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A novel gaussian distribution and tukey weight (gdatw) algorithms: deformation accuracy for augmented reality (ar) in facelift surgery

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Abstract

In facelift surgeries, tracking the exact position of the patient’s facial nerves, blood vessels and other tissues can help the surgeons make the right decisions during surgery. Using Augmented Reality technologies that display the mapping of soft tissues beneath the skin, surgeons will be able to detect and locate the regions of cutting correctly prior to making the first cut. The study of Augmented Reality-assisted surgeries has not been found in facelift surgeries involving facial soft tissues, thus this journal can provide with invaluable first steps into the more concentrated studies involving this area. The current available systems in the oral and maxillofacial areas has shown limitation in supporting the elastic nature of facial soft tissues, which shape shifts and changes due to patient’s movement, or movement caused by surgeon during surgery. This paper aims to increase overlay accuracy by reducing elastic deformation error for Augmented Reality in facelift surgeries. The proposed system consists of a Gaussian Distribution and Tukey Weight (GDaTW) algorithm to reduce the deformation error after the geometric error algorithm had been performed. The test results confirm that the new algorithm improves the video accuracy by ~0.10 mm by reducing the overlay error caused by elastic deformation with the display framerate of 5–10 frames per second compared to 10–13 frames per second in existing system. The improvement proposed in this system increases the overlay accuracy by reducing elastic deformation error. The correct display of soft tissues in the mandibular region using Augmented Reality aims to aid plastic surgeons perform facelift surgeries with confidence, to avoid making the wrong cuts of vital areas occluded by the patient’s skin.

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Acknowledgements

This study was supported in part by Study Support Manager Angelika Maag and CSU student Shelsa Ng et al. [14], from the Charles Sturt University Study Centre, Sydney, Australia.

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Authors and Affiliations

  1. School of Computing and Mathematics, Charles Sturt University (CSU), Sydney, Australia

    Abeer Alsadoon, Yahini Murugesan & P. W. C. Prasad

  2. School of Computer Data and Mathematical Sciences, University of Western Sydney (UWS), Sydney, Australia

    Abeer Alsadoon

  3. School of Information Technology, Southern Cross University (SCU), Sydney, Australia

    Abeer Alsadoon

  4. Asia Pacific International College (APIC), Information Technology Department, Sydney, Australia

    Abeer Alsadoon

  5. Department of Oral and Maxillofacial Services, Greater Western Sydney Area Health Services, Sydney, Australia

    Sami Haddad

  6. Department of Oral and Maxillofacial Services, Central Coast Area Health, Gosford, Australia

    Sami Haddad

  7. Faculty of Medicine and Health Sciences, Macquarie University, Sydney, Australia

    Anand Deva

Authors
  1. Abeer Alsadoon
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  2. Yahini Murugesan
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  3. P. W. C. Prasad
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  4. Sami Haddad
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  5. Anand Deva
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Correspondence to Abeer Alsadoon.

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Appendix 1

Appendix 1

Table 5 Abbreviations for the terms used in this paper
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Alsadoon, A., Murugesan, Y., Prasad, P.W.C. et al. A novel gaussian distribution and tukey weight (gdatw) algorithms: deformation accuracy for augmented reality (ar) in facelift surgery. Multimed Tools Appl 80, 15719–15743 (2021). https://doi.org/10.1007/s11042-021-10590-z

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  • DOI: https://doi.org/10.1007/s11042-021-10590-z

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