Browse > Article

Measurement and Algorithm Calculation of Maxillary Positioning Change by Use of an Optoelectronic Tracking System Marker in Orthognathic Surgery  

Park, Jong-Woong (Department of Dentistry, School of Dentistry, Seoul National University)
Kim, Soung-Min (Department of Dentistry, School of Dentistry, Seoul National University)
Eo, Mi-Young (Department of Oral and Maxillofacial Surgery, School of Dentistry, Seoul National University)
Park, Jung-Min (Department of Dental Research Institute, Seoul National University)
Myoung, Hoon (Department of Dentistry, School of Dentistry, Seoul National University)
Lee, Jong-Ho (Department of Dentistry, School of Dentistry, Seoul National University)
Kim, Myung-Jin (Department of Dentistry, School of Dentistry, Seoul National University)
Publication Information
Maxillofacial Plastic and Reconstructive Surgery / v.33, no.3, 2011 , pp. 233-240 More about this Journal
Abstract
Purpose: To apply a computer assisted navigation system to orthognathic surgery, a simple and efficient measuring algorithm calculation based on affine transformation was designed. A method of improving accuracy and reducing errors in orthognathic surgery by use of an optical tracking camera was studied. Methods: A total of 5 points on one surgical splint were measured and tracked by the Polaris $Vicra^{(R)}$ (Northern Digital Inc Co., Ontario, Canada) optical tracking system in two cases. The first case was to apply the transformation matrix at pre- and postoperative situations, and the second case was to apply an affine transformation only after the postoperative situation. In each situation, the predictive measuring value was changed to the final measuring value via an affine transformation algorithm and the expected coordinates calculated from the model were compared with those of the patient in the operation room. Results: The mean measuring error was $1.027{\pm}0.587$ using the affine transformation at pre- and postoperative situations and the average value after the postoperative situation was $0.928{\pm}0.549$. The farther a coordinate region was from the reference coordinates which constitutes the transform matrixes, the bigger the measuring error was found which was calculated from an affine transformation algorithm. Conclusion: Most difference errors were brought from mainly measuring process and lack of reproducibility, the affine transformation algorithm formula from postoperative measuring values by using of optic tracking system between those of model surgery and those of patient surgery can be selected as minimizing the difference error. To reduce coordinate calculation errors, minimum transformation matrices must be used and reference points which determine an affine transformation must be close to the area where coordinates are measured and calculated, as well as the reference points need to be scattered.
Keywords
Affine transformation; Coordinate measurement; Navigation surgery; Orthognathic surgery; Point maker;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Schwestka-Polly R, Roese D, Kuhnt D, Hille KH. Application of the model-positioning appliance for three-dimensional positioning of the maxilla in cast surgery. Int J Adult Orthodon Orthognath Surg 1993;8:25-31.
2 Santler G. 3-D COSMOS: a new 3-D model based computerised operation simulation and navigation system. J Craniomaxillofac Surg 2000;28:287-93.   DOI   ScienceOn
3 Schmelzeisen R, Schramm A. Computer-assisted reconstