Skip to main content

Virtual Cranio-Maxillofacial Surgery Planning with Stereo Graphics and Haptics

  • Chapter
Computer-Assisted Musculoskeletal Surgery

Abstract

Cranio-maxillofacial surgery to restore normal skeletal anatomy in patients with serious facial conditions is both complex and time consuming. There is, however, ample evidence that careful pre-operative planning leads to a better outcome with a higher degree of function and reduced morbidity and at the same time reduced time in the operating room. We are building a cranio-maxillofacial surgery planning system that, based on patient specific three-dimensional CT data, allows the surgeon to plan the surgical procedure without the help of a technician. Using a combination of stereo visualization with six degrees-of-freedom, high-fidelity haptic feedback, the system allows the surgeon to test alternative surgical solutions, move bone fragments, and design patient-specific implants and plates. Our goal is a system where the surgeon, after minimal training, can plan a complex procedure in less than an hour. Preliminary tests indicate that this goal is achievable.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 159.00
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    https://www.brainlab.com/, accessed July 1, 2014.</Emphasis>

  2. 2.

    http://biomedical.materialise.com/mimics, accessed July 1, 2014.</Emphasis>

  3. 3.

    http://geomagic.com/, accessed July 1, 2014.</Emphasis>

  4. 4.

    http://www.sensegraphics.com/, accessed July 1, 2014.</Emphasis>

  5. 5.

    https://www.naturalpoint.com/, accessed July 1, 2014.</Emphasis>

  6. 6.

    http://www.ultimaker.com/, accessed July 1, 2014.</Emphasis>

References

  1. Boyle P, Levin B, editors. World cancer report 2008. Lyon: IARC Press; 2008.

    Google Scholar 

  2. Murray CJL, Lopez AD. Alternative projections of mortality and disability by cause 1990–2020: global burden of disease study. Lancet. 1997;349(9064):1498–504.

    Article  CAS  PubMed  Google Scholar 

  3. Peden M, et al. World report on road traffic injury prevention. Geneva: World Health Organization; 2004.

    Google Scholar 

  4. Ridgway EB, Weiner HL. Skull deformities. Pediatr Clin North Am. 2004;51(2):359–87.

    Article  PubMed  Google Scholar 

  5. Roser SM, et al. The accuracy of virtual surgical planning in free fibula mandibular reconstruction: comparison of planned and final results. J Oral Maxillofac Surg. 2010;68(11):2824–32.

    Article  PubMed  Google Scholar 

  6. Antony AK, et al. Use of virtual surgery and stereolithography-guided osteotomy for mandibular reconstruction with the free fibula. Plast Reconstr Surg. 2011;128(5):1080–4.

    Article  CAS  PubMed  Google Scholar 

  7. Schvartzman S, et al. A computer-aided trauma simulation system with haptic feedback is easy and fast for oral-maxillofacial surgeons to learn and use. J Oral Maxillofac Surg. 2014;72(10):1984–93.

    Article  PubMed  Google Scholar 

  8. Held RT, Hui TT. A guide to stereoscopic 3D displays in medicine. Acad Radiol. 2011;18(8):1035–48.

    Article  PubMed  Google Scholar 

  9. Zachow S, et al. 3D osteotomy planning in cranio-maxillofacial surgery: experiences and results of surgery planning and volumetric finite-element soft tissue prediction in three clinical cases. In Computer Assisted Radiology and Surgery (CARS). Springer; 2002. p. 983–7.

    Google Scholar 

  10. McIntire JP, Havig PR, Geiselman EE. Stereoscopic 3D displays and human performance: a comprehensive review. Displays. 2014;35(1):18–26.

    Article  Google Scholar 

  11. van Schooten BW, et al. The effect of stereoscopy and motion cues on 3D interpretation task performance. In Proceedings of the International Conference on Advanced Visual Interfaces. ACM; 2010. p. 167–70.

    Google Scholar 

  12. Ware C, Mitchell P. Visualizing graphs in three dimensions. ACM Trans Appl Percept (TAP). 2008;5(1):2.

    Google Scholar 

  13. Olsson P, Nysjö F, Seipel S, Carlbom IB. Physically co-located haptic interaction with 3D displays. In Haptics Symposium (HAPTICS). IEEE; 2012. p. 267–72.

    Google Scholar 

  14. Coles TR, Meglan D, John N. The role of haptics in medical training simulators: a survey of the state of the art. IEEE Trans Haptic. 2011;4(1):51–66.

    Article  Google Scholar 

  15. Grady L. Random walks for image segmentation. IEEE Trans Pattern Anal Mach Intell. 2006;28(11):1768–83.

    Article  PubMed  Google Scholar 

  16. Liu L, et al. Interactive separation of segmented bones in CT volumes using graph cut. In Medical Image Computing and Computer-Assisted Intervention, MICCAI, LNCS 5241. Springer; 2008. p. 296–304.

    Google Scholar 

  17. Kruger J, Westermann R. Acceleration techniques for GPU-based volume rendering. In Proceedings of the IEEE Visualization (VIS’03); 2003. p. 38.

    Google Scholar 

  18. Bell WN, Olson LN, Schroder J. PyAMG: algebraic multigrid solvers in Python; 2008. Version 1.1.

    Google Scholar 

  19. Olsson P, Nysjö F, Hirsch J-M, Carlbom IB. A haptics-assisted cranio-maxillofacial surgery planning system for restoring skeletal anatomy in complex trauma cases. Int J Comput Assist Radiol Surg. 2013;8(6):887–94.

    Article  PubMed Central  PubMed  Google Scholar 

  20. Olsson P, Nysjö F, Hirsch J-M, Carlbom IB. Snap-to-fit, a haptic 6 DOF alignment tool for virtual assembly. In World Haptics Conference. IEEE; 2013. p. 205–10.

    Google Scholar 

  21. Nyström I, Nysjö J, Malmberg F. Visualization and haptics for interactive medical image analysis: image segmentation in cranio-maxillofacial surgery planning. In Proceedings of International Visual Informatics Conference, LNCS 7066. Springer; 2011. p. 1–12.

    Google Scholar 

  22. Canny J. A computational approach to edge detection. IEEE Trans Pattern Anal Mach Intell. 1986;8(6):679–98.

    Article  CAS  PubMed  Google Scholar 

  23. Tomasi C, Manduchi R. Bilateral filtering for gray and color images. In Proceedings of the Sixth International Conference on Computer Vision (ICCV 1998). IEEE Computer Society; 1998. p. 839–46.

    Google Scholar 

  24. Nysjö F, Olsson P, Hirsch J-M, Carlbom IB. Custom mandibular implant design with deformable models and haptics. In Proceedings of Computer Assisted Radiology and Surgery (CARS), 20th Computed Maxillofacial Imaging Congress; 2014. p. 246.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ingela Nyström PhD, Docent .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Nyström, I. et al. (2016). Virtual Cranio-Maxillofacial Surgery Planning with Stereo Graphics and Haptics. In: Ritacco, L., Milano, F., Chao, E. (eds) Computer-Assisted Musculoskeletal Surgery. Springer, Cham. https://doi.org/10.1007/978-3-319-12943-3_4

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-12943-3_4

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-12942-6

  • Online ISBN: 978-3-319-12943-3

  • eBook Packages: MedicineMedicine (R0)

Publish with us

Policies and ethics