Peter B. Noël, Ph.D.
Department of Diagnostic and Interventional Radiology
Technische Universität München
Klinikum rechts der Isar
Ismaningerstr. 22, 81675 München
Chair of Biomedical Physics
Techniche Universität München
James-Franck-Strasse 1, 85748 Garching
phone: +49 (0) 89 4140 7220
Peter B. Noël, Ph.D. (2009, Computer Science, State University of New York at Buffalo, United States). Dr. Noël is currently member of the Institute for Diagnostic and Interventional Radiology and of the Chair of Biomedical Physics. He is the Principle Investigator of the "image reconstruction & x-ray" group. For his undergraduate training Dr. Noël completed a degree in Biomedical Engineering at the University of Applied Sciences in Giessen, Germany. While conducting research in the area of intervential imaging at the Toshiba Stroke Research Center (Buffalo, NY), he received a Masters degree in Computer Science. In 2009 he finalized his Ph.D. in Computer Science from SUNY at Buffalo with focus on advanced 3D reconstruction algorithms. Currently his primary research interest is in the area of Computed Tomography and includes diagnostic and interventional 2D and 3D x-ray imaging, tomographic reconstruction, statistical reconstruction approaches, phase contrast imaging, spectral imaging with photon counting detectors, imaging on micro / nano scale, high performance computing with GPUs and clinical translation of advanced technologies. Dr. Noëls research efforts are currently supported by national as well as industrial grants. His achievements in the area of radiation exposure for CT imaging were awarded with a research award from the Behnker-Berger foundation.
The "image reconstruction & x-ray" Lab is located in the Institute for Diagnostic and Interventional Radiology at Klinikum rechts der Isar der Technischen Universität München and is under the direction of Peter B. Noël, PhD. The lab is connected with the Chair of Biomedical Physics at TUM.
The "image reconstruction & x-ray" Lab is dedicated to developing next generation x-ray and computed tomography solutions for improved diagnostics at lowest radiation exposures and to make additional diagnostic and therapy information available that exceeds plain absorption. Our clinical research interest lies in development of advanced reconstruction algorithms and their clinical evaluation. With respect to current developments in clinical computer tomography, we are interested in the revival of statistical iterative reconstruction methods and their thrust in improved diagnostic quality while reducing radiation exposure. More advanced iterative approaches are currently making their way into the clinical arena, which bring up very interesting questions we are answering for the development of next-generation statistical iterative approaches.
When it comes to diagnostics and therapy monitoring, the current tendency is to look at simple ‘gray-values’ (representing attenuation) and contrast differences to determine whether anatomical or pathological changes have occurred. In order to extend current possibilities and limitations of x-ray radiography and computed tomography, several new approaches are coming up on the horizon, namely spectral / photon-counting and phase-contrast / dark-field imaging. Both of these technologies promise to significantly extend current diagnostic possibilities; however, clinical standards, for example with respect to radiation exposure and acquisition speed, need to be maintained for a future clinical system. To be part of solving the remaining challenges and to fulfill current clinical standards, we are dedicated to the development of advanced reconstruction algorithms.
Our strong collaboration with experts in clinical departments and the medical device industry guides and accelerates the translation of new technologies into early clinical application.
Peter B. Noël, Ph.D.
Melanie Kimm, Dr. rer. hum. biol.
Stephan Engels (Ph.D. Student)
Felix Kopp (Ph.D. Student)
Kai Mei (Ph.D. Student)
Prof. Dr. Mats Danielsson, KTH Royal Institute of Technology
Prof. Dr. Philippe Douek, Claude Bernard University Lyon
PD Dr. Torsten Enßlin, Max-Planck-Institut für Astrophysik
Prof. Dr. Martin Fiebich, Institut für Medizinische Physik und Strahlenschutz, Technische Hochschule Mittelhessen
Prof. Dr. Kenneth Hoffmann, University at Buffalo, The State University of New York
Prof. Dr. Gabriele Multhoff, Experimentelle Radioonkologie und Strahlenbiologie, Technische Universität München
Prof. Dr. Nassir Navab, Chair for Computer Aided Medical Procedures & Augmented Reality, Technische Universität München
Prof. Dr. Franz Pfeiffer, Chair of Biomedical Physics, Technische Universität München
Prof. Dr. Hiroyuki Yoshida, Massachusetts General Hospital, Harvard University
We are always looking for highly skilled and highly motivated individuals to add to the research team. Please do send us an email. However, please include a CV and take a moment to read a few of our publications and let us know specifically what you find interesting and how your skills would contribute. Thanks!
Noël, P. B., Walczak, A. M., Xu, J., Corso, J. J., Hoffmann, K. R., & Schafer, S. (2010). GPU-based cone beam computed tomography. Computer methods and programs in biomedicine, 98(3), 271-277.
Noël, P. B., Fingerle, A. A., Renger, B., Münzel, D., Rummeny, E. J., & Dobritz, M. (2011). Initial performance characterization of a clinical noise–suppressing reconstruction algorithm for mdct. American Journal of Roentgenology, 197(6), 1404-1409.
Noël, P. B., Renger, B., Fiebich, M., Münzel, D., Fingerle, A. A., Rummeny, E. J., & Dobritz, M. (2013). Does iterative reconstruction lower CT radiation dose: evaluation of 15,000 examinations. PloS one, 8(11), e81141.
Burger, K., Koehler, T., Chabior, M., Allner, S., Marschner, M., Fehringer, A., ... & Noël, P. (2014). Regularized iterative integration combined with non-linear diffusion filtering for phase-contrast x-ray computed tomography. Optics Express, 22(26), 32107-32118.
Hahn, D., Thibault, P., Fehringer, A., Bech, M., Koehler, T., Pfeiffer, F., & Noël, P. B. (2015). Statistical iterative reconstruction algorithm for X-ray phase-contrast CT. Nature Scientific Reports, 5.