3D Global Estimation and Augmented Reality Visualization of Intra-operative X-ray Dose

  • Nicolas Loy Rodas
  • Nicolas Padoy
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8673)


The growing use of image-guided minimally-invasive surgical procedures is confronting clinicians and surgical staff with new radiation exposure risks from X-ray imaging devices. The accurate estimation of intra-operative radiation exposure can increase staff awareness of radiation exposure risks and enable the implementation of well-adapted safety measures. The current surgical practice of wearing a single dosimeter at chest level to measure radiation exposure does not provide a sufficiently accurate estimation of radiation absorption throughout the body. In this paper, we propose an approach that combines data from wireless dosimeters with the simulation of radiation propagation in order to provide a global radiation risk map in the area near the X-ray device. We use a multi-camera RGBD system to obtain a 3D point cloud reconstruction of the room. The positions of the table, C-arm and clinician are then used 1) to simulate the propagation of radiation in a real-world setup and 2) to overlay the resulting 3D risk-map onto the scene in an augmented reality manner. By using real-time wireless dosimeters in our system, we can both calibrate the simulation and validate its accuracy at specific locations in real-time. We demonstrate our system in an operating room equipped with a robotised X-ray imaging device and validate the radiation simulation on several X-ray acquisition setups.


Surgical workflow analysis hybrid surgery radiation monitoring augmented reality RGBD cameras 


  1. 1.
    Krim, S., Brodecki, M., Carinou, E., Donadille, L., Jankowski, J., Koukorava, C., Dominiek, J., Nikodemova, D., Ruiz-Lopez, N., Sans-Merce, M., Struelens, L., Vanhavere, F.: Extremity doses of medical staff involved in interventional radiology and cardiology: Correlations and annual doses (hands and legs). Radiation Measurements 46(11), 1223–1227 (2011)CrossRefGoogle Scholar
  2. 2.
    Koukorava, C., Carinou, E., Ferrari, P., Krim, S., Struelens, L.: Study of the parameters affecting operator doses in interventional radiology using monte carlo simulations. Radiation Measurements 46(11), 1216–1222 (2011)CrossRefGoogle Scholar
  3. 3.
    RaySafe: Raysafe i2 active dosimetry system,
  4. 4.
    Ladikos, A., Cagniart, C., Ghotbi, R., Reiser, M., Navab, N.: Estimating radiation exposure in interventional environments. In: Jiang, T., Navab, N., Pluim, J.P.W., Viergever, M.A. (eds.) MICCAI 2010, Part III. LNCS, vol. 6363, pp. 237–244. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  5. 5.
    Bott, O.J., Wagner, M., Duwenkamp, C., Hellrung, N., Dresing, K.: Improving education on C-arm operation and radiation protection with a computer-based training and simulation system. Int. J. Computer Assisted Radiology and Surgery 4(4), 399–407 (2009)CrossRefGoogle Scholar
  6. 6.
    Siemens: Artis zeego robotised x-ray imaging system,
  7. 7.
  8. 8.
    ICRU: Report. Number n 33 in 1956-1964: National Bureau of Standards handbook. International Commission on Radiation Units and Measurements (1980)Google Scholar
  9. 9.

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Nicolas Loy Rodas
    • 1
  • Nicolas Padoy
    • 1
  1. 1.ICubeUniversity of Strasbourg, CNRS, IHUStrasbourgFrance

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