Motion Tracking in Narrow Spaces: A Structured Light Approach

  • Oline Vinter Olesen
  • Rasmus R. Paulsen
  • Liselotte Højgaard
  • Bjarne Roed
  • Rasmus Larsen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6363)


We present a novel tracking system for patient head motion inside 3D medical scanners. Currently, the system is targeted at the Siemens High Resolution Research Tomograph (HRRT) PET scanner. Partial face surfaces are reconstructed using a miniaturized structured light system. The reconstructed 3D point clouds are matched to a reference surface using a robust iterative closest point algorithm. A main challenge is the narrow geometry requiring a compact structured light system and an oblique angle of observation. The system is validated using a mannequin head mounted on a rotary stage. We compare the system to a standard optical motion tracker based on a rigid tracking tool. Our system achieves an angular RMSE of 0.11° demonstrating its relevance for motion compensated 3D scan image reconstructions as well as its competitiveness against the standard optical system with an RMSE of 0.08°. Finally, we demonstrate qualitative result on real face motion estimation.


Positron Emission Tomography Point Cloud Iterative Close Point Iterative Close Point Algorithm Positron Emission Tomography Brain 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Green, M.V., Seidel, J., Steina, S.D., Tedder, T.E., Kempner, K.M., Kertzman, C.: Head movement in normal subjects during simulated PET brain imaging with and without head restraint. J. Nuclear Medicine 35(9), 1538–1546 (1994)Google Scholar
  2. 2.
    Stegmann, M.B., Larsson, H.B.W.: Motion-compensation of cardiac perfusion MRI using a statistical texture ensemble. In: Magnin, I.E., Montagnat, J., Clarysse, P., Nenonen, J., Katila, T. (eds.) FIMH 2003. LNCS, vol. 2674. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  3. 3.
    Ehrhardt, J., Werner, R., Frenzel, T., Säring, D., Lu, W., Low, D., Handels, H.: Reconstruction of 4D-CT data sets acquired during free breathing for the analysis of respiratory motion. In: Proc. SPIE Medical Imaging, vol. 6144, pp. 614414–1–8 (2006)Google Scholar
  4. 4.
    Olesen, O.V., Sibomana, M., Keller, S.H., Andersen, F., Jensen, J.A., Holm, S., Svarer, C., Højgaard, L.: Spatial resolution of the HRRT PET scanner using 3D-OSEM PSF reconstruction. In: Proc. IEEE Nuclear Science Symposium and Medical Imaging Conference, vol. M13-225, pp. 3789–3790 (2009)Google Scholar
  5. 5.
    Picard, Y., Thompson, C.J.: Motion correction of PET images using multiple acquisition frames. IEEE Trans. on Medical Imaging 16(2), 137–144 (1997)CrossRefGoogle Scholar
  6. 6.
    Woo, S.K., Watabe, H., Choi, Y., Kim, K.M., Park, C.C., Bloomfield, P.M.: Sinogram-based motion correction of PET images using optical motion tracking system and list-mode data acquisition. IEEE Trans. on Nuclear Science 51(3), 782–788 (2004)CrossRefGoogle Scholar
  7. 7.
    Rahmim, A., Dinelle, K., Cheng, J.C., Shilov, M.A., Segars, W.P., Lidstone, S.C., Blinder, S., Rousset, O.G., Vajihollahi, H., Tsui, B., Wong, D.F., Sossi, V.: Accurate event-driven motion compensation in high-resolution PET incorporating scattered and random events. IEEE Trans. on Medical Imaging 27(8), 1018–1033 (2008)CrossRefGoogle Scholar
  8. 8.
    Raghunath, N., Faber, T.L., Suryanarayanan, S., Votaw, J.R.: Motion correction of PET brain images through deconvolution: II. Practical implementation and algorithm optimization. Physics in Medicine and Biology 54(3), 813 (2009)CrossRefGoogle Scholar
  9. 9.
    Lopresti, B.J., Russo, A., Jones, W.F., Fisher, T., Crouch, D.G., Altenburger, D.E.: Implementation and performance of an optical motion tracking system for high resolution brain PET imaging. IEEE Trans. on Nuclear Science 46(6), 2059–2067 (1999)CrossRefGoogle Scholar
  10. 10.
    Herzog, H., Tellman, L., Fulton, R., Pietrzyk, U.: Motion correction in PET brain studies. In: IEEE Proc. The Fourth International Workshop on Multidimensional Systems, pp. 178–181 (2005)Google Scholar
  11. 11.
    Olesen, O.V., Jørgensen, M.R., Paulsen, R.R., Højgaard, L., Roed, B., Larsen, R.: Structured light 3D tracking system for measuring motions in PET brain imaging. In: Proc. SPIE Medical Imaging, vol. 7625, p. 76250X (2010)Google Scholar
  12. 12.
    Besl, P.J., McKay, N.: A method of registration of 3D shapes. IEEE Trans. on Pattern Analysis and Machine Intelligence 14(2), 239–256 (1992)CrossRefGoogle Scholar
  13. 13.
    Rusinkiewicz, S., Levoy, M.: Efficient variants of the ICP algorithm. In: Proc. Int. Conf. 3-D Digital Imaging and Modeling, pp. 145–152 (2001)Google Scholar
  14. 14.
    Paulsen, R., Bærentzen, J., Larsen, R.: Markov Random Field Surface Reconstruction. IEEE Transactions on Visualization and Computer Graphics (2009)Google Scholar
  15. 15.
    Kazhdan, M., Bolitho, M., Hoppe, H.: Poisson Surface Reconstruction. In: Proc. Symposium on Geometry Processing, pp. 61–70 (2006)Google Scholar
  16. 16.
    Huang, P., Hu, Q., Jin, F., Chiang, F.: Color-encoded digital fringe projection technique for high-speed three-dimensional surface contouring. Optical Engineering 38, 1065 (1999)CrossRefGoogle Scholar
  17. 17.
    Herráez, M., Burton, D., Lalor, M., Gdeisat, M.: Fast two-dimensional phase-unwrapping algorithm based on sorting by reliability following a noncontinuous path. Appl. Opt. 41, 7437–7444 (2002)CrossRefGoogle Scholar
  18. 18.
    Horn, B.K.P.: Closed form solution of absolute orientation using unit quaternions. Journal of the Optical Society A 4(4), 629–642 (1987)CrossRefMathSciNetGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Oline Vinter Olesen
    • 1
    • 2
    • 3
  • Rasmus R. Paulsen
    • 1
  • Liselotte Højgaard
    • 2
  • Bjarne Roed
    • 3
  • Rasmus Larsen
    • 1
  1. 1.Informatics and Mathematical ModellingTechnical University of DenmarkLyngbyDenmark
  2. 2.Department of Clinical Physiology, Nuclear Medicine & PET, RigshospitaletCopenhagen University Hospital, University of Copenhagen 
  3. 3.Siemens HealthcareSiemens A/SDenmark

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