Symposium on AI for Biomedical Imaging Across Scales

Organizers





Speakers and Session Chairs

Anne Le Grand

Anne Le Grand is Vice President of IBM Watson Health and General Manager of Imaging, Oncology, Genomics, and Life Science at IBM. Dr Le Grand has more than 25 years experience dedicated to the global healthcare technology industries. She has extensive experience running large global healthcare technology businesses, a strong customer focus, deep market insights and unrelenting focus on continuous improvement. She is passionate about building diverse and talented teams, future leaders with an outstanding reputation for securing team loyalty. Dr Le Grand has an exclusive background in health-tech – imaging, informatics, diagnostics, professional services. Prior to joinin IBM, she held senior executive roles with Philips Healthtech, GE Healthcare, Eastman Kodak Health Group, 3M Medical Imaging.



Jeffrey Welser

Dr. Jeffrey Welser is a Vice President in IBM Research, directing Labs based in Almaden,California, as well asAustralia, China and Japan. He is also the VP of Exploratory Science research and university partnerships globally, including the MIT-IBM Watson Lab. He oversees exploratory and applied research to advancedata technology and analytics for Cloud and AI systems and software, with a strong focuson advanced computing technologies for AI, neuromorphic devices and quantum computing. After joining IBM Research in 1995, Dr. Welser worked on a broad range of technologies, including novel silicon devices, high-performance CMOS and SOI device design, and next generation system components. He has ledteams in both development and research,as well as running industrial, academic and government consortiums, including the SRCNanoelectronics Research Initiative. Dr. Welser received his Ph.D. in Electrical Engineering from Stanford University. He holds 21 US Patents and has published over 75 technical papers and presentations. He is a member of the IBM Academy of Technology, an IEEE Fellow, a member of the American Physical Society, Chairman of the Bay Area Science and Innovation Consortium. He serves on several university and industry technical boards, and has participated in numerousFederal agency, National Academies and Congressional panels on advanced semiconductor and computing technology.



Simone Bianco

Simone Bianco is research staff member in the department of Industrial and Applied Genomics at the IBM Almaden Research Center, where he leads the Cellular Engineering lab. He got his BS and MS in Physics at the University of Pisa, Italy, and his PhD in Physics from the University of North Texas. His main research interests are in in theoretical evolutionary biology, especially the evolution of RNA viruses, and cellular engineering. Prior to joining IBM, Dr Bianco worked at the UCSF Department of Bioengineering and Therapeutic Science and at the UCSF Department of Microbiology and Immunology. At UCSF he contributed to several scientific developments in computational genomics and theoretical biology. Before his time at UCSF, Dr Bianco worked at the College of William and Mary, where he modeled the spread of multistrain diseases with interacting strains, focusing on dengue fever. Dr Bianco is IBM PI and site director of the Center for Cellular Construction, an NSF Science and Technology Center in partnership with UC San Francisco, UC Berkeley, Stanford University, SF State University and the SF Exploratorium. The center aims at transforming cell biology into an engineering discipline. He is a TED speaker with over 1M views, leader of one of 2018 IBM's 5-in-5, the 5 projects which will change the world in the next 5 years according to IBM, and a honorary visiting lecturer for the Society for Industrial and Applied Mathematics, for his standing in the field of dynamical systems and his commitment to education.



Wallace Marshall

Wallace Marshall is Professor of Biochemistry and Biophysics at the University of California San Francisco. He received his bachelor’s degrees in Electrical Engineering and Biochemistry from the State University of New York at Stony Brook, and his Ph.D. in Biochemistry from UC San Francisco, where he studied organization of chromosomes within the nucleus with John Sedat. He then moved to Yale University for postdoctoral studies with Joel Rosenbaum, where he became interested in questions of organelle size control and cell organization, using cilia, flagella, and centrioles as model systems. In 2003, he joined the faculty at UCSF where he continues to study questions of cellular organization in a variety of model organisms using an integrated combination of live-cell microscopy, image analysis, and computational modeling. He was co-director of the Physiology summer course at the Marine Biological Laboratory in Woods Hole, Massachusetts from 2013-2018, as well as the organizer of an NSF funded program to promote the development of quantitative cell biology through a series of workshops and hackathons. He is currently Director of the Center for Cellular Construction, an NSF funded Science and Technology Center devoted to engineering cellular structure, and Director of the Integrative Program in Complex Biological Systems at UCSF.



