major research interests include functional biomedical imaging and neuroengineering. He has made significant original contributions to electrophysiological source imaging, multimodal functional neuroimaging, and brain-computer interface. Dr. He and his colleagues have pioneered the early development of anatomically constrained EEG source imaging and localization by means of the boundary element method, made significant contributions to novel methodologies of imaging oscillatory brain activity, and to the integrated EEG-fMRI neuroimaging methods. His lab has also made important contributions to noninvasive EEG based brain-computer interface. Dr. He has served on editorial boards of a number of international journals and edited several books. He is currently an Associate Editor of IEEE Transactions on Biomedical Engineering, IEEE Transactions on Neural Systems and Rehabilitation Engineering, Brain Topography, and an Editorial Board Member of NeuroImage, Journal of Neural Engineering and IEEE Spectrum. Dr. He is a Fellow of IEEE, American Institute of Medical and Biological Engineering, Institute of Physics, and International Society for Functional Source Imaging. He was the 2009-2010 President of IEEE Engineering in Medicine and Biology Society, and chaired the first IEEE EMBS Forum on Grand Challenges in Neuroengineering held in 2010.

James Duncan, Ph.D

Ebenezer K. Hunt Professor of Biomedical Engineering and Professor of Diagnostic Radiology and Electrical Engineering at Yale University

Talk Title: Model-based Strategies for Biomedical Image Analysis: A Platform for Information Integration

The development of methods to accurately and reproducibly recover useful quantitative information from biomedical images is often hampered by uncertainties in handling the data related to: image acquisition parameters, the variability of normal biological, anatomical and physiological structure and function, the presence of disease or other abnormal conditions, and a variety of other factors. This talk will review image analysis strategies that make use of models based on geometrical and physical/biomechanical information to help constrain the range of possible solutions in the presence of such uncertainty. The discussion will be focused by looking primarily at several problem areas in the realms of neuroanatomical structure analysis, cardiac function analysis, and work in cellular image analysis, with an emphasis on image segmentation and motion/deformation tracking. The presentation will include a description of the problem areas and visual examples of the image datasets being used, an overview of the mathematical techniques involved and a presentation of results obtained when analyzing actual patient image data using these methods. Emphasis will be placed on how image-derived information and appropriate modeling can be used together to address key challenges in the years ahead related to the development of integrated reasoning at and across imaging scales and imaging modalities.

Biography:

James S. Duncan is the Ebenezer K. Hunt Professor of Biomedical Engineering, as well as a Professor of Diagnostic Radiology and Electrical Engineering at Yale University, New Haven, CT, USA. He trained in Electrical Engineering, receiving the Ph.D. from the University of Southern California, Los Angeles, in 1982. His research is focused in the area of biomedical image analysis, including segmentation, non-rigid motion /deformation tracking and image-guided intervention/surgery. From 1973-1983, he worked for Hughes Aircraft Company, Electro- Optical and Data Systems Group, El Segundo, California, and joined the Yale faculty in 1983. Professor Duncan is a member of Eta Kappa Nu and Sigma Xi, is a Fellow of the IEEE, a Fellow of the American Institute for Medical and Biological Engineering (AIMBE) and a Fellow of The MICCAI Society. He was awarded the “MICCAI 2008 Significant Researcher Award,” given for his “pioneering research on Statistical and Deformable Model-Based Methods and their multi-organ-based applications.” He is on the editorial board of the Journal of Mathematical Imaging and Vision, is an Associate Editor for the IEEE Transactions on Medical Imaging and is one of the founding co-Editors-in-Chief of the journal Medical Image Analysis (Elsevier). He was a Fulbright Research Scholar at the Universities of Amsterdam and Utrecht in the Netherlands during part of the 1993-94 academic year. In 1997, he chaired the 15th international meeting on Information Processing in Medical Imaging and was the general chair for the 2005 meeting on Medical Image Computing and Computer-Assisted Intervention (MICCAI). From 1999 to 2003, Dr. Duncan was a charter member of the National Institutes of Health (NIH) Diagnostic Imaging Study Section, serving as its Chair from 2001-2003.

Daniel Rueckert, Ph.D

Professor of Visual Information Processing at Imperial College London

Talk Title: Learning and Discovery of Clinically Useful Information from Medical Images

Three-dimensional (3D) and four-dimensional (4D) imaging plays an increasingly important role in computer-assisted diagnosis, intervention and therapy. However, in many cases the interpretation of these images is heavily dependent on the subjective assessment of the imaging data by clinicians. Over the last decades medical image computing has transformed the clinical workflow in many areas of medical imaging. This talk will focus on the convergence of image acquisition, image analysis and machine learning techniques for the discovery and quantification of clinically useful information from medical images. To illustrate this we will show several examples such as the segmentation of neuro-anatomical structures, the discovery of biomarkers for neurodegenerative diseases such as Alzheimer’s and the combination of imaging and genetic data.

Biography

Daniel Rueckert joined the Department of Computing as a lecturer in 1999 and became senior lecturer in 2003. Since 2005 he is Professor of Visual Information Processing and heads the Biomedical Image Analysis group. He received a Diploma in Computer Science (equiv to M.Sc.) from the Technical University Berlin and a Ph.D. in Computer Science from Imperial College London. Before moving to Imperial College, he has worked as a post-doctoral research fellow in the Division of Radiological Sciences and Medical Engineering, King’s College London where he has worked on the development of non-rigid registration algorithms for the compensation of tissue motion and deformation. The developed registration techniques have been successfully used for the non-rigid registration of various anatomical structures, including in the breast, liver, heart and brain and are currently commercialized by IXICO, an Imperial College spin-out company. During his doctoral and post-doctoral research he has published more than 250 journal and conference articles. Professor Rueckert is an associate editor of IEEE Transactions on Medical Imaging, a member of the editorial board of Medical Image Analysis, Image & Vision Computing and a referee for a number of international medical imaging journals and conferences. He has served as a member of organising and programme committees at numerous conferences, e.g. he has been General Co-chair of MMBIA 2006 and Programme Co-Chair of MICCAI 2009, ISBI 2012 and WBIR 2012.

Dorin Comaniciu, Ph.D

Global Technology Head for Image Analytics and Informatics at Siemens Corporate Research

Talk Title: Shaping the Future through Innovations: Towards Personalized Medicine

The promise of personalized medicine is to do more in advance, promote early detection of the disease, more efficient workflows, and provide patient-specific therapies. This talk will analyze three emerging dimensions of imaging for personalized medicine: knowledge-based imaging, real-time, and in-silico modeling of the body function and disease. We will underline the role that semantic information plays in parsing the medical image data into hundreds of quantifiable components. We will showcase comprehensive cardiac models that include patient’s anatomy, dynamics, hemodynamics and biomechanics. By presenting example applications that make today a difference in hospitals we will extrapolate on the imaging technology potential and expectations for the near future, with a focus on accountable care.

Biography

Dr. Dorin Comaniciu is Global Technology Head for Image Analytics and Informatics at Siemens Corporate Research, Princeton, New Jersey. His scientific interests include medical imaging, cardiac modeling, whole body, image-guided surgery, and biomedical informatics. He is a Fellow of the IEEE and Top Innovator of Siemens AG. He holds 89 US patents and has co-authored more than 200 publications in the area of information processing, including best papers in CVPR and MICCAI. Dr. Comaniciu received the 2011 Thomas Alva Edison Award for a patent on heart modeling, the 2010 IEEE Longuet-Higgins Prize for ‘fundamental contributions to computer vision’, and served as the scientific director of Health-e-Child, a project granted the 2008 Europe’s Information Society Grand Prize. The aortic valve implantation technology his team contributed to Siemens received the 2010 Innovation Award of the European Association for Cardio-Thoracic Surgery. He served as an Associate Editor of IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Medical Imaging. He graduated from University of Pennsylvania – The Wharton School (AMP’11), Rutgers University (PhD’99), and the Polytechnic University of Bucharest (PhD’95).

