Molekulare Bildgebung (Molecular imaging)

Muskuloskelettale Radiologie (Musculoskeletal Radiology)

 

 

Laboratory for Advanced Computed Tomography Imaging

Contact Details

Department of Diagnostic and Interventional Radiology
Technische Universität München
Klinikum rechts der Isar
Ismaningerstr. 22, 81675 München

phone: +49 (0) 89 4140 7220
email: peter.noel@tum.de

Mission

The "Laboratory for Advanced Computed Tomography Imaging" is dedicated to developing next generation x-ray and computed tomography solutions to make additional diagnostic and therapy information available that exceeds current clinical standards. 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, several new approaches are under investigation in our Lab, 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 future clinical systems.  To fulfill current clinical standardsnow and in the future, we are investigating new acquisition schemes (e.g. sparse sampling) in combination with advanced reconstruction algorithms. This type of approach is a central ingredient to our research: the harmonization between hardware and software, reconstruction as well as post processing, to achieve integrated clinical solutions. 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.The "Laboratory for Advanced Computed Tomography Imaging" is located in the Institute for Diagnostic and Interventional Radiology at Klinikum rechts der Isar der Technischen Universität München. The lab is connected with the Chair of Biomedical Physics at TUM.

Group Members

PI

Peter B. Noël, PhD 
  
Link to google scholar profileScholar
  
Link to LinkedIn
  
  
  

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"Laboratory for Advanced Computed Tomography Imaging". 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 biomedical imaging and includes x-ray imaging, Computed Tomography, advanced 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. Noël’sresearch 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.

  
Clinical PIs
  
Daniela Münzel, MD, MHBA
  
  
  
  
  
  
  
  
  
  
  
  
  
  
Alexander Fingerle, MD, MHBA
  
Staff
   

Veronica Bodek (Project Management)

Melanie Kimm, PhD

Research Fellows

Julia Dangelmaier, MD

Alexandra Gersing, MD

Martin Renz, MD

Isabelle Riederer, MD

Andreas Sauter, MD

Benedikt Schwaiger, MD

PhD Students

Felix Kopp, MSc

Kai Mei, MSc

Common PhD Students with Chair of Biomedical Physics

Media Echo

RSNA Daily Bulletin (Wednesday, December 04, 2013)

medtech zwo: Telemedizin auf Traumschiff (Jun 30, 2014)

TUM IdeAward zeichnet Ideen mit Marktpotenzial aus (Feb 20, 2015)

Collaborators

Mats Danielsson, KTH Royal Institute of Technology, Stockholm, Sweden.

Philippe Douek, Claude Bernard University Lyon, Lyon, France.

Torsten Enßlin, Max-Planck-Institut für Astrophysik, München, Germany

Martin Fiebich, Institut für Medizinische Physik und Strahlenschutz, Technische Hochschule Mittelhessen, Giessen, Germany.

Zeng Zu Jin, Peking Union Medical College, Beijing, P. R. China.

J. Webster Stayman, Johns Hopkins University, Baltimore, United States.

Hiroyuki Yoshida, Massachusetts General Hospital, Harvard University.

Open Positions

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!

Top 5 Publications (Google Scholar)

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.

Grant support