Zev Gartner

Dr. Gartner is working to understand the principles governing the self-organization of human tissues, with the goal of engineering tissues for regenerative medicine and stabilizing tissues for cancer prevention. Dr. Gartner completed his undergraduate studies in Chemistry at UC Berkeley where he worked as a Beckman Fellow with Dr. Yeon-Kyun Shin. He received a PhD in Chemical Biology as a National Science Foundation Graduate Research Fellow with David Liu at Harvard University, and completed training as Jane Coffin Childs Postdoctoral Fellow with Carolyn Bertozzi at UC Berkeley. He is currently a Professor in the Department of Pharmaceutical Chemistry at the University of California, San Francisco and co-director of the NSF Center for Cellular Construction. His work has been honored with the NIH New Innovator Award and the DOD Era of Hope Scholars award. He was selected among the Popular Science “Brilliant 10” in 2015 and as a Chan/Zuckerberg Biohub investigator in 2017.



Scott Fraser

Professor Scott E. Fraser has a long-standing commitment to quantitative biology, applying the tools of chemistry, engineering, and physics to problems in biology and medicine. His personal research centers on imaging and molecular analyses of intact biological systems, with an emphasis on early development, organogenesis, and medical diagnostics. After training in physics (BS, Harvey Mudd College, 1976) and biophysics (PhD, Johns Hopkins University, 1979), he joined the faculty at UC Irvine, and rose through the ranks to become Chair of the Department of Physiology and Biophysics. In 1990 he moved to Caltech to serve as the Anna L. Rosen Professor of Biology, and the Director of the Biological Imaging Center. He is deeply committed to interdisciplinary training and translational research, having helped found the Caltech Brain Imaging Center and the Kavli Institute of Nanoscience, as well as serving as the Director of the Rosen Center for Biological Engineering. In Fall 2012, he moved to USC to take a Provost Professorship in the Dornsife College of Letters Arts and Sciences, the Children’s Hospital Los Angeles, Keck School of Medicine and the Viterbi School of Engineering. He remains active in interdisciplinary research and serves as the Director of Science Initiatives for the USC campuses.



Michael Angelo

Dr Angelo’s academic background spans across the fields of physics, biochemistry, electrical engineering, and medicine. The Angelo lab uses custom built high dimensional imaging technologies and computational approaches to understand the interplay between single cell phenotype and tissue histology in health and disease. They employ a method known as Multiplexed Ion Beam Imaging (MIBI) that uses secondary ion mass spectrometry to image antibodies tagged with isotopically pure elemental metal reporters. MIBI is capable of analyzing up to 100 targets simultaneously over a five-log dynamic range. Thus, MIBI enables highly multiplexed and sensitive immunohistochemistical analysis of complex tissues. The Angelo Lab applies MIBI to questions in the fields of cancer biology, infectious diseases, immune tolerance, allergy, and the maternal-fetal interface in addition to technology and methods development.



Sandy Napel

Dr. Napel's primary interests are in developing diagnostic and therapy-planning applications and strategies for the acquisition and visualization of multi-dimensional medical imaging data. Examples are: creation of three-dimensional images of blood vessels using CT, visualization of complex flow within blood vessels using MR, computer-aided detection and characterization of lesions (e.g., colonic polyps, pulmonary nodules) from cross-sectional image data, visualization and automated assessment of 4D ultrasound data, and fusion of images acquired using different modalities (e.g., CT and MR). He has also been involved in developing and evaluating techniques for exploring cross-sectional imaging data from an internal perspective, i.e., virtual endoscopy (including colonoscopy, angioscopy, and bronchoscopy), and in the quantitation of structure parameters, e.g., volumes, lengths, medial axes, and curvatures. Finally, he is also interested in creating workable solutions to the problem of "data explosion," i.e., how to look at the thousands of images generated per examination using modern CT and MR scanners. He is co-director of the Radiology 3D and Quantitative Imaging Lab, providing clinical service to the Stanford and local community, and and co-Director of IBIIS (Integrative Biomedical Imaging Informatics at Stanford), whose mission is to advance the clinical and basic sciences in radiology, while improving our understanding of biology and the manifestations of disease, by pioneering methods in the information sciences that integrate imaging, clinical and molecular data.