Milan Sonka, Ph.D.

Professor and Chair, Dept. of Electrical & Computer Engineering and Professor of Radiation Oncology, and Ophthalmology & Visual Sciences at The University of Iowa

Talk Title: Medical image analysis for early detection and disease outcome prediction

Quantitative medical image analysis has proven invaluable for non-invasively reaching the correct diagnosis, deciding about therapy, or planning image-guided interventions. Fully utilizing the power of imaging and quantitative analysis for personalized earliest detection of diseases, predicting the course of disease, comparing multiple therapy options, and determining the best available approaches to treatment are needed to maximize the impact of imaging. The presentation will focus on building and combining large-scale population data from imaging and non-imaging sources, genetics, electronic patient records, lab samples, etc. for forward-looking analyses. The motivation examples will include translational research challenges from the areas of cardiovascular, pulmonary, ophthalmic, and orthopedic diseases.

Biography:

Milan Sonka received his Ph.D. degree in 1983 from the Czech Technical University in Prague, Czech Republic. He is Professor and Chair of the Department of Electrical & Computer Engineering, Professor of Ophthalmology & Visual Sciences, and Radiation Oncology at the University of Iowa, Director of the Iowa Institute for Biomedical Imaging, IEEE Fellow, and AIMBE Fellow. His research interests include medical imaging and knowledge-based image analysis with emphasis on cardiovascular, pulmonary, orthopedic, and ophthalmic image analysis. He is the first author of 3 editions of Image Processing, Analysis and Machine Vision book (1993, 1998, 2008) and co-authored or co-edited 18 books/proceedings. He has published more than 110 journal papers and over 340 other publications. He is Editor in Chief of the IEEE Transactions on Medical Imaging and member of the Editorial Board of the Medical Image Analysis journal. To bring results of his research work to clinical practice, he has co-founded two medical image analysis companies — Medical Imaging Applications LLC, and VIDA Diagnostics Inc.

Jennifer Lippincott-Schwartz, Ph.D

Eugene Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD

Talk Title: Navigating the cellular landscape with new optical probes, imaging strategies and technical

Emerging visualization technologies are playing an increasingly important role in the study of numerous aspects of cell biology, capturing processes at the level of whole organisms down to single molecules. Recent developments in probes, techniques, microscopes and quantification are dramatically expanding the areas of productive imaging. Photoactivatable fluorescent proteins (PA-FPs) have been particular fruitful in this regard. They become bright and visible upon being exposed to a pulse of UV light. This allows selected populations of proteins to be pulse-labeled and tracked over time. Used for in cellulo pulse chase experiments, the PA-FPs have helped clarify mechanisms for biogenesis, targeting, and maintenance of organelles as separate identities within cells. PA-FPs have further permitted the development of single molecule-based superresolution (SR) imaging, which dramatically improves the spatial resolution of light microscopy by over an order of magnitude (~10-20 nm resolution). Involving the controlled activation and sampling of sparse subsets of photoconvertible fluorescent molecules, single molecule SR imaging offers exciting possibilities for obtaining molecule scale information on biological events occurring at variable time scales. Here, I discuss the new fluorescent imaging techniques and the ways they are helping researchers navigate through the cell to unravel long-standing biological questions.

Biography:

Jennifer Lippincott-Schwartz obtained her Ph.D from Johns Hopkins University in Baltimore, MD, received post-doctoral training with Dr. Richard Klausner at the National Institute of Child Health and Human Development (NICHD), NIH, Bethesda, MD, and is currently Chief of the Section on Organelle Biology in the Cell Biology and Metabolism Branch of the NICHD at NIH. Lippincott-Schwartz’s research uses live cell imaging approaches to analyze the spatio-temporal behavior and dynamic interactions of molecules and organelles in cells. Her group has pioneered the use of green fluorescent protein (GFP) technology for quantitative analysis and modeling of intracellular protein traffic and organelle biogenesis in live cells and embryos, providing novel insights into cell compartmentalization, protein trafficking and organelle inheritance. Most recently, her research has focused on the development and use of photoactivatable fluorescent proteins, which ‘switch on’ in response to uv light. One application of these proteins she has put to use is photoactivated localization microscopy, (i.e., PALM), a superresolution imaging technique that enables visualization of molecule distributions at high density at the nano-scale. Dr. Lippincott-Schwartz was elected to the National Academy of Sciences in 2008 and the National Institute of Medicine in 2009.

Michael Unser, Ph.D

Professor and Director of EPFL’s Biomedical Imaging Group, Lausanne, Switzerland

Talk Title: Novel mathematical tools for improved 3-D reconstruction and biological image analysis

Biological imaging has recently entered its golden age, thanks to advances in fluorescent probe development and novel high-resolution microscopies [e.g., confocal, two-photon, stimulated emission depletion (STED), and localization microscopy (PALM and STORM)]. We shall argue that the capabilities of modern microscopes can be further enhanced with the help of sophisticated signal processing for denoising, three-dimensional (3-D) deconvolution, and/or tomographic reconstruction. We shall demonstrate that the use of wavelets and sparsity-promoting criteria can be very helpful for such tasks. The other important point is that biological structures are inherently 3-D, which calls for the development of adapted basis functions and specific feature detectors. We shall illustrate the concept with the design of steerable wavelets that can be optimized for the extraction of specific structures such as particles, sheets and filaments.

Biography:

Michael Unser is Professor and Director of EPFL’s Biomedical Imaging Group, Lausanne, Switzerland. His main research area is biomedical image processing. He has a strong interest in sampling theories, multiresolution algorithms, wavelets, and the use of splines for image processing. He has published about 200 journal papers on those topics, and is one of ISI’s Highly Cited authors in Engineering (http://isihighlycited.com).
From 1985 to 1997, he was with the Biomedical Engineering and Instrumentation Program, National Institutes of Health, Bethesda USA, conducting research on bioimaging and heading the Image Processing Group.

Dr. Unser is a fellow of the IEEE (1999), an EURASIP fellow (2009), and a member of the Swiss Academy of Engineering Sciences. He is the recipient of several international prizes including three IEEE-SPS Best Paper Awards and two Technical Achievement Awards from the IEEE (2008 SPS and EMBS 2010).

Scott Fraser, Ph.D

Anna L. Rosen Professor of Biology & Engineering and Applied Science and Director, Rosen Center for Biological Engineering at Beckman Institute

Talk Title: Imaging the cellular and molecular dynamics of embryonic development

Intravital imaging offers unprecedented opportunities for studying the cell lineages, cell interactions and intercellular signaling that guide embryonic development and function. These powerful techniques are challenged by major tradeoffs between spatial resolution, temporal resolution, and the limited photon budget.

We are attempting to advance this tradeoff by constructing faster and more efficient microscopes that maintain subcellular resolution. This combination of speed and resolution is required as intravital imaging can only generate accurate data on cell lineages and cell migration if it can re-acquire the three dimensional image of the entire specimen before any of the cells can move half of the distance separating them from their neighbors. Failing this, imaging tools can only give information on the averaged behaviors of cells (such as optical flow or PIV), which is often mistakenly taken as revealing cellular mechanism.
We have developed a new microscope, combining the deep penetration of two-photon microscopy and the speed of light sheet microscopy to generate images with more than ten-fold improved imaging speed and sensitivity. As with other light sheet technologies, dramatically faster acquisitions rates results from the collection of an entire 2-D optical section in parallel. This two-photon SPIM is far less subject to light scattering, permitting subcellular resolution to be maintained far better than possible with conventional light sheet microscopes.

