Pico Lantern: A Pick-up Projector for Augmented Reality in Laparoscopic Surgery

  • Philip Edgcumbe
  • Philip Pratt
  • Guang-Zhong Yang
  • Chris Nguan
  • Rob Rohling
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8673)


The Pico Lantern is proposed as a new tool for guidance in laparoscopic surgery. Its miniaturized design allows it to be picked up by a laparoscopic tool during surgery and tracked directly by the endoscope. By using laser projection, different patterns and annotations can be projected onto the tissue surface. The first explored application is surface reconstruction. The absolute error for surface reconstruction using stereo endoscopy and untracked Pico Lantern for a plane, cylinder and ex vivo kidney is 2.0 mm, 3.0 mm and 5.6 mm respectively. The absolute error using a mono endoscope and a tracked Pico Lantern for the same plane, cylinder and kidney is 0.8mm, 0.3mm and 1.5mm respectively. The results show the benefit of the wider baseline produced by tracking the Pico Lantern. Pulsatile motion of a human carotid artery is also detected in vivo. Future work will be done on the integration into standard and robot-assisted laparoscopic surgery.


pico projector laparoscopic surgery augmented reality 


  1. 1.
    Fuchs, H., et al.: Augmented Reality Visualization for Laparoscopic Surgery. In: Wells, W.M., Colchester, A.C.F., Delp, S.L. (eds.) MICCAI 1998. LNCS, vol. 1496, pp. 934–943. Springer, Heidelberg (1998)CrossRefGoogle Scholar
  2. 2.
    Pratt, P., Stoyanov, D., Visentini-Scarzanella, M., Yang, G.-Z.: Dynamic Guidance for Robotic Surgery Using Image-Constrained Biomechanical Models. In: Jiang, T., Navab, N., Pluim, J.P.W., Viergever, M.A. (eds.) MICCAI 2010, Part I. LNCS, vol. 6361, pp. 77–85. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  3. 3.
    Benincasa, A.B., Clements, L.W., Duke Herrell, S., Galloway, R.L.: Feasibility study for image-guided kidney surgery: Assessment of required intraoperative surface for accurate physical to image space registrations. Med. Phys. 35(9), 4251–4261 (2008)CrossRefGoogle Scholar
  4. 4.
    Hansen, C., Wieferich, J., Ritter, F., Rieder, C., Peitgen, H.-O.: Illustrative Visualization of 3D Planning Models for Augmented Reality in Liver Surgery. IJCARS 5, 133–141 (2010)Google Scholar
  5. 5.
    Maier-Hein, L., Mountney, P., Bartoli, A., Elhawary, H., Elson, D., Groch, A., Kolb, A., Rodrigues, M., Sorger, J., Speidel, S., Stoyanov, D.: Optical Techniques for 3D Surface Reconstruction in Computer-Assisted Laparoscopic Surgery. Med. Img. 17, 974–996 (2013)CrossRefGoogle Scholar
  6. 6.
    Clancy, N.T., Stoyanov, D., Maier-Hein, L., Groch, A., Yang, G.-Z., Elson, D.S.: Spectrally Encoded Fiber-Based Structured Lighting Probe for Intraoperative 3D Imaging. Biomedical Optics Express 2(11), 3119–3128 (2011)CrossRefGoogle Scholar
  7. 7.
    Schneider, C., Guerrero, J., Nguan, C., Rohling, R., Salcudean, S.: Intra-operative “Pick-Up” Ultrasound for Robot Assisted Surgery with Vessel Extraction and Registration: A Feasibility Study. In: Taylor, R.H., Yang, G.-Z. (eds.) IPCAI 2011. LNCS, vol. 6689, pp. 122–132. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  8. 8.
    Lincoln, J.: March of the Pico Projectors. IEEE Spectrum 47, 40–45 (2010)CrossRefGoogle Scholar
  9. 9.
    Park, H., Lee, M.-H., Kim, S.-J., Park, J.-I.: Surface-Independent Direct-Projected Augmented Reality. In: Narayanan, P.J., Nayar, S.K., Shum, H.-Y. (eds.) ACCV 2006. LNCS, vol. 3852, pp. 892–901. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  10. 10.
    Tardif, J.P., Roy, S., Meunier, J.: IEEE: Projector-based augmented reality in surgery without calibration. In: IEEE EMBS, pp. 548–551. IEEE Press, New York (2003)Google Scholar
  11. 11.
    Edgcumbe, P., Nguan, C., Rohling, R.: Calibration and Stereo Tracking of a Laparoscopic Ultrasound Transducer for Augmented Reality in Surgery. In: Liao, H., Linte, C.A., Masamune, K., Peters, T.M., Zheng, G. (eds.) MIAR 2013 and AE-CAI 2013. LNCS, vol. 8090, pp. 258–267. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  12. 12.
    Geng, J.: Structured-Light 3D Surface Imaging: a Tutorial. Advances in Optics and Photonics 3, 128–160 (2011)CrossRefGoogle Scholar
  13. 13.
    Bouguet, J.-Y.: Visual Methods for Three-dimensional Modeling, Phd Thesis (1999)Google Scholar
  14. 14.
    Falcao, G., Hurtos, N., Massich, J., Fofi, D.: Projector-Camera Calibration Toolbox. Erasumus Mundus Masters in Vision and Robotics (2009)Google Scholar
  15. 15.
    Zhang, Z.: A Flexible New Technique for Camera Calibration. IEEE T PAMI 22, 1330–1334 (2000)CrossRefGoogle Scholar
  16. 16.
    Pratt, P., Di Marco, A., Payne, C., Darzi, A., Yang, G.-Z.: Intraoperative ultrasound guidance for transanal endoscopic microsurgery. In: Ayache, N., Delingette, H., Golland, P., Mori, K. (eds.) MICCAI 2012, Part I. LNCS, vol. 7510, pp. 463–470. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  17. 17.
    Hughes-Hallett, A., Pratt, P., Mayer, E., Di Marco, A., Yang, G.-Z., Vale, J., Darzi, A.: Intraoperative Ultrasound Overlay in Robot-assisted Partial Nephrectomy: First Clinical Experience. Eur. Urol. 65(3), 671–672 (2014)CrossRefGoogle Scholar
  18. 18.
    Röhl, S., Bodenstedt, S., Suwelack, S., Dillmann, R., Speidel, S., Kenngott, H., Müller- Stich, B.P.: Dense GPU-Enhanced Surface Reconstruction From Stereo Endoscopic Images for Intraoperative Registration. Med. Phys. 39, 1632–1645 (2012)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Philip Edgcumbe
    • 1
  • Philip Pratt
    • 2
  • Guang-Zhong Yang
    • 2
  • Chris Nguan
    • 3
  • Rob Rohling
    • 1
    • 4
  1. 1.Department of Electrical and Computer EngineeringUniversity of British ColumbiaVancouverCanada
  2. 2.Hamlyn Centre for Robotic SurgeryImperial College of Science, Technology and MedicineLondonUK
  3. 3.Department of Urologic SciencesUniversity of British ColumbiaVancouverCanada
  4. 4.Mechanical EngineeringUniversity of British ColumbiaVancouverCanada

Personalised recommendations