James Duncan

James Duncan, the Ebenezer K. Hunt Professor of Biomedical Engineering, has focused his research and teaching in the areas of biomedical image processing and analysis. Duncan is the associate chair and director of undergraduate studies in the Department of Biomedical Engineering as well as the vice-chair for bioimaging sciences research in diagnostic radiology. He is particularly interested in the use of model-based mathematical strategies for the analysis of biomedical images. He helped pioneer the use of geometrical models for segmenting deformable (typically anatomical) objects of approximately known shape and for tracking certain forms of non-rigid object motion, and later soft tissue deformation, most notably that of the heart. Duncan is a fellow of the Institute of Electrical and Electronics Engineers (IEEE) and the American Institute for Medical and Biological Engineering. He is president of the International Society for Medical Image Computing and Computer Assisted Intervention and is a member of the American Association for Artificial Intelligence and the I.E.E.E. Computer Society, among other professional organizations.



Sandy Wells

Dr Wells is researcher in medical image analysis with the Surgical Planning Laboratory, a unit of the MRI division of the Radiology Department of Brigham and Women's Hospital, Harvard Medical School. He maintain an active collaboration with the MIT Computer Science and Artificial Intelligence Laboratory, where he worked with a talented group of graduate students. He is also affiliated with the Harvard-MIT Division of Health Sciences and Technology. His work has focused primarily on the analysis of structural and functional MRI, including segmentation and registration of MRI, with some emphasis on applications in image-guided surgery. Dr Wells’ research in medical image registration concerns the use of Mutual Information as a criterion for image fusion. This approach has become the de-facto standard for multi-modality problems. Implementations of this method are available in 3D Slicer, an open-source platform for medical image analysis, and in ITK, an NIH sponsored segmentation and registration library. In addition to morphological analysis, he is also interested in univariate and multivariate analysis of functional MRI.



Bennett Landman

Bennett Landman graduated with a bachelor of science (’01) and master of engineering (’02) in electrical engineering and computer science from the Massachusetts Institute of Technology, Cambridge, MA. After graduation, he worked in an image processing startup company and a private medical imaging research firm before returning for a doctorate in biomedical engineering (‘08) from Johns Hopkins University School of Medicine, Baltimore, MD. Since 2010, he has been with the Faculty of the Electrical Engineering and Computer Science Department, Vanderbilt University, Nashville, TN, where he is currently an associate professor. His research concentrates on applying image-processing technologies to leverage large-scale imaging studies to improve understanding of individual anatomy and personalize medicine.



Alejandro Frangi

Professor Frangi is Diamond Jubilee Chair in Computational Medicine at the University of Leeds, Leeds, UK, with joint appointments at the School of Computing and the School of Medicine. He leads the CISTIB Center for Computational Imaging and Simulation Technologies in Biomedicine. He has been awarded a Royal Academy of Engineering Chair in Emerging Technologies (2019-2029). Professor Frangi has edited several books, published 7 editorial articles and over 215 journal papers in key international journals of his research field and more than over 200 book chapters and international conference papers with an h-index 55 and over 20,700 citations according to Google Scholar. He has been three times Guest Editor of special issues of IEEE Trans Med Imaging, one on IEEE Trans Biomed Eng, and one of Medical Image Analysis journal. He was chair of the 3rd International Conference on Functional Imaging and Modelling of the Heart (FIMH05) held in Barcelona in June 2005, Publications Chair of the IEEE International Symposium in Biomedical Imaging (ISBI 2006), Programme Committee Member of various editions of the Intl Conf on Medical Image Computing and Computer Assisted Interventions (MICCAI) (Brisbane, AU, 2007; Beijing CN, 2010; Toronto CA 2011; Nice FR 2012; Nagoya JP 2013), International Liaison of ISBI 2009, Tutorials Co-Chair of MICCAI 2010, and Program Co-chair of MICCAI 2015. He was also General Chair for ISBI 2012 held in Barcelona. He is the General Chair of MICCAI 2018 held in Granada, Spain. Professor Frangi is Chair of the Editorial Board of the MICCAI-Elsevier Book Series (2017-2020), and serves as Associate Editor of IEEE Trans on Medical Imaging, Medical Image Analysis, SIAM Journal Imaging Sciences, Computer Vision and Image Understanding journals. Professor Frangi was foreign member of the Review College of the Engineering and Physical Sciences Research Council (EPSRC, 2006-10) in UK, is a recipient of the IEEE Engineering in Medicine and Biology Early Career Award in 2006, the ICT Knowledge Transfer Prize (2008) and two Teaching Excellence Prizes (2008, 2010) by the Social Council of the Universitat Pompeu Fabra. He also was awarded the UPF Medal (2011) for his service as Dean of the Escuela Politècnica Superior. He was awarded the ICREA-Academia Prize by the Institució Catalana de Recerca i Estudis Avançats (ICREA) in 2008. Professor Frangi is an IEEE Fellow (2014), EAMBES Fellow (2015), SPIE Member, SIAM Member, MICCAI Member, and elected member to the Board of Directors of the Medical Image Computing and Computer Assisted Interventions (MICCAI) Society (2014-2018). Professor Frangi serves in the Scientific Advisory Board of the European Institute for Biomedical Imaging Research (EIBIR) and was Chair of the Fellows Committee of the IEEE EMBS (2017-2018).



Thomas Fuchs





Brittany Dugger

Dr. Dugger is a PhD trained neuropathologist/neuroanatomist. Throughout her career she has served as an interface to the fields of neurology and neuropathology, resulting in more than 50 peer-reviewed manuscripts and numerous private, state, and federally funded grants. Dr. Dugger earned her Bachelor of Science from Michigan State University. She went on to obtain her PhD from Mayo Clinic Graduate School, where she became fascinated by the selective vulnerability of neuropathologies through her thesis work under the direction of Dr. Dennis Dickson. She then completed a postdoctoral fellowship under Dr. Thomas Beach, being promoted to an independent staff scientist at the Banner Sun Health Research Institute in Sun City, Arizona, aiding in a research-based human autopsy program. In 2015, she was recruited by Dr. Stanley Prusiner to serve as the neuropathology core leader for academic and drug discovery groups within the Institute of Neurodegenerative Diseases at the University of California San Francisco. In 2018, she became an assistant professor of Pathology at the University of California Davis. In addition to running her own laboratory she supports the University of California Davis-Alzheimer’s Disease Center as a neuropathology core leader alongside Dr. Lee-Way Jin, Professor and Director of Neuropathology. Her laboratory focuses on: Understanding heterogeneity within neurodegenerative diseases and understanding the interaction of peripheral changes to aging and neurodegenerative diseases.



Yukako Yagi

Dr. Yukako Yagi’s Digital Pathology Laboratory at the Josie Robertson Surgical Center serves as an incubator to explore, evaluate and develop new technology to advance digital pathology in a clinical setting and actively engage vendors to help improve the technology and develop clinical applicability. Collaborations with clinical departments (e.g., Surgery), Radiology, Medical Physics, and Informatics groups, enhance these assessments and creates opportunities for multidisciplinary applications. Dr. Yagi completed her Doctorate in Medical Science at Tokyo Medical University in Japan. She has a broad interest in various aspects of medical science, which include the development and validation of technologies in digital imaging, such as color and image quality calibration, evaluation and optimization, digital staining, 3D imaging, and decision support systems for pathology diagnosis, research and education. Since joining MSK, she has led pioneering work using MicroCT, Whole Slide Imaging (WSI) and Confocal imaging to connect multi-dimensional and multi-modality images (e.g., single-cell to whole-body analysis). She participated in creating image viewers for several imaging modalities and established new imaging data formats. Her team has established the technology to streamline colorization within Pathology 3D, i.e., H&E, immuno-florescent, immuno-histochemistry, and florescence in situ hybridization imaging. Once the colorization is mapped, it can be correlated with another modality such as radiology, for a holistic analysis that will improve patient care and outcomes. The team also created 3D histology images of a single organ using thousands of slides. Dr. Yagi’s work further enriches our knowledge of disease by integrating computational pathology data with other specimen-related data (genomics, proteomics, radiographic imaging, etc.). This brings an unprecedented breadth and depth of information to each individual case and yields a comprehensive, multidimensional analysis that would otherwise be impossible.



Tina Kapur

Tina Kapur is the Executive Director of Image Guided Therapy in the Department of Radiology at Brigham and Women's Hospital and Harvard Medical School. Dr. Kapur’s research interests and accomplishments are in the area of medical image computing and computer aided interventions in image-guided neurosurgery, surgical navigation, and MR-guided pelvic brachytherapy. She has numerous publications in medical image segmentation, and is the holder of several issued US and international patents in the field of surgical navigation. She leads national and international outreach and collaboration efforts for image-guided therapy and is particularly interested in fostering collaborations between efforts in open science to accelerate important discoveries that improve health and save lives. She is the founding director for the first open-science hackathons for medical image computing, "NA-MIC Project Week", which began in 2005, and has been running continuously (twice a year) since then. She received her Ph.D. in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology in 1999. She was the Chief Scientist at a Boston area surgical navigation company, Visualization Technology Inc., and upon its acquisition by GE Healthcare, the Chief Scientist at the GE Navigation.



Jayashree Kalpathy-Kramer

Dr. Kalpathy-Kramer’s research lies at the intersection of machine learning, statistics, informatics, image acquisition and analysis with a goal towards clinical translation. She is an electrical engineer by training, having receied a B.Tech in EE from IIT Bombay and a PhD in EE from Rensselaer Polytechnic Institute. After a number of years in the semiconductor industry, she returned to academia following a MS in Biomedical Informatics from OHSU. Her current projects include quantitative imaging in cancer, image analysis and decision support for retinal imaging, cloud computing, mathematical modeling of drug delivery in cancer, crowd sourcing and challenges, algorithm development and deep learning.



Daniel L. Rubin

Daniel L. Rubin, MD, MS is Professor of Biomedical Data Science, Radiology, Medicine (Biomedical Informatics), and Ophthalmology (courtesy) at Stanford University. He is Principal Investigator of two centers in the National Cancer Institute's Quantitative Imaging Network (QIN) and is Director of Biomedical Informatics for the Stanford Cancer Institute. He also leads the Research Informatics Center (RIC) of the School of Medicine (https://med.stanford.edu/ric.html). He previously chaired the Informatics Committee of the ECOG-ACRIN cooperative group, of the QIN Executive Committee, and of the RadLex Steering Committee of the Radiological Society of North America. His NIH-funded research program focuses on quantitative imaging and integrating imaging data with clinical and molecular data to discover imaging phenotypes that can predict the underlying biology, define disease subtypes, and personalize treatment. He is a Fellow of the American Institute for Medical and Biological Engineering (AIMBE), Fellow of the American College of Medical Informatics (ACMI), Fellow of the Society of Imaging Informatics in Medicine (SIIM), and recipient of the Distinguished Investigator Award from the Academy for Radiology & Biomedical Imaging Research. He has published over 240 scientific publications in biomedical imaging informatics and radiology.



Ajay Royyuru

Ajay Royyuru leads Healthcare & Life Sciences research at IBM. His team is actively pursuing high quality science, developing novel technologies and achieving translational insights across this industry, including areas of cancer, cardiac, neurological, mental health, immune system, and infectious diseases. Scientific interests and active projects include genomics, protein science, systems biology, computational neuroscience, health informatics, miniaturizing for medical devices, and nano-biotechnology. Working with institutions around the world, he is engaged in research that will advance personalized, information-based medicine. Ajay previously led the life sciences research portfolio through the Computational Biology Center. Ajay has authored numerous research publications and several patents in structural and computational biology. His work has featured in The New York Times, The Washington Post, BBC, Forbes, Scientific American, Nature Medicine, and Nature news articles. After his undergraduate and masters education in human biology and biophysics from All India Institute of Medical Sciences, New Delhi, Ajay obtained his Ph. D. in molecular biology from Tata Institute of Fundamental Research, Mumbai. He had postdoctoral training at Memorial Sloan-Kettering Cancer Center, New York and a brief stint at scientific software development before joining IBM Research. In 2016 Ajay was named an IBM Fellow, the company's pre-eminent technical distinction. Ajay is a member of International Society for Computational Biology and IBM Academy of Technology.



Tanveer Syeda-Mahmood

Dr. Tanveer Syeda-Mahmood is an IBM Fellow and Chief Scientist/overall lead for the Medical Sieve Radiology Grand Challenge project in IBM Research, Almaden. Medical Sieve is an exploratory research project with global participation from many IBM Research Labs around the world including Almaden Labs in San Jose, CA, Haifa Research Labs in Israel and Melbourne Research Lab in Australia. The goal of this project is to develop automated radiology and cardiology assistants of the future that help clinicians in their decision making. Dr. Syeda-Mahmood graduated from the MIT AI Lab in 1993 with a Ph.D in Computer Science. Prior to IBM, she worked as a Research Staff Member at Xerox Webster Research Center, Webster, NY. She joined IBM Almaden Research Center in 1998. Prior to coming to IBM, Dr. Syeda-Mahmood led the image indexing program at Xerox Research and was one of the early originators of the field of content-based image and video retrieval. Currently, she is working on applications of content-based retrieval in healthcare and medical imaging. Over the past 30 years, her research interests have been in a variety of areas relating to artificial intelligence including computer vision, image and video databases, medical image analysis, bioinformatics, signal processing, document analysis, and distributed computing frameworks. She has over 200 refereed publications and over 80 patent filed. Dr. Syeda-Mahmood was the General Chair of the First IEEE International Conference on Healthcare Informatics, Imaging,and Systems Biology, San Jose, CA 2011. She was also the program co-chair of CVPR 2008. Dr. Syeda-Mahmood is a Fellow of IEEE. She is also a member of IBM Academy of Technology. Dr. Syeda-Mahmood was declared Master Inventor in 2011. She is the recipient of key awards including IBM Corporate Award 2015, Best of IBM Award 2015, 2016 and several outstanding innovation awards.



Orest B. Boyko

Orest B. Boyko MD PhD is an American Board of Radiology board certified radiologist with an additional ABR certificate of added qualifications in Neuroradiology. Dr. Boyko has been an Associate Professor since 2007 at the University of Southern California in Los Angeles California, and currently joined in 2017 the USC Bridge Institute housed in the USC Michelson Center for Convergent Bioscience on the main campus of USC. As a radiologist, Dr. Boyko as been working in the Ai research community as a physician consultant since Dec 2013 in multi-modal mining in Healthcare in the research lab of Dr. Tanveer Sayeda-Mahmood in the IBM Almaden Research Center 650 Harry Road, San Jose, CA 95120 which has developed natural language processing applications to the electronic health record to assist in clinical decision support. Dr. Boyko has also been since its inception involved the currently concluding IBM Healthcare Initiative in Radiology called the IBM Medical Sieve Radiology Grand Challenge in initial cutting edge research development of a radiology and cardiology cognitive assistant. Recently Dr. Boyko accepted an invitation to chair the newly created Guerbet Digital Solutions Ai Advisory Board and to contribute to the Guerbet initiative to create an Ai community in conjunction with Applied Radiology. Dr Boyko has developed a focus on the need for education tools for healthcare providers wanting to learn about Ai and Machine and Deep Learning and to better understand their applications in healthcare. Dr. Boyko is active in advancing learning initiatives for the field of Ai and machine learning. Dr. Boyko has co-authored over 100 papers and book chapters in the field of radiology, neuroradiology and MRI.



Charles Kahn

Dr. Charles Kahn is Professor and Vice Chair of Radiology at the University of Pennsylvania Perelman School of Medicine. He earned his Bachelor of Arts in Mathematics at the University of Wisconsin‚ Madison, his M.D. at the University of Illinois, and completed radiology residency at the University of Chicago, where he served as chief resident. He served on the faculty of the University of Chicago and the Medical College of Wisconsin before moving to his current position at the University of Pennsylvania. He earned a Master's degree in Computer Sciences from UW-Madison in 2003. He is a Board-certified, practicing radiologist with expertise in body CT and ultrasound. Professional interests include health services research, comparative effectiveness research, artificial intelligence, decision support, information standards, and knowledge representation. He has received the Gold Medal of the American Roentgen Ray Society, and has been elected a Fellow of the American College of Radiology, American College of Medical Informatics, and Society for Imaging Informatics in Medicine. He is author of more than 110 scientific publications, and serves as Editor of Radiology: Artificial Intelligence.



Curtis Langlotz

Dr. Langlotz's laboratory investigates the use of deep neural networks and other machine learning technologies to help radiologists detect disease and eliminate diagnostic errors. His laboratory’s translational approach facilitates rapid evaluation and dissemination of the resulting algorithms. He is responsible for the information technology that supports Stanford’s radiology practice, including 6 million imaging studies that require 0.5 petabytes of storage. Dr. Langlotz has led many recent national and international efforts to improve the quality of radiology communication, including the RadLex™ terminology standard, the RadLex™ Playbook of radiology exam codes, the RSNA report template library, and a technical standard for communication of radiology templates. He has published over 100 scholarly articles, and is author of the recent book “The Radiology Report: A Guide to Thoughtful Communication for Radiologists and Other Medical Professionals”. Raised in St. Paul, Minnesota, Dr. Langlotz received his undergraduate degree in Human Biology, masters in Computer Science, MD in Medicine, and PhD in Medical Information Science, all from Stanford University. He is a founder and past president of the Radiology Alliance for Health Services Research, served as chair of the Society for Imaging Informatics in Medicine (SIIM), and as a board member of the American Medical Informatics Association and the Association of University Radiologists. He is a fellow of the American College of Medical Informatics and currently serves as president of the College of SIIM Fellows and as a board member of the Radiological Society of North America. He is a recipient of the Lee B. Lusted Research Prize from the Society of Medical Decision Making and the Career Achievement Award from the Radiology Alliance for Health Services Research. He has founded three healthcare information technology companies, most recently Montage Healthcare Solutions, which was acquired by Nuance Communications in 2016.



Maria Gabrani

Maria has been a Research Staff Member at IBM Research – Zurich since 2001. Her research has focused primarily on image processing and pattern recognition techniques to extract meaningful information from data in different application areas from computational lithography to drug discovery. Currently she is focusing on developing methods and tools to analyze histopathological and gene expression images for clinical purposes. Maria received a B.S. (Diplom) degree in Electrical Engineering from Aristoteleion Univeristy in Thessaloniki, Greece, in 1993, and M.Sc. and Ph.D. degrees in Electrical and Computer Engineering from Drexel University, Philadelphia, USA, in 1997 and 1998, respectively. During her M.Sc. and Ph.D work, she conducted research in the area of medical imaging with applications to neuroimaging. Prior to joining IBM, Maria was a senior researcher at Philips Research, Eindhoven, The Netherlands, from 1999 to 2001, where she worked on quality of service for video applications and programmable video-processing architectures. She also served an internship at Sensar (subsidiary of Sarnoff) in the summer of 1999, where she worked on retina images from wide-field-of-view cameras. Maria holds more than 25 US patents, and has received several awards including two Outstanding Technical Achievement awards from the IBM Corporation, a Technical Achievement Award from the IBM Research Division and best paper awards, among them from NASA/Goddard Space Flight Center, Image Registration Workshop.