In parallel to microscope development, we have been refining Second Harmonic Generation (SHG) nanoparticles as labeling reagents with greater photostability and brightness. These nanoparticles give sufficient signal for clear imaging down to the single molecule level, even in complex optical environments, and avoid the limitations of quantum dots (blinking and bleaching).

Combined, these improvements define a new compromise between spatial resolution, temporal resolution, and the limited photon budget: combining needed resolution, speed and sensitivity to follow complex cell/tissue events over the prolonged periods of embryogenesis. We are applying these tools to study zebrafish in which the FlipTrap vector has been used to create functional fusion proteins that are expressed at normal levels. These fusions permit cellular and molecular imaging of the key events in normally and conditionally mutated embryos, offering systems analyses of embryonic development.

Biography:

Professor Scott E. Fraser has a long-standing interest in the imaging and molecular analysis of intact biological systems, and has been active in developing new technologies for novel assays. He has been the Anna L. Rosen Professor of Biology and Director of the Biological Imaging Center at the Beckman Institute at the California Institute of Technology since 1991, the Founding Director of the Caltech Brain Imaging Center from 2002 to 2008, a founding member of the Kavli Institute of Nanoscience, and now serves as the Director of the Rosen Center for Biological Engineering. Before coming to Caltech, he served on the faculty and as the Chair of the Department of Physiology and Biophysics at the University of California, Irvine. Professor Fraser earned his B.S. with honors in Physics from Harvey Mudd College and his Ph.D. in Biophysics with Distinction from Johns Hopkins University. His current research centers on the high-content imaging of embryonic imaging in the zebrafish and the analysis of craniofacial development in avians and mice.

Jean-Christophe Olivo-Marin, Ph.D

Chair of Cell Biology and Infection Department and Director, Quantitative Image Analysis Unit, Institut Pasteur

Talk Title: The future of bioimaging: less photons, more numbers

Further improvements and breakthroughs in microscopy acquisition methods can be achieved by incorporating innovative signal/image processing ingredients directly into the acquisition and/or reconstruction protocols, and by developing the new paradigm of mathematical microscopy. We will present some recent developments of smart acquisition methods in biological imaging whereby it is possible with mathematical tools to recover a high quality image from very fewer samples than the full acquisition and to design smart dynamic imaging protocols. They are based on theoretical tools from Compressed Sensing (CS), which is a recent mathematical theory for sampling and reconstructing signals in an efficient manner. Indeed, the use of CS-based computational tools does provide a novel framework to enable faster frame rates, better preservation of biological samples and higher qualities of image reconstruction. We will discuss examples of how the use of these tools makes it possible the design of new imaging protocols, dedicated to specific biological paradigms and experimental conditions.

Biography:

J.-C. Olivo-Marin is the head of the Quantitative Image Analysis Unit and the Chair of the Cell Biology and Infection Department at the Institut Pasteur, Paris. He holds a Ph.D. in Optics and Signal Processing and the HDR from the Institut d’Optique Théorique et Appliquée, University of Paris-Orsay. He was a co-founder of the Institut Pasteur Korea, Seoul, where he held a joint appointment as Chief Technology Officer from 2004 to 2005. Previous to that, he was a staff scientist from 1990 to 1998 at the European Molecular Biology Laboratory, Heidelberg. He is a specialist of image analysis of multidimensional microscopy images, computer vision and motion analysis for cellular dynamics. He is IEEE Fellow, Past Chair of the Bio Imaging and Signal Processing Technical Committee (BISP-TC), and member of the Editorial Board of the journal Medical Image Analysis. He has organized several special sessions dedicated to biological imaging at international biomedical conferences (ELMI’02, ELSO’03, ISBI’04, ICASSP’06 & ’11, SPIE Wavelets’09 & ’11, EMBO’11) and was General Chair of the IEEE International Symposium on Biomedical Imaging held in Paris in 2008.

Misha Pavel, Ph.D.

Program Director, Small Health and Well-Being, Information and Intelligent Systems at National Science Foundation

Talk Title: Transforming Health Care: The Role of Technology and Biomedical Imaging

As healthcare is rapidly becoming one of the key national and global challenges, technology-based solutions are increasingly viewed as important components of a potential solution to these healthcare delivery problems. However, transforming healthcare to be evidence-based, patient-centered and proactive will require substantial fundamental and technical advances. Recognizing these challenges, NSF has developed a program in Smart Health and Wellbeing (SHB) that is focused on stimulating relevant research in key areas including computer science, engineering, and behavioral and social sciences, reflecting the multidisciplinary nature of problems. This presentation will describe the SHB program and several current applications of imaging as well as a number of issues related to the corresponding image analysis. In particular, recent advances in mobile technology, emergence of new sensing technologies and the progress in interconnection of electronic health records that include imaging data present new challenges to the image acquisition and interpretation. The presentation will include examples of specific challenges such as model-based detection of anomalies and information fusion.

Biography:

Misha Pavel is currently a Program Director at the National Science Foundation in charge of a program called Smart Health and Wellbeing. Concurrently, he has an appointment as a professor in the Department of Biomedical Engineering, with a joint appointment in the Department of Medical Informatics and Clinical Epidemiology, at Oregon Health and Science University. Previously, he was a chair of the Department of Biomedical Engineering and the Director of the Point of Care Laboratory, which focuses on unobtrusive monitoring, neurobehavioral assessment and computational modeling. His current research is focused on technology that would enable transformation of healthcare to be proactive, distributed and patient-centered. Prior to his academic career, he was a member of the technical staff at Bell Laboratories, where his research included network analysis and modeling. His current research is at the intersection of computational modeling of complex behaviors of biological systems, engineering, and cognitive science with a focus on information fusion, pattern recognition, augmented cognition, and the development of multimodal and perceptual human-computer interfaces. He developed a number of quantitative and computational models of perceptual and cognitive processes, eye movement control, and a theoretical framework for knowledge representation; the resulting models have been applied in a variety of areas, ranging from computer-assisted instruction systems, to enhanced vision systems for aviation, to augmented cognition systems. He has a Ph.D. in experimental psychology from New York University, an M.S. in electrical engineering from Stanford University, and a B.S. in electrical engineering from the Polytechnic Institute of Brooklyn.

Dimitris N. Metaxas, Ph.D

Distinguished Professor of Computer Science at Rutgers the State University of New Jersey

Talk Title: Progress and Challenges in Patient Specific Cardiac Wall and Blood Flow Modeling and Characterization from CT, MRI and US.

We outline our framework, methods and results for the patient specific 4D cardiac wall motion modeling and characterization and the respective blood flow analysis based on the use of sparsity, physics-based deformable models, and Navier Stokes equations. We will first present cardiac wall modeling and characterization results based on the use of CT, MRI and tMRI data, and novel methods for comparing cardiac wall motion analysis from US and tMRI data, respectively . We will then present novel MRI signal reconstruction methods based on dynamic group sparsity. We will conclude with future challenges and especially our focus on real time and clinically useful methods for signal reconstruction and modeling/classification, and the fusion of multiple modalities.

Biography:

Dr. Dimitris Metaxas is a Distinguished Professor in the Division of Computer and Information Sciences at Rutgers University. He also holds appointments in the BME dept and the Dept of Radiology at UMDNJ. He was a tenured faculty of Computer and Information Science, and Biomedical Engineering at the University of Pennsylvania from 1992 to 2002. Dr. Metaxas received his Diploma in EE from NTUA in Greece in 1996 with highest honors, his MSs in CS from the University of Maryland in College Park and his PhD in CS from the University of Toronto, Ontario Canada in 1992. His thesis “Physics-based Deformable Models for Vision and Graphics” was nominated for the ACM best thesis award. He is currently directing the Center for Computational Biomedicine, Imaging and Modeling (CBIM) at Rutgers University. Dr. Metaxas has been conducting research towards the development of formal methods upon which medical image analysis, computer vision and computer graphics can advance synergistically. He has pioneered several patient specific cardiac tissue modeling and blood flow modeling methods. Dr. Metaxas has published over 350 research articles in these areas and has graduated 32 PhD students. His research has been funded by NSF, NIH, ONR, AFOSR and the ARO. Dr Metaxas was recently awarded an NSF I/UCR Center on Dynamic Data Analytics whose goal is develop in conjunction with industry algorithms and methods that can deal with massive, dynamic and multidimensional data. Dr. Metaxas research has received several best paper awards from most major conferences (e.g., MICCAI, ISBI) and he has several patents. He was awarded a Fulbright Fellowship in 1986, is a recipient of an NSF Research Initiation and Career awards, an ONR YIP, is a Fellow of the American Institute of Medical and Biological Engineers, and a member of ACM and IEEE. He was also Program Chair of ICCV 2007, a General Chair of ICCV 2011, FIMH 20011, MICCAI 2008 and CVPR 2014 and the Senior Program Chair for SCA 2007.

Baba C Vemuri Ph.D.

Professor & Director Laboratory for Computer Vision, Department of CISE at the University of Florida

Talk Title: Diffusion MRI Processing: Where are we where do we go from here?

Diffusion MRI (dMRI) is a relatively nascent non-invasive imaging technique that allows the measurement of water molecular diffusion through tissue in vivo. The directional features of water diffusion allow one to infer the connectivity patterns prevalent in tissue and possibly track changes in this connectivity over time for various clinical applications. There are two fundamental quantities that one is normally interested in computing for analysis of dMRI data sets, they are: (i) water molecule displacement probability function and (ii) the diffusivity function. The former is needed in estimating the fiber orientations required in tractography and the latter is needed in computing clinically significant quantities such as mean diffusivity, generalized anisotropy etc. I will present a brief survey of the state-of-the-art indicating where the field is at and what the future challenges are. Time permitting, I will touch upon some key challenges in dMRI acquisition as well.

Biography:

Dr. Baba C. Vemuri received the PhD degree in electrical and computer engineering from the University of Texas at Austin in 1987. After his PhD, he joined the Department of Computer and Information Sciences at the University of Florida, Gainesville, and is currently a university research foundation professor of computer and information sciences and engineering. He was a coprogram chair of the 11th IEEE International Conference on Computer Vision (ICCV 2007). He has been an area chair and a program committee member of several IEEE conferences. He was an associate editor for several journals, including the IEEE Transactions on Pattern Analysis and Machine Intelligence (from 1992 to 1996) and the IEEE Transactions on Medical Imaging (from 1997 to 2003). He is currently an associate editor for the Journal of Medical Image Analysis. His research interests include medical image analysis, computational vision, modeling for vision and graphics, and applied mathematics. For the last several years, his research work has primarily focused on information geometric methods. Along this theme, he has been developing algorithms for the analysis of diffusion weighted MRI and diffusion tensor MRI, 3D image segmentation, unimodal and multimodal image (rigid+nonrigid) registration, nonrigid registration of 3D point sets, metric learning, and large margin classifiers. He has published more than 100 refereed journal articles and conference proceedings on medical image analysis, computer vision, graphics, and applied mathematics. He is a fellow of the IEEE and ACM. He received the US National Science Foundation Research Initiation Award (NSF RIA) in 1988 and the Whitaker Foundation Award in 1994. He was a recipient of the Best Peer Reviews at the Third European Conference on Computer Vision (ECCV 1994), the Best Poster Award at the 17th International Conference on Information Processing in Medical Imaging (IPMI 2001), as well as at IPMI 2005.

Andrew Laine, D.Sc

Percy K. and Vida L. W. Hudson Professor of Biomedical Engineering and Radiology at Columbia University

Talk Title: Smart health, cardiovascular and brain imaging

Andrew F. Laine received his D.Sc. degree from Washington University (St. Louis) School of Engineering and Applied Science in Computer Science, in 1989 and BS degree from Cornell University (Ithaca). He was first tenured as an Associate Professor in the Department of Computer and Information Sciences at the University of Florida (Gainesville), 1990-1997. For the last 14 years, he has been Director of the Heffner Biomedical Imaging Laboratory in the Department of Biomedical Engineering at Columbia University in New York City, as Professor of Biomedical Engineering and Radiology (Physics) and served as Vice Chair of the Department of Biomedical Engineering at Columbia, 1992-2011. Professor Laine has been very active in professional societies and has served as: Chair of Technical Committee (TC-BIIP) on Biomedical Imaging and Image Processing for the EMBS (2006-2009); and on the IEEE ISBI (International Symposium on Biomedical Imaging) steering committee (2006-09, 2009-12) and Program Chair for the IEEE EMBS annual conference in 2006 (New York City) and EMBC 2011 (Boston, MA), Program Co-Chair for IEEE ISBI in 2008 (Paris, France); Vice President of Publications for IEEE EMBS since 2008. His research interests include quantitative image analysis; cardiac functional imaging: ultrasound and MRI, retinal imaging, intravascular imaging and biosignal processing. He has graduated 23 doctoral students over the past 21 years and over has 150 peer reviewed manuscripts. He is a Fellow of AIMBE and IEEE.

Biography:

Dynamic cardiac metrics, including strains and displacements, can provide a quantitative approach to evaluate cardiac function. However, in current clinical diagnosis, strain measures in 2D are used despite the fact that cardiac motions are complex changes in 4D. Recent advances in 4D ultrasound enable the capability to capture such complex motion in real time. In our previous work, a 4D optical flow based motion tracking algorithm was developed to extract full 4D dynamic cardiac metrics from such 4D ultrasound data. In order to quantitatively evaluate this method, coronary artery occlusion experiments at various locations were performed on five canine hearts with 4D ultrasound and sonomicrometry data acquired during the occlusion. Optical flow displacement was then mapped onto a finite element field fitted model. Corresponding 4D ultrasound data from these experiments were then analyzed where estimated principal strains were directly compared to those recorded by sonomicrometry. The results of this study will used to focus on the problem of how to best present and make practical use of this type of real-time dynamic data to cardiologists and clinicians. The talk will also include consideration on other methods to quantify dynamic metrics over time such as imaging longitudinal studies of the brain and chronic vasculature disease.

Roger Y. Tsien, Ph.D.

Professor, Depts. of Pharmacology and of Chemistry & Biochemistry, University of California San Diego, 2008 Nobel Laureate

Talk Title: Building molecules to image disease pathways and guide therapy

For clinical applications, we need synthetic molecules with novel amplifying mechanisms for homing to diseased tissues. Activatable cell penetrating peptides (ACPPs) are polycationic cell penetrating peptides (CPPs) whose cellular uptake is minimized by a polyanionic inhibitory domain and then restored upon proteolysis of the peptide linker connecting the polyanionic and polycationic domains. Local activity of proteases able to cut the linker causes amplified retention in tissues and uptake into cells. ACPPs sensitive to matrix metalloproteinases-2 and -9 attached to dendrimers labeled with Cy5 and Gd-DOTA enable whole body magnetic resonance imaging (MRI) (Olson et al (2010) PNAS 107: 4311-4316) followed by fluorescence-guided surgery. Such fluorescence guidance illuminates tumor margins and improves tumor-free survival in two animal models (Nguyen et al (2010) PNAS 107: 4317-4322). Contrast for tumor over normal tissues is amplified and accelerated when the polyanionic domain includes an acceptor of fluorescence resonance energy transfer (FRET), because loss of FRET (monitored either by multispectral emission or donor excited-state lifetime) instantly signals proteolysis without waiting for uncleaved substrate to wash out of normal tissues. Thrombin-cleavable ACPPs accumulate in atherosclerotic plaques, and their labeling intensity seems to correlate with progression towards rupture. Separately, we have developed fluorescent peptides that light up peripheral nerves to show surgeons where not to cut (Whitney et al (2011) Nature Biotech. 29: 352-356). Thus chemical biology and multimodal imaging can improve early detection and accurate resection, which together offer relatively promising avenues to deliver complete cures at relatively low cost.

Biography:

Roger Y. Tsien received an A.B. in Chemistry and Physics from Harvard College in 1972, then received his Ph.D. in Physiology from the University of Cambridge in 1977, where he remained as a Research Fellow until 1981. He then became an Assistant, Associate, then full Professor in the Dept. of Physiology-Anatomy at the University of California, Berkeley. In 1989 he moved to the University of California, San Diego, where he is an Investigator of the Howard Hughes Medical Institute and Professor in the Depts. of Pharmacology and of Chemistry & Biochemistry. He is a member of the National Academy of Sciences and a foreign member of the Royal Society. Dr. Tsien’s research has been at the interfaces between organic chemistry, cell biology, and neurobiology. He is best known for designing and building molecules that either report or perturb signal transduction inside living cells. His work on fluorescent proteins was recognized by numerous honors culminating in a Nobel Prize in Chemistry in 2008. His current research is focused on dissecting neural circuits and synaptic plasticity, as well as developing new ways to target contrast agents and therapeutic agents to tumor cells based on their expression of extracellular proteases.

John Gore, Ph.D

Hertha Ramsey Cress University Professor of Radiology and Radiological Sciences, Biomedical Engineering, Physics and Astronomy, and Molecular Physiology and Biophysics at Vanderbilt University Institute of Imaging Science

Talk Title: Molecular Imaging Without Radiopharmaceuticals

A continuing challenge for biomedical imaging is the development of imaging agents or contrast materials that can be used to measure or map specific molecular and cellular processes. Most promising of these have been optical agents (which are limited by how deep they can be detected in tissues) and radiopharmaceuticals, which may be designed to reveal many fundamental aspects of tissue biology and metabolism with high sensitivity. Other modalities face significant challenges in terms of their relatively poor ability to detect small signal changes introduced by targeted media. The known physical limitations on the sensitivity for detecting small changes in MRI, CT, and ultrasound pulse-echo images can be used to estimate the practical requirements for molecular imaging and targeted contrast enhancement for these modalities. These types of imaging are highly unlikely to approach the sensitivity for detecting molecular processes of radionuclear methods, and the prospects for achieving sufficient concentrations of appropriate agents in vivo are poor for several types of applications such as small-molecule targeting of specific receptors. However, using relatively large carrier systems such as particles and liposomes, sufficient concentrations of paramagnetic agents may be delivered to achieve MR-signal changes adequate for detection. Theoretic considerations also predict that a similar approach, using rather large particles or carriers of materials with a high atomic number, might also be successful for CT, especially with additional developments such as the use of monochromatic x-rays. MRI probably offers the greatest variety of classes of agents that may be designed, including “smart” agents that change their behavior (and therefore affect signal) according to the local environment, thereby reducing the need for targeting and relying instead on sensing physico-chemical modulators of their effectiveness. High resolution MR spectroscopic imaging has long been the “truest” form of molecular imaging, and limitations on the ability to use compounds of interest containing e.g. carbon-13 or nitrogen-15 may be dramatically reduced using hyperpolarization techniques to increase sensitivity by several orders of magnitude.

Biography:

John C. Gore, Ph.D., holds the Hertha Ramsey Cress Chair in Medicine and is a University Professor of Radiology and Radiological Sciences, Biomedical Engineering, Physics and Astronomy, and Molecular Physiology and Biophysics, at Vanderbilt University. Dr. Gore obtained his Ph.D. in Physics at the University of London in the UK in 1976 and also holds a degree in Law. He is a member of the National Academy of Engineering and an elected fellow of the American Association for the Advancement of Science, the American Institute of Medical and Biological Engineering, the International Society for Magnetic Resonance in Medicine (ISMRM), and the Institute of Physics (UK). In 2004 Dr. Gore was awarded the Gold Medal of the ISMRM for his contributions to the field of magnetic resonance imaging. He is editor-in-chief of the journal Magnetic Resonance Imaging and a member of the National Advisory Council on Biomedical Imaging and Bioengineering for NIBIB. He founded the pioneering MRI research program at Hammersmith Hospital in the UK in the late 1970’s prior to establishing and directing the MRI research program at Yale University from 1982-2002. Since 1982 he has served as the founding director of the Vanderbilt University Institute of Imaging Science, a comprehensive, trans-institutional center that is engaged in multi-modal research for biomedical applications. His research interests include the development and application of imaging methods for understanding tissue physiology and structure, molecular imaging and functional brain imaging.

Lihong V. Wang, Ph.D.

Gene K. Beare Distinguished Professorship, Department of Biomedical Engineering, Washington University in St. Louis

Talk Title: Photoacoustic Tomography: Ultrasonically Breaking through the Optical Diffusion Limit

Photoacoustic tomography (PAT), combining optical and ultrasonic waves via the photoacoustic effect, provides in vivo multiscale non-ionizing functional and molecular imaging. Light offers rich tissue contrast but does not penetrate biological tissue in straight paths as x-rays do. Consequently, high-resolution pure optical imaging (e.g., confocal microscopy, two-photon microscopy, and optical coherence tomography) is limited to depths within the optical diffusion limit (~1 mm in the skin). Ultrasonic imaging, on the contrary, provides good image resolution but suffers from poor contrast in early-stage tumors as well as strong speckle artifacts. In PAT, pulsed laser light penetrates the tissue and generates a small but rapid temperature rise, which induces emission of ultrasonic waves due to thermoelastic expansion. The ultrasonic waves, ~1000 times less scattering than optical waves in tissue, are then detected to form high-resolution images at depths up to 7 cm, breaking through the optical diffusion limit. Further depths can be reached by using microwaves or RF waves as the excitation source. PAT, embodied in the forms of scanning photoacoustic microscopy or photoacoustic computed tomography, is the only modality capable of imaging across the length scales of organelles, cells, tissues, and organs with consistent contrast. Such a technology has the potential to enable multiscale systems biology and accelerate translation from microscopic laboratory discoveries to macroscopic clinical practice. PAT may also hold the key to the earliest detection of cancer by in vivo label-free quantification of hypermetabolism, the quintessential hallmark of cancer. The technology is commercialized by several companies.

Biography:

Lihong Wang holds the Gene K. Beare Distinguished Professorship of Biomedical Engineering at Washington University in St. Louis. His book entitled “Biomedical Optics: Principles and Imaging,” one of the first textbooks in the field, won the 2010 Joseph W. Goodman Book Writing Award. He also edited the first book on photoacoustic tomography. Professor Wang has published over 270 peer-reviewed journal articles with an h-index of 56 and delivered more than 300 keynote, plenary, or invited talks. He has received 31 research grants as the principal investigator with a cumulative budget of over $34M. He is the Editor-in-Chief of the Journal of Biomedical Optics. He chairs the annual conference on Photons plus Ultrasound, and chaired the 2010 Gordon Conference on Lasers in Medicine and Biology and the 2010 OSA Topical Meeting on Biomedical Optics. Wang serves as the founding chairs of the scientific advisory boards for two companies commercializing photoacoustic tomography. He received NIH’s FIRST and NSF’s CAREER awards. He was awarded OSA’s C.E.K. Mees Medal and IEEE’s Technical Achievement Award for “seminal contributions to photoacoustic tomography and Monte Carlo modeling of photon transport in biological tissues and for leadership in the international biophotonics community”.

Xiaochuan Pan, Ph.D.

Professor of Radiology at the University of Chicago

Talk Title:TBD

Biography

Xiaochuan Pan, Ph.D., is a Professor in the Department of Radiology, Department of Radiation and Cellular Oncology, the College, the Committee on Medical Physics, and the Comprehensive Cancer Center at The University of Chicago. His research interest centers on physics, algorithms, and applications of tomographic imaging. Awards received by Dr. Pan include IEEE NPSS Early Achievement Award and IEEE EMBS Technical Award for his contributions to medical imaging. He is a Fellow of AAPM, AIMBE, IEEE, OSA, and SPIE. Dr. Pan has served, and is serving, as the chair, a charter member, and/or a grant reviewer for funding agencies and foundations such as NIH, NSF, and NSFC, and is currently an associate editor, or an editorial board member, for a number of journals in the field, including IEEE Trans. Med. Imaging, IEEE Trans. Biomed Eng., and Phys. Biol. Med. He has served, and is serving, as a chair or member of numerous technical committees of professional organizations such as IEEE and RSNA, and as a chair of programs, themes, and sessions, or as a technical or a scientific committee chair or member, for conferences such as IEEE EMBC, IEEE MIC, RSNA, AAPM, and MICCIA.

Eliot Siegel, Ph.D.

Professor and Vice Chairman of the University of Maryland School of Medicine, Chief of Radiology and Nuclear Medicine for the Veterans Affairs Maryland Healthcare System

Talk Title: Bringing Imaging into the Era of Personalized Medicine

There has been a disconnect between the perceived high value of medical imaging in clinical care in oncology and the incorporation of medical imaging data in research. This has been due to the lack of a highly structured standard for image annotation and mark-up for human and machine interpretation of diagnostic images.

This challenge and others have been addressed by the National Cancer Institute’s Cancer Biomedical Informatics Grid Imaging workspace with projects that include:

1. eXtensible Imaging Platform which provides a suite of tools that utilize the DICOM working group 23 standard to allow a host program to run standard algorithms written to run across different proprietary platforms
2. Middleware including computer aided diagnosis over the grid and “virtual PACS”
3. The Annotation and Imaging Markup model and standard
4. The algorithm validation toolkit

The software and standards have been combined to perform in silico mining as a demonstration of the power of medical images to improve the practice of personalized medicine.

In order to make personalized medicine a reality, it will be critical to create a standard process whereby databases including those that contain images can be easily made available for research and clinical decision support.

Biography:

Dr. Eliot Siegel is Professor and Vice Chair at the University of Maryland School of Medicine, Department of Diagnostic Radiology, as well as Chief of Radiology and Nuclear Medicine for the Veterans Affairs Maryland Healthcare System. He is the director of the Maryland Imaging Research Technologies Laboratory and has adjunct appointments as Professor of Bioengineering at the University of Maryland College Park and as Professor of Computer Science at the University of Maryland Baltimore County campus. Dr. Siegel is also responsible for the NCI’s National Cancer Image Archive and is Workspace Lead of the National Cancer Institute’s caBIG In Vivo Imaging Workspace. He has been named as overall Radiology Researcher of the Year by his peers and separately as Educator of the year in Radiology. Dr. Siegel has also been selected by the editorial board of Medical Imaging as one of the top radiologists in the US on multiple occasions.

Dr. Siegel has a grant from the IBM “Jeopardy” team to help “educate” the “Dr. Watson” software in the field of medicine. His areas of include digital imaging and PACS, telemedicine, the electronic medical record, and informatics and artificial intelligence in medicine.

Dr. Siegel has won numerous teaching awards at the University of Maryland including medical school mentor of the year. He has been named as overall Radiology Researcher of the Year by his peers and separately as Educator of the year in Radiology. Dr. Siegel has also been selected by the editorial board of Medical Imaging as one of the top radiologists in the US on multiple occasions.

William W. Stead, M.D.

Associate Vice Chancellor for Health Affairs and Chief Strategy & Information Officer at Vanderbilt University Medical Center

Talk Title: A Grand Challenge in Image Assembly & Analysis

Biomedical science holds the promise of personalized medicine, such as selecting a medicine perfectly matched to a person’s biology so that they get the desired benefit without risk of side effect. To deliver on this promise, we need to identify subpopulations that react exactly the same way. Dr. Stead will contrast today’s approach to patient examination and diagnosis, which start with patterns humans have recognized over the years, with the computer-assisted granular classifications we need for personalized medicine. He will posit that granular patient classification calls for approaching the EHR as a grand challenge in image assembly and analysis.

Biography:

Dr. Stead is McKesson Foundation Professor of Biomedical Informatics and Professor of Medicine at Vanderbilt University. He received his B.A. and M.D. from Duke University where he also completed specialty and subspecialty training Internal Medicine and Nephrology. He has worked at the intersection of informatics and clinical practice for 40 years. He established the Department of Biomedical Informatics and led the development of information management infrastructure at Vanderbilt over the past 20 years. His current focus is on system-supported, evidence-based practice and research leading toward personalized medicine. He chaired the NRC committee to Engage the Computer Science Research Community in Health Care Informatics and co-edited its report calling for more emphasis on cognitive support. He is a member of the Council of the Institute of Medicine.

George Hripcsak, MD, MS

Vivian Beaumont Allen Professor and Chair of Columbia University’s Department of Biomedical Informatics and Director of Medical Informatics Services for NewYork-Presbyterian Hospital

Talk Title: Secondary Use of Electronic Health Record Data

The national adoption of electronic health records (EHRs) promises to make an unprecedented amount of data available for clinical research, but the data are complex, inaccurate, and frequently missing, and the record reflects complex processes beyond the patient’s biology. Nevertheless, clinicians use the EHR effectively to manage patient care, so valuable information is in fact present. By better understanding the EHR and by developing methods to correct for biases, it should be possible to overcome the challenges and to study disease over diverse populations, over long time scales, and with large sample sizes.

Biography:

George Hripcsak, MD, MS, is Vivian Beaumont Allen Professor and Chair of Columbia University’s Department of Biomedical Informatics and Director of Medical Informatics Services for NewYork-Presbyterian Hospital. Dr. Hripcsak is a board-certified internist with degrees in chemistry, medicine, and biostatistics. He led the effort to create the Arden Syntax, a language for representing health knowledge that has become a national standard. Dr. Hripcsak’s current research focus is on the clinical information stored in electronic health records. Using data mining techniques such as machine learning and natural language processing, he is developing the methods necessary to support clinical research and patient safety initiatives. He is currently co-chair of the Meaningful Use Workgroup of HHS’s Office of the National Coordinator of Health Information Technology; it defines the criteria by which health care providers collect incentives for using electronic health records. Dr. Hripcsak chaired the National Library of Medicine’s Biomedical Library and Informatics Review Committee, and he is a fellow of the American College of Medical Informatics and the New York Academy of Medicine. He has published over 200 papers.

