Skip to main content
Log in

Robotic laser osteotomy through penscriptive structured light visual servoing

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

Abstract

Purpose

Planning osteotomies is a task that surgeons do as part of standard surgical workflow. This task, however, becomes more difficult and less intuitive when a robot is tasked with performing the osteotomy. In this study, we aim to provide a new method for surgeons to allow for highly intuitive trajectory planning, similar to the way an attending surgeon would instruct a junior.

Methods

Planning an osteotomy, especially during a craniotomy, is performed intraoperatively using a sterile surgical pen or pencil directly on the exposed bone surface. This paper presents a new method for generating osteotomy trajectories for a multi-DOF robotic manipulator using the same method and relaying the penscribed cut path to the manipulator as a three-dimensional trajectory. The penscribed cut path is acquired using structured light imaging, and detection, segmentation, optimization and orientation generation of the Cartesian trajectory are done autonomously after minimal user input.

Results

A 7-DOF manipulator (KUKA IIWA) is able to follow fully penscribed trajectories with sub-millimeter accuracy in the target plane and perpendicular to it (0.46 mm and 0.36 mm absolute mean error, respectively).

Conclusions

The robot is able to precisely follow cut paths drawn by the surgeon directly onto the exposed boney surface of the skull. We demonstrate through this study that current surgical workflow does not have to be drastically modified to introduce robotic technology in the operating room. We show that it is possible to guide a robot to perform an osteotomy in much the same way a senior surgeon would show a trainee by using a simple surgical pen or pencil.

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

Similar content being viewed by others

References

  1. Giraud JY, Villemin S, Darmana R, Cahuzac JP, Autefage A, Morucci JP (1991) Bone cutting. Clin Phys Physiol Meas 12(1):1

    Article  CAS  PubMed  Google Scholar 

  2. AOT AG. Advanced osteotomy tools. https://aot.swiss/en/

  3. Vadera S, Chan A, Low T, Gill A, Morenkova A, Phiellip NM, Hermanowicz N, Hsu FP (2017) Frameless stereotactic robot-assisted subthalamic nucleus deep brain stimulation: case report. World Neurosurg 97:762-e11

    Article  Google Scholar 

  4. Giger A, Jud C, Cattin P (2017) Respiratory motion compensation for the robot-guided laser osteotome. Int J Comput Assist Radiol Surg 12(10):1751–1762

    Article  PubMed  Google Scholar 

  5. Burgner J (2010) Robot assisted laser osteotomy. KIT Scientific Publishing, Karlsruhe

    Google Scholar 

  6. Baek KW, Deibel W, Martinov D, Griessen M, Bruno A, Zeilhofer HF, Cattin P, Juergens P (2015) Clinical applicability of robot-guided contact-free laser osteotomy in cranio-maxillo-facial surgery: in-vitro simulation and in-vivo surgery in minipig mandibles. J Oral Maxillofac Surg 53(10):976–981

    Article  Google Scholar 

  7. Deibel W, Schneider A, Augello M, Bruno AE, Juergens P, Cattin P (2015) A compact, efficient and light weight laser head for CARLO®: integration, performance and benefits. In: Novel optical systems design and optimization XVIII, vol 9579, International Society for Optics and Photonics

  8. Mönnich H, Stein D, Raczkowsky J, Wörn H (2010) Results of CO2 robotic laser oseotomy in surgery with motion compensation. In: Photonic therapeutics and diagnostics VI, vol 7548, International Society for Optics and Photonics

  9. Xu D, andLinkun Wang ZJ, Tan M (2004) Features extraction for structured light image of welding seam with arc and splash disturbance. In: 8th International conference on control, automation, robotics and vision, Kunming, China, pp 1559–1563

  10. Xu D, Wang L, Tan M (2004) Image processing and visual control method for arc welding robot. In: International conference on robotics and biomimetics, Shenyang, pp 727–732

  11. Xu D, Tan M, Li Y (2006) Visual control system for robotic welding. In: Industrial robotics theory modelling control, Pro Literatur Verlag, Austria

  12. Xu D, Tan M, Zhao X, Tu Z (2004) Seam tracking and visual control for robotic arc welding based on structured light stereovision. Int J Autom Comput 1:63–75