Eliot Siegel

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. Dr. Siegel was responsible for the NCI's National Cancer Image Archive and served as Workspace Lead of the National Cancer Institute's caBIG In Vivo Imaging Workspace. He has been named as Radiology Researcher and Radiology Educator of the year by his peers as well as one of the Top Ten radiologists. Under his leadership, the VA Maryland Healthcare System became the first filmless healthcare enterprise in the world. He has written over 200 articles and book chapters about PACS (Picture Archiving and Communication Systems) and digital imaging, and has edited six books on the topic, including Filmless Radiology and Security Issues in the Digital Medical Enterprise. He has made more than 1,000 presentations throughout the world on a broad range of topics involving computer applications in imaging and medicine. Dr. Siegel served as symposium chairman for the Society of Photo-optical and Industrial Engineers (SPIE) Medical Imaging Meeting for three years, and is currently serving on the board of directors of the Society of Computer Applications in Radiology. He is a fellow of the American College of Radiology and of the Society of Imaging Informatics in Medicine.



Joel S. Schuman

Joel S. Schuman is an American ophthalmologist, specialising in glaucoma. In 2016 he was appointed Director of NYU Langone Eye Center and Professor and Chairman of Ophthalmology at NYU Langone Medical Center, NYU School of Medicine, and Professor of Biomedical, Electrical and Computer Engineering at NYU Tandon School of Engineering. In 2016 he was also appointed Professor of Neuroscience and Physiology and a member of the Neuroscience Institute, at NYU Langone Medical Center, NYU School of Medicine. In 2017 he became Professor of Neural Science in the Center for Neural Science at NYU. From 2003 - 2016 he was the Professor and Chairman of Ophthalmology at the Eye and Ear Institute, University of Pittsburgh School of Medicine, the Eye and Ear Foundation Endowed Chair and Director of the University of Pittsburgh Medical Center (UPMC) Eye Center. He was also Professor of Bioengineering at the Swanson School of Engineering, University of Pittsburgh and Director of the Louis J. Fox Center for Vision Restoration of UPMC and the University of Pittsburgh.[1] He was a member of the McGowan Institute for Regenerative Medicine and the Center for the Neural Basis of Cognition, Carnegie Mellon University and University of Pittsburgh. He became a Distinguished Professor of Ophthalmology at the University of Pittsburgh in September 2014.



Hayit Greenspan

Prof. Greenspan heads the Medical Image Processing and Analysis Lab at the Biomedical Engineering Dept. in the Faculty of Engineering, Tel-Aviv University. Prof. Greenspan has been conducting research in image processing and computer vision for the past 20 years, with a special focus on deep learning, image modeling and analysis, resolution augmentation, and content-based image retrieval. Prof. Greenspan received the B.S. and M.S. degrees in Electrical Engineering from the Technion- Israel Institute of Technology, in 1986 and 1989, respectively, and the Ph.D. degree in Electrical Engineering from CALTECH – California Institute of Technology, in 1994. She was a Postdoc with the Computer Science Division at U.C. Berkeley from 1995 to 1997. In 1997 she joined Tel-Aviv University. From 2008 until 2011, Prof. Greenspan was a visiting Professor at Stanford University, Department of Radiology, Faculty of Medicine. She was also a visiting researcher at IBM Research in the Multi-modal Mining for Healthcare group, in Almaden CA. She is now also affiliated with the Computer Science Institute (ICSI) at Berkeley, CA. Prof. Greenspan has 51 journal publications in top-ranking journals, and more than 100 conference publications. She is the inventor of several patents. She is an Associate Editor of the top ranking journal in Medical imaging (IEEE-TMI) and is an active member of several international professional societies.