Walter “Buzz” Stewart, PhD, MPH

Associate Chief Research Officer for the Geisinger Health System and Director of the Geisinger Center for Health Research

Talk Title: Longitudional ERH Data, Predictive Modeling and Implications for Clinical Care

The rapid growth in adoption of EHRs affords a unique opportunity to develop novel and cost-effective strategies to both create value and improve the delivery of health care through the application of text analytics, machine learning, and other data mining methods applied to longitudinal patient data. Real time access to imaging data in combination with fixed field clinical, lab, order, diagnostic, text, and other (e.g., EKG) data offer unprecedented opportunity for predictive modeling. When applied to longitudinal patient data, these models will offer the means to provide highly tailored guidance to patients and providers that is relevant to: early disease detection, guided therapy recommendations, shared decision-making, and prevention of hospitalization, never events, and readmissions. This presentation will describe scenarios for the application of these models for different time scales (e.g., early detection of heart failure versus prevention of inpatient DVTs), the challenges to combining different forms of data, and what will be required to effectively communicate with patients and providers.

Biography:

Walter “Buzz” Stewart, PhD, MPH, Geisinger Center for Health Research, is the Associate Chief Research Officer for the Geisinger Health System and Director of the Geisinger Center for Health Research. He started the Center in 2003, with a mission to serve as the Research & Development (R & D) division at Geisinger, focused on developing, testing, and evaluating novel approaches to delivering health care and on the science of translating methods of care with proven value to sustainable solutions. As Associate Chief Research Officer, he is directly involved in building R & D capabilities with the Clinical Enterprise and the Geisinger Health Plan. These efforts have lead to sustainable approaches to routine integration of patient data capture with ambulatory care, shared decision-making, point of decision expert guidance, and use of predictive models in ambulatory care. Prior to joining Geisinger, Dr. Stewart was previously: a full-time faculty member of the Johns Hopkins Bloomberg School of Public Health, Department of Epidemiology (1983-1995) and later Vice President of Research and Development (1998-2002) at AdvancePCS (2000-2002). Since 1992, Dr. Stewart has founded and managed several successful companies. He received his PhD in epidemiology from Johns Hopkins University.

Shahram Ebadollahi, Ph.D

Manager, Healthcare Analytics Research at IBM T.J. Watson Research Center

Biography:

Dr. Shahram Ebadollahi is the Senior Manager of Healthcare Systems and Analytics Research department at IBM T.J. Watson Research Center in New York. He and the team of scientists working with him conduct research in the area of healthcare informatics. Dr. Ebadollahi is especially interested in the applications of data mining, machine learning, advanced visualization and visual analytics to large patient population data for deriving insights and evidence for decision support in healthcare. He also has conducted research and published in the domains of multimedia content analysis and retrieval, event recognition in multimedia content, and medical imaging. Dr. Ebadollahi received his PhD and MS degrees in Electrical Engineering from Columbia University before joining IBM Research. He is also an adjunct faculty with the department of Electrical Engineering at Columbia University in New York.

Thomas F. Budinger, Ph.D

Professor of the Graduate School at University of California, Berkeley

Talk Title: Education, Ethics, and Exploring the Future

Thirty-eight years ago the only known higher education courses in tomography outside possibly medical schools were in a few schools where a professor had a keen interest and aptitude in electron microscopy, nuclear medicine, or optical imaging along with some mathematical skills that allowed some form of inverse problem solutions. The common educational basics were the tools of frequency analysis and linear algebra. Though geometric optics courses were taught throughout the world, physical optics was a course in physics departments and not found in life sciences, and to a limited degree in electrical engineering. Medical tomography in the early 1970s stimulated the field of medical imaging, and clever manipulations of electron micrographs (e.g. DeRosier and Klug) stimulated graduate courses in image data analysis and opened the door to new horizons for both electron microscopy and optical image separation (e.g. confocal microscopy).

Also, thirty-eight years ago the introduction of magnetic resonance imaging was not met with an educational fervor as the educators that could make an impact were limited to those with skills in physical chemistry or physical optics and by and large undergraduate students were not prepared.

Biography:

Thomas Budinger received the B.S. in chemistry (magna cum laude, Regis College, Denver, 1954); the M.S. degree in physical oceanography (University of Washington, Seattle, 1957); the M.D. degree (gold-headed cane award, Univ. of Colo. 1964); and the PhD in physical optics of electron microscopy (Univ. of Calif., Berkeley, 1971). Military service was as the International Ice patrol science officer of the U.S. Coast Guard (1957-1960). Thomas Budinger holds concurrent positions at the University of California, Berkeley (UCB) and the Lawrence Berkeley National Laboratory (LBNL). At UCB, he has held the Henry Miller Research Medicine Chair (1974 –2008) and he has been professor of bioinstrumentation, electrical engineering, and computer sciences since 1976. In 2004 he completed a six-year appointment as founding chair of the department of bioengineering at Berkeley. He is also Professor Emeritus at the University of California Medical Center where he served as director of the Magnetic Resonance Science Center (1993-97). At the Lawrence Berkeley national Laboratory, he has been Medical Research Division Director (1986–1992), Head, Center for Functional Imaging (1992-2007), and Faculty Senior Staff Scientist (1986-present). He is a member of the Institute of Medicine and the National Academy of Engineering where he is the Home Secretary.

At both Berkeley and UCSF, he has been active in undergraduate and graduate teaching and mentoring for which he received The Berkeley Citation. For imaging research he received the NIH Merit Award for Alzheimer’s Research; Distinguished Scientist Silver Medal Award from the International Society for Magnetic Resonance in Medicine; Georg Charles de Hevesy Nuclear Pioneer Award and Paul C. Aebersold Basic Science Award from the Society of Nuclear Medicine; the Ernst Jung Preis fur Medizin, Jung-Stiftung fur Wissenschaft und Forschung, Germany and the Gold Medal from the Roentgen Ray Society. Research papers are mainly on imaging technologies and applications to cardiovascular disease and mental disorders. In 2006 he authored a teaching text with his spouse on Ethics of Emerging Technologies: Scientific Facts and Moral Challenges.

Richard A. Baird, Ph.D

Director, Division of Interdisciplinary Training at the National Institute of Biomedical Imaging and Bioengineering (NIBIB), National Institutes of Health (NIH)

Talk Title: Research Training in Biomedical Imaging: Where Are We and Where Should We Be Going?

The primary challenge in preparing the next generation of biomedical imaging researchers is that this field includes research in many disparate areas, including the development of new imaging and contrast agents; the identification of new imaging biomarkers; new imaging paradigms for the detection, diagnosis, and treatment of disease; and hardware and software advances in imaging acquisition, post-processing, and analysis. This means that biomedical imaging requires the training of individual researchers from many disciplines, including biology, chemistry, computer science, engineering, mathematics, and physics, and the broad-based training of multidisciplinary and interdisciplinary research teams. This broad-based training needs to be undertaken as early as possible, preferably during the undergraduate and graduate years, and coordinated across multiple academic departments. To maximize the clinical application of imaging technologies, we also need to expose engineers and physical scientists to the clinical environment and needs, train more clinician-scientists in imaging usage and methodology, and encourage training and research partnerships between the academic and industry sectors. In my presentation, I will examine these training challenges and briefly review the NIH and NIBIB training programs that are trying to meet them.

