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Norbert Pelc is Professor of Radiology, Emeritus. His primary research interests are in the physics, engineering, and mathematics of diagnostic imaging and the development of applications of this imaging technology. His current work focuses on computed tomography, specifically in methods to improve the information content and image quality and to reduce the radiation dose from these examinations. He holds a doctorate and master degrees in Medical Radiological Physics from Harvard University and a BS from the University of Wisconsin in Madison. He served on the first National Advisory Council of the National Institute of Biomedical Imaging and Bioengineering of the NIH. He is a member of the National Academy of Engineering and a Fellow of the American Association of Physicists in Medicine, the International Society for Magnetic Resonance in Medicine, the American Institute of Medical and Biological Engineering, and of SPIE.
Medical imaging has made enormous strides in recent decades. In clinical medicine, imaging plays an increasingly important role in patient care. A recent study found that internists rank the development of computed tomography (CT) and magnetic resonance imaging (MRI), together, as the most important innovation in medicine (Health Affairs, Vol 20, p. 30, 2001). At the same time, experts in a completely different scientific field, the National Academy of Engineering, ranks the development of imaging as one of the top 20 greatest engineering achievements of the 20th century (www.greatachievements.org), amazingly at a rank higher than that of household appliances and nuclear technology. Imaging is also taking on an increasing role in research, improving our understanding of both normal and diseased states and as a surrogate endpoint in the evaluation of therapies. Imaging allows serial studies in the same individual, thereby increasing statistical power and reducing the number of subjects needed in a study. Imaging is also a powerful tool to guide minimally invasive therapies.<br/><br/>The effectiveness of imaging and the powerful impact of visual images have led to a major increase in the utilization of this strategy, a trend that will continue but will evolve in coming years. Further advances will lead to improved detection, localization, and characterization of disease which should enable more accurate selection of optimized therapies for individual subjects (personalized medicine) as well as treatments that are more effective, less expensive, and less traumatic. Imaging will also play an increasingly important role in the challenges facing biomedical research.<br/><br/>There are many imaging modalities , each acquiring data using physical mechanisms such as x-ray transmission, nuclear magnetic resonance, acoustic or optical properties, and signals from radioactive tracers. Optimal design and utilization of each requires an appreciation of the underlying physical phenomena. Each modality uses sensors to detect signals and mathematical methods to covert the measured signals to images. Additional image processing methods are used to extract physiological information from the images.<br/><br/>My own interests center on the physics, engineering and mathematics of medical imaging. While I have worked on many imaging modalities over the past decades, my current projects are focused on computed tomography, digital x-ray imaging, and hybrid multimodality systems. An area of current focus is understanding the potential impact of a new class of x-ray detectors for CT imaging, energy discriminating photon counting detectors. They promise improved tissue characterization and dose efficiency, but currently available detectors have imperfections that detract from their performance. Important questions for this and other new technologies are: what are the real benefits and when is it worthwhile adopting them into clinical systems.<br/><br/>In addition to these technical projects, I am also interested in the development of new clinical and research applications of medical imaging. This is highly interdisciplinary research, incorporating not only the latest imaging technology but also fundamental appreciation of anatomy and pathophysiology.