• RSNA 2018 Spotlight Course - Paris, France
  • Course Presenters

    Safwan Halabi, MD

    Safwan Halabi, MD - Course Director/Presenter

    Safwan Halabi, MD is a Clinical Associate Professor of Radiology at the Stanford University School of Medicine and serves as the Medical Director for Radiology Informatics at Stanford Children's Health. He is board-certified in Radiology with a Certificate of Added Qualification in Pediatric Radiology. He is also board-certified in Clinical Informatics. He clinically practices obstetric and pediatric imaging at Lucile Packard Children's Hospital. Dr. Halabi’s clinical and administrative leadership roles are directed at improving quality of care, efficiency, and patient safety. He has also lead strategic efforts to improve the enterprise imaging platforms at Stanford Children’s Health. He is a strong advocate of patient-centric care and has helped guide policies for radiology report and image release to patients. He has published in peer-reviewed journals on various clinical and informatics topics. His current academic and research interests include imaging informatics, deep/machine learning in imaging, artificial intelligence in medicine, clinical decision support and patient-centric health care delivery. He is currently leading the RSNA Informatics Data Science Committee and serves as a Board Member for the Society for Imaging Informatics in Medicine.

    An Tang, MD, MSc, FRCPC

    An Tang, MD, MSc, FRCPC - Course Director/Presenter

    An Tang, MD, MSc, FRCPC is an Associate Professor of Radiology at the University of Montreal and practices abdominal radiology at the Centre hospitalier de l’Université de Montréal (CHUM). He serves as Director of Abdominal Imaging Research at the CHUM Research Center. He is a proponent of noninvasive imaging biomarkers. He has active research funding from the Canadian Institutes of Health Research. His current academic and research interests include imaging biomarkers of chronic liver disease and detection of liver cancer using artificial intelligence techniques. He is a member of the Liver Imaging Reporting and Data System (LI-RADS) Steering Committee and current Chair of its International Working Group. He is also the current Chair of the Canadian Association of Radiologists Artificial Intelligence Working Group. 

    Marc Zins, MD

    Marc Zins, MD - Course Director/Presenter

    Marc Zins, MD currently practices as Chairman of the Radiology department at Saint Joseph Hospital, René Descartes University, Paris, France. Dr. Zins received his medical degree from the Medical Faculty of Paris in 1991. He has authored over 120 peer reviewed papers, 20 book chapters, and one book. He reviews for numerous scientific journals including Radiology and European Radiology. He also acts as Associate Editor for Radiology since 2018. Dr. Zins’ main areas of clinical expertise and research include pancreatic and liver diseases and imaging of the acute abdomen. Dr. Zins is Secretary-Treasurer of the European Society of Gastro-Intestinal and Abdominal Radiology, he is the Past President of the French Society of Abdominal Radiology and currently serves as Secretary General of the French Society of Radiology.

    Kristen Yeom, MD

    Kristen Yeom, MD - Presenter

    Kristen Yeom, MD is an Associate Professor of Radiology and Associate Director of MRI at Lucile Packard Children’s Hospital at Stanford University School of Medicine in Palo Alto, CA, with subspecialty in Pediatric Neuroradiology. She obtained a medical degree from University of Michigan, Diagnostic Radiology residency at UCLA School of Medicine, and Neuroradiology fellowship at Stanford University. Dr. Yeom’s research has focused on clinical and translational studies of advanced MRI methods, such as diffusion, perfusion, and quantitative susceptibility MRI, as well as novel image processing tools for improved understanding of normal neural development and diagnosis and management of neurological and neuro-oncologic diseases. Her recent works include radiomic and machine-learning strategies for pediatric brain tumor classification, as well as computer vision tasks for clinical neuroimaging diagnostics, such as deep neural networks for assessing normal fetal and pediatric brain development and creation of deep learning classifier models for brain and neurovascular pathologies.

    Nabile Safdar, MD, MPH

    Nabile Safdar, MD, MPH - Presenter

    Nabile M. Safdar, MD, MPH believes that technology can be leveraged to continuously improve the quality of health care delivery and save lives. This belief motivates his work as Associate CMIO at Emory Healthcare and the Vice Chair of Informatics in the Department of Radiology and Imaging Sciences. Dr. Safdar completed his Imaging Informatics fellowship at the University of Maryland in Baltimore, MD. He is a pediatric radiologist board certified in clinical informatics, and currently one of the Co-Directors of the National Imaging Informatics Curriculum. His research interests have included computational approaches to pediatric imaging, the intersection of quality and informatics in healthcare, and exploring ethical issues associated in medical imaging. 

    Erik R. Ranschaert, MD, PhD

    Erik R. Ranschaert, MD, PhD - Presenter

    Erik Ranschaert,MD, PhD completed his medical training at the KU Leuven in Belgium. He works as a radiologist at the ETZ teaching hospital in Tilburg in the Netherlands. In 2016 he obtained his PhD degree at the University of Antwerp with a thesis titled "The impact of information technology on radiology services”. Since 2017 he is Certified Imaging Informatics Professional (CIIP). He fulfilled a leadership role in the e-Healh and Informatics Subcommittee of the European Society of Radiologists (ESR) and currently is the Vice-President of the European Society of Medical Imaging Informatics (EuSoMII). He often is an invited speaker and lectured at international meetings such as the European Congress of Radiology (ECR), RSNA, JFR, UKRC and other. He is Chief Medical Officer for the Diagnose.me platform and has an advisory role at MedicalPHIT and Barco. He is Co-Editor of a Springer book about Artificial Intelligence in Radiology that hopefully will be published by the end of 2018. Several authors from the US, Europe and Australia are contributing.

    Laure Fournier, MD, PhD

    Laure Fournier, MD, PhD - Presenter

    Laure Fournier, MD, PhD works as a Professor at the Hôpital Européen Georges Pompidou, in Paris, France. Her time is divided between clinical work on urogenital cancers, and imaging research in the Laboratoire de Recherche en Imagerie (INSERM U970). She is working on functional imaging, radiomics and big data, to extract quantitative parameters from images reflecting tumour physiology and biology, more specifically to define response to therapy, particularly for targeted therapies requiring new response criteria.

    Katherine Andriole, PhD

    Katherine Andriole, PhD - Presenter

    Katherine Andriole, PhD is an Associate Professor of Radiology at Harvard Medical School, Brigham and Women’s Hospital, and was recently named the Director of Research Strategy and Operations at the MGH & BWH Center for Clinical Data Science (CCDS). She studied Biomedical Engineering, and Electrical Engineering and Medicine at Duke University and Yale University, respectively, and did postdoctoral fellowships at the University of California at Los Angeles, and the University of California at San Francisco (UCSF) Departments of Radiology. At UCSF, Dr. Andriole was instrumental in designing, building and implementing picture archiving and communication systems (PACS) before they became commercial entities. Her research has involved technical as well as clinically-relevant developments in medical informatics, PACS, digital radiography, image processing and analysis, business analytics and machine learning. Dr. Andriole has developed and taught several formal courses, directed fellowships in biomedical imaging and informatics, and mentored more than 70 trainees. She has served in multiple leadership roles for the Society of Imaging Informatics in Medicine (SIIM), currently serves on the Radiological Society of North America (RSNA) Radiology Informatics Committee and the RSNA Machine Learning Steering Committee, and is the Senior Scientist for Education at the American College of Radiology (ACR) Data Science Institute. She is an Associate Editor of the Journal of Digital Imaging and the Journal of Medical Imaging. Dr. Andriole has been elected a member of the Academy of Harvard Medical School, inducted into the SIIM College of Fellows, and named Second Vice President of the RSNA.

    Hugh Harvey, MD

    Hugh Harvey, MD - Presenter

    Hugh Harvey, MD is a consultant radiologist and academic, trained in the NHS and Europe’s leading cancer research center, the Institute of Cancer Research, where he was twice awarded ICR Science Writer of the Year. He led the regulatory affairs team at Babylon Health, the UK's largest digital health start-up, successfully gaining the world-first CE marking for an AI-supported triage service. He is a Royal College of Radiologists informatics committee member, and board advisor to many AI start-up companies across the globe, including Algomedica, Smart Reporting and Agamon. He is Clinical Director at Kheiron Medical, a UK start-up focused on deep learning in breast cancer screening. He has recently been selected to Co-Chair the Topol health technology review for Health Education England and the Secretary of State for Health and Social Care, and is Associate Editor of the global open source scientific journal Nature: Digital Medicine.

    Luke Oakden-Rayner, MD

    Luke Oakden-Rayner, MD - Presenter

    Luke Oakden-Rayner, MD is a radiologist and medical researcher. He completed his medical training at the University of Adelaide, and is a Fellow of the Royal Australian and New Zealand College of Radiology. He is undertaking a PhD at the University of Adelaide and is a research associate of the Australian Institute of Machine Learning, developing and exploring artificial intelligence systems for use in medical imaging. He has lectured at the University of Adelaide and the University of Melbourne, and is regularly invited to speak about the intersection of medicine and artificial intelligence at conferences, on podcasts, and to the media. He is a passionate science communicator, and writes a popular academic blog on medical artificial intelligence and radiology at https://lukeoakdenrayner.wordpress.com/. He can also be found on Twitter (@drlukeor) and Reddit (/u/drlukeor) discussing these topics.

    Marie-Pierre Revel, MD, PhD

    Marie-Pierre Revel, MD, PhD - Presenter

    Marie-Pierre Revel, MD, PhD is a Professor of Radiology (Head of Cardiothoracic Imaging) at the Cochin Hospital, Paris Descartes University in Paris, France. She also serves as the Current President of the European Society of Thoracic Imaging. Dr. Revel finished her Medical Degree at the Necker-Enfants Malades Faculty of Medicine, Paris 5 University. Her Master's Degree was completed in Ethics at the Paris 5 University and her PhD in Science at the Lille 2 University. She also holds a Research Supervision Certification from Paris Descartes University. Dr. Revel has a large number of publications in various topics. 

    Guillaume Chassagnon, MD

    Guillaume Chassagnon, MD - Presenter

    Guillaume Chassagnon, MD is a radiologist at Cochin Hospital in Paris and also a PhD candidate at the CentraleSupelec University in France. His focus is in the development of new quantitative imaging biomarkers for obstructive and interstitial lung diseases. Dr. Chassagnon completed his Medical Doctor Degree with Honors at the Francois Rabelais University. The specialty of the degree was in Radiology and the thesis was: "Association between tetralogy of fallot and tracheobronchial branching abnormalities: a new clue for pathogenesis?". Dr. Chassagnon's Master Degree was completed with Honors at the BioMedical Engineering (BME-Paris) and the Medical Education was completed at Pitié-Salpêtrière - University of Paris VI, Paris, France. Dr. Chassagnon has a significant amount of publications and an active patent. 

    Charles E. Kahn Jr. MD, MS

    Charles E. Kahn Jr. MD, MS - Presenter

    Charles E. Kahn Jr. MD, MS is professor and vice chair of the Department of Radiology at the University of Pennsylvania’s Perelman School of Medicine in Philadelphia. He is also a senior fellow of the Institute for Biomedical Informatics and the Leonard Davis Institute of Health Economics at Penn and was recently announced the Editor of Radiology: Artificial Intelligence. Dr. Kahn is a graduate of the University of Wisconsin–Madison, and earned his medical degree from the University of Illinois College of Medicine in 1985. He completed a diagnostic radiology residency at University of Chicago Medical Center. He received a Master of Science in Computer Sciences from UW–Madison in 2003. As a board-certified radiologist with a clinical specialty in abdominal imaging, Dr. Kahn’s research interests include health services, comparative effectiveness, decision support, information standards and knowledge representation.  

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