Biography:

Dr. Richard Baird is currently the Director of the Division of Interdisciplinary Training at the National Institute of Biomedical Imaging and Bioengineering (NIBIB). He obtained the B.S. in Electrical Engineering (1975) from MIT and the Ph.D. in Electrical Engineering and Computer Sciences (1981) from the University of California, Berkeley. After a postdoctoral fellowship at the University of Chicago from 1981 to 1984, he became a research scientist at the Neurological Sciences Institute and the Department of Physiology and Pharmacology at Oregon Health Sciences University in Portland, Oregon. In 1998, Dr. Baird became the founding Head of the Simons Center for the Biology of Hearing and Deafness at the Central Institute for the Deaf (CID), Olin Professor in the Department of Speech and Hearing, Department of Otolaryngology, and Department of Anatomy and Neurobiology at Washington University in St. Louis, Missouri. He also founded and directed the Inner Ear Consortium, a multi-institutional group encouraging collaboration among inner ear researchers and supporting NIH-funded core facilities in confocal and multi-photon imaging, electron microscopy, molecular biology, and electronic services. In 2002, Dr. Baird became Director of Research of the Siebens Hearing Research Center, coordinating both basic and applied research programs in hearing and hearing loss. His own research interests include the use of electrophysiological, immunocytochemical, and optical imaging methods to study mechanotransduction, injury-induced synaptic remodeling, and the development, repair, and regeneration of sensory hair cells in the vertebrate inner ear.

Dr. Baird joined the NIBIB in 2005, where he coordinates its inter-agency training partnerships and conference, education, research training, and career development programs. In this capacity, he partnered with HHMI to develop the HHMI-NIBIB Interfaces Interdisciplinary training initiative and with NSF to develop the Bioengineering and Bioinformatics Summer Institutes (BBSI) program. During this period, he also initiated new NIBIB programs in undergraduate diversity and team-based design, doubled the size of NIBIB’s institutional training portfolio, launched NIBIB’s transitional career development program, and revamped NIBIB’s residency research education program. Dr. Baird has been a member of several NIH Blueprint for Neuroscience working groups, where he helped develop the Enhancing Neuroscience Diversity Through Undergraduate Research Education Experiences (ENDURE) program and training programs in neuro-imaging and computational neuroscience. He has also worked extensively with the NIH Roadmap (Common Fund), where he helped develop many interdisciplinary training programs as well as the NIH Director’s Early Independence Award program. For the past two years, Dr. Baird has also co-chaired the NIH Training Advisory Committee (TAC) and NIH-TAC Workforce (NTW) Committee, analyzing the relationship between training outcomes, biomedical workforce needs, and NIH research and training support policy.

Semahat Demir, Ph.D

Program Director, Biomedical Engineering at NSF

Talk Title: Training Future Interdisciplinary Biomedical Engineers

Dr. Demir will present an overview of National Science Foundation (NSF) and a summary of different NSF training funding opportunities. She will present recent studies and recommendations for the future of interdisciplinary biomedical engineering research and education.

Biography:

Dr. Semahat Demir has 22 years experience in academic research, 10 years experience in teaching in academia, 2 years experience in medical industry and 7.5 years experience in research funding administration and science/public diplomacy in the US federal government. Currently, Dr. Semahat Demir is the Program Director for Biomedical Engineering at National Science Foundation (NSF). She has developed and lead 6 new programs and participated in 13 other NSF and interagency funding programs. At NSF, she received two awards: Program Officer Excellence Award and Director’s Award for Collaborative Integration. Before joining NSF, Dr. Demir has held the positions of professor of Biomedical Engineering at the Joint Biomedical Engineering Program of University of Memphis and University of Tennessee, Expert Scientist and Consultant (for the Bioinformatics) for The Scientific and Technical Research Council of Turkey, Technical Manager and Medical Laser Engineer for Messerschmidt Bolkow Blohm and Rodenstock in Turkey, and Research and Development Engineer in the X-Ray Division of the Medical Engineering Center of Siemens Company in Erlangen, Germany.

Dr. Demir’s academic research expertise is computational modeling of bioelectricity in cardiac cells and bursting neurons. She has developed simulation-based teaching and learning resources including the interactive cell modeling resource, iCell. She supervised, trained and mentored 42 undergraduate students, graduate students and postdocs in research. She was a visiting professor at Istanbul Technical University, Bogazici University (former Robert College), Isik University and Yeditepe University in Turkey. Currently, she is an advisor to the Chair of Board Trustees and to President of Istanbul Kultur University. She is also a member of Board Trustees Atilim University, Ankara, Turkey.

Dr. Demir, an inspirational and sought-after speaker, gave 395 (295 invited) presentations, keynotes, plenaries, seminars and workshops in presentations, talks, seminars and workshops in USA, Canada, Mexico, Argentina, China, Japan, Hong Kong, Vietnam, Australia, New Zealand, Sweden, Germany, Austria, France, UK, Uruguay, Greece, and Turkey. She has 130 publications (including 7 refereed book chapters). There are 175 editorials and articles written about Dr. Demir and her work and 17 TV programs hosted her.

Semahat Demir received her BS degree in electronics engineering from Istanbul Technical University, MS degree in biomedical engineering from Bosphorous University, and second MS degree, and PhD degree in electrical and computer engineering from Rice University and postdoctoral training at Biomedical Engineering Department, Johns Hopkins University. Dr. Demir has held leadership roles at IEEE EMBS, BMES, ASEE BED, and SWE. She served on the governing boards of 6 technical organizations including IEEE EMB AdCom, ASEE Bioengineering Division and SWE. She is an AIMBE fellow and an US Embassy Science Fellow selected by the State Department. She has contributed to the US State Department’s science diplomacy and public diplomacy work in Turkey.

Srini Tridandapani, PhD, MD

Faculty, Department of Radiology and Imaging Sciences, Emory University and Adjunct Professor, Electrical & Computer Engineering, Georgia Institute of Technology

Talk Title: Grand Challenges in Integrating Education in Medicine and Engineering

As the intersection space between medicine and engineering evolves and enlarges, there are many challenges that can best be met by individuals cross-trained in engineering and medicine. An exciting opportunity exists to bring together trainees in the two fields to work in an integrated fashion and expand the reach of medical imaging. Just as engineers must better understand the clinical application areas where their imaging tools will be employed, so too must physicians understand the emerging technologies and tools that will impact their practice. Building synergies at the intersection must be approached at multiple levels including enhancing both curricula from the basic undergraduate to the advanced post-doctoral levels, hands-on joint projects, and building and nurturing conference and publication venues that appeal to both groups of professionals. I will present specific examples where cross-training between engineers and physicians is possible. I will also examine some barriers that we must overcome to develop the types of training programs most effective in educating the next generation of biomedical engineers and imaging scientists to meet the grand challenges before us.

Biography:

Dr. Srini Tridandapani received his B.E degree from Anna University, Madras, India and his M.S.E.E. and Ph.D. degrees from the University of Washington, Seattle, all in Electrical Engineering. After post-doctoral training in Computer Science at University of California, Davis, he was an Assistant Professor of Electrical and Computer Engineering at Iowa State University, Ames. Not satisfied with his engineering training, he then took the bold plunge into medical school and received his M.D. degree from the University of Michigan, Ann Arbor, MI followed by residency training in Radiology also at Michigan. He then obtained clinical fellowships in Cardiothoracic Imaging and Abdominal Imaging at Emory University. A board-certified radiologist, he is currently a faculty member in the Department of Radiology and Imaging Sciences at Emory University and an Adjunct Professor in the School of Electrical and Computer Engineering at Georgia Institute of Technology. Dr. Tridandapani has received multiple awards in radiology including the RSNA Resident Research Award, the ARRS Residents in Radiology Executive Council Award, the Elio-Bracco/ARRS Scholars Award, the Radiology Research Alliance New Investigator Award, and the Melvin M. Figley Fellowship in Radiology Journalism from the ARRS. Dr. Tridandapani’s current research involves the development of novel gating strategies for optimizing cardiac computed tomography and innovative tools to increase patient safety in medical imaging. His clinical interests include thoracic and abdominal imaging and advanced image-guided procedures.