Skip to main content
Log in

A touch panel surgical navigation system with automatic depth perception

  • Original Article
  • Published:
International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose

A touch panel navigation system may be used to enhance endoscopic surgery, especially for cauterization. We developed and tested the in vitro performance of a new touch panel navigation (TPN) system.

Methods

This TPN system uses finger motion trajectories on a touch panel to control an argon plasma coagulation (APC) attached to a robot arm. Thermal papers with printed figures were soaked in saline for repeated recording and analysis of cauterized trajectory. A novice and an expert surgeon traced squares and circles displayed on the touch panel and cauterized them using the APC. Sixteen novices and eight experts cauterized squares and circles using both conventional endoscopic and TPN procedures. Six novices cauterized arcs using the endoscopic and TPN procedures 20 times a day for 5 consecutive days.

Results

For square shapes, the offset was 5.5 mm with differences between the novice and the expert at 2 of 16 points. For circles, the offset was 5.0 mm and did not differ at any point. Task completion time for the TPN procedure was significantly longer than that for the endoscopic procedure for both squares and circles. For squares, the distance from the target for the TPN procedure was significantly smaller than that for the endoscopic procedure. For circles, the distance did not differ. There was no difference in task completion time and distance between the novices and the experts. Task completion time and distance improved significantly for the endoscopic procedure but not for the TPN procedure.

Conclusions

A new TPN system enabled the surgeons to accomplish continuous 3D positioning of the surgical device with automatic depth perception using finger tracing on a 2D monitor. This technology is promising for application in surgical procedures that require precise control of cauterization.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  1. Shimada J, Nishikawa A (2009) Remote control system. U.S. Patent Number 2009/0187288 to be issued

  2. Shimada J, Ito K, Kato D, Shimomura M, Tsunezuka H, Okada S, Ishihara S (2012) Intuitive touch panel navigation system through Kyoto Digital Sosui Network. Comput Aided Surg Proc Info Common Technol 3:92–100. doi:10.1007/978-4-431-54094-6_11

    Article  Google Scholar 

  3. Shimada J, Ito K, Kato D, Shimomura M, Tsunezuka H, Terauchi K, Ichise K, Ishihara S (2012) Intuitive touch panel control system with tablet PC. Int J CARS 7(Suppl 1):S173–174

    Google Scholar 

  4. Schulder M, Liang D, Carmel PW (2001) Cranial surgery navigation aided by a compact intraoperative magnetic resonance imager. J Neurosurg 94:936–945. doi:10.3171/jns.2001.94.6.0936

    Article  CAS  PubMed  Google Scholar 

  5. Krupa A, Gangloff J, Doignon C, de Mathelin M, Morel G, Leroy J, Soler L, Marescaux J (2003) Autonomous 3-D positioning of surgical instruments in robotized laparoscopic surgery using visual servoing. IEEE Trans Robotics Autom 19:842–853. doi:10.1109/TRA.2003.817086

    Article  Google Scholar 

  6. Zaitsev M, Dold C, Sakas G, Hennig J, Speck O (2006) Magnetic resonance imaging of freely moving objects: Prospective real-time motion correction using an external optical motion tracking system. Neuroimage 31:1038–1050. doi:10.1016/j.neuroimage.2006.01.039

    Article  CAS  PubMed  Google Scholar 

  7. Voros S, Long JA, Cinquin P (2007) Automatic detection of instruments in laparoscopic images. Int J Robot Res 26:1173–1190. doi:10.1177/0278364907083395

    Article  Google Scholar 

  8. Shin S, Kim Y, Kwak H, Lee D, Park S (2011) 3D tracking of surgical instruments using a single camera for laparoscopic surgery simulation. Stud Health Technol Inform 163:581–587. doi:10.3233/978-1-60750-706-2-581

    PubMed  Google Scholar 

  9. Loukas C, Lahanas V, Georgiou E (2013) An integrated approach to endoscopic instrument tracking for augmented reality applications in surgical simulation training. Int J Med Robot 9:e34–e51. doi:10.1002/rcs.1485

    Article  PubMed  Google Scholar 

  10. Tonet O, Thoranaghatte RU, Megali G, Dario P (2007) Tracking endoscopic instruments without a localizer: a shape-analysis-based approach. Comput Aided Surg 12:35–42. doi:10.1080/10929080701210782

    Article  PubMed  Google Scholar 

  11. Uemura M, Tomikawa M, Kumashiro R, Miao T, Souzaki R, Ieiri S, Ohuchida K, Lefor AT, Hashizume M (2014) Analysis of hand motion differentiates expert and novice surgeons. J Surg Res 188:8–13. doi:10.1016/j.jss.2013.12.009

    Article  PubMed  Google Scholar 

  12. Yamaguchi S, Yoshida D, Kenmotsu H, Yasunaga T, Konishi K, Ieiri S, Nakashima H, Tanoue K, Hashizume M (2011) Objective assessment of laparoscopic suturing skills using a motion-tracking system. Surg Endosc 25:771–775. doi:10.1007/s00464-010-1251-3

    Article  PubMed  Google Scholar 

  13. Michael D, Diodato M, Sunil M, Prosad M, Mary E, Klingensmith M, Ralph J, Damiano M (2004) Robotics in surgery. Curr Probl Surg 41:752–810. doi:10.1067/j.cpsurg.2004.07.002

    Article  Google Scholar 

  14. Loulmet D, Carpentier A, d’Attellis N, Berrebi A, Cardon M, Ponzio O, Aupècle B, Relland J (1999) Endoscopic coronary artery bypass grafting with the aid of robotic assisted instruments. J Thorac Cardiovasc Surg 118:4–10. doi:10.1016/S0022-5223(99)70133-9

    Article  CAS  PubMed  Google Scholar 

  15. Anthony RL, Castellanos AE, Desai PD, Meyers WC (2004) Robotic surgery: a current perspective. Ann Surg 239:14–21. doi:10.1097/01.sla.0000103020.19595.7d

    Article  Google Scholar 

  16. The da Vinci Surgical System. http://www.intuitivesurgical.com. Accessed May 1, 2014

  17. Chandra V, Nehra D, Parent R, Woo R, Reyes R, Hernandez-Boussard T, Dutta S (2010) A comparison of laparoscopic and robotic assisted suturing performance by experts and novices. Surgery 147:830–839. doi:10.1016/j.surg.2009.11.002

    Article  PubMed  Google Scholar 

  18. Lawton V, Dmitry O, Stephen H, Hani H, Leonid Z (2003) Measurements of the level of surgical expertise using flight path analysis from da Vinci robotic surgical system. Stud Health Technol Inform 94:373–378

    Google Scholar 

Download references

Acknowledgments

This study was financially supported by a Grant-in-Aid for Scientific Research (A) (No. 17209047) and (B) (No. 22390270) from the Japan Society for the Promotion of Science.

Conflict of interest

None.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Junichi Shimada.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Okada, S., Shimada, J., Ito, K. et al. A touch panel surgical navigation system with automatic depth perception. Int J CARS 10, 243–251 (2015). https://doi.org/10.1007/s11548-014-1080-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11548-014-1080-2

Keywords

Navigation