    Article  CAS  Google Scholar 

  13. Yu Z, He Y, Xu Y, Chen H (2018) Vision-based deviation extraction for three-dimensional control in robotic welding with steel sheet. Int J Adv Manuf Technol 95(9–12):4449–4458

    Article  Google Scholar 

  14. Ye Z, Fang G, Chen S, Zou JJ (2012) Passive vision based seam tracking system for pulse-MAG welding. Int J Adv Manuf Technol 67:1987–1996

    Article  Google Scholar 

  15. Xu Y, Fang G, Chen S, Zou JJ, Ye Z (2014) Real-time image processing for vision-based weld seam tracking in robotic GMAW. Int J Adv Manuf Technol 73(9):1413–1425

    Article  Google Scholar 

  16. Guha D, Gupta S, Fehlings MG, Yang V (2017) Optical topographic imaging for spinal intraoperative three-dimensional navigation in minimally invasive approaches: initial preclinical experience. Spine J 17(10):S254

    Article  Google Scholar 

  17. Sciavicco L, Siciliano B (2000) Modelling and control of robot manipulators, 2nd edn. Springer, Berlin

    Book  Google Scholar 

  18. Boomgaard RVD, Balen RV (1992) Computer vision, methods for fast morphological image transforms using bitmapped images. Gr Image Process Gr Models Image Process 54(3):254–258

    Google Scholar 

  19. Sobel I, Feldman G (1968) A \(3\times 3\) isotropic gradient operator for image processing. In: A talk at the Stanford artificial project, pp 271–272

  20. Zill D, Cullen M (2006) Advanced engineering mathematics, 3rd edn. Jones & Bartlett Learning, Burlington

    Google Scholar 

  21. Jolliffe I (2002) Principal component analysis, series: Springer series in statistics, 2nd edn. Springer, New York

    Google Scholar 

  22. Wiles A, Thompson D, Frantz D (2004) Accuracy assessment and interpretation for optical tracking systems. In: Proceedings of SPIE medical imaging 2004: visualization, image-guided procedures and display (SPIE), vol 5367, pp 421–432

  23. Elfring R, de la Fuente M, Radermarcher K (2010) Assessment of optical localizer accuracy for computer aided surgery systems. Comput Aided Surg 15(1–3):1–12

    Article  PubMed  Google Scholar 

  24. Dillon NP (2014) Preliminary testing of a compact bone-attached robot for otologic surgery. In: Medical imaging 2014: image-guided procedures, robotic interventions, and modeling, vol 9036, International Society for Optics and Photonics

  25. Dillion NP, Balachandran R, Fitzpatrick JM, Siebold MA, Labadie RF, Wanna GB, Withrow TJ, Webster RJ (2015) A compact, bone-attached robot for mastoidectomy. J Med Devices 9(3):031003

    Article  Google Scholar 

  26. Gerber N, Bell B, Gavaghan K, Weisstanner C, Caversaccio M, Weber S (2014) Surgical planning tool for robotically assisted hearing aid implantation. Int J Comput Assist Radiol Surg 9(1):11–20

    Article  PubMed  Google Scholar 

  27. Zagzoog N, Yang VX (2018) State of robotic mastoidectomy: literature review. World Neurosurg 116:347–351

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

Thank you to Jillian Cardinell for the graphics help.

Funding

Funding for this research was provided by The Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant: “Optical Coherence Tomography, Optical Topographical Imaging and Fluorescence Guided Surgical Laser Ablation”—Grant Number RGPIN/6263-2014.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jamil Jivraj.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Humans and animal rights

This article does not contain and studies with human or animal participants performed by any of the authors. All ex-vivo animal parts were obtained in accordance with the research ethics guidelines of Ryerson University. All patient data were anonymized in accordance with Sunnybrook Health Sciences Centre policy. Informed consent was obtained from all individual participants included in the study.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jivraj, J., Deorajh, R., Lai, P. et al. Robotic laser osteotomy through penscriptive structured light visual servoing. Int J CARS 14, 809–818 (2019). https://doi.org/10.1007/s11548-018-01905-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11548-018-01905-x

Keywords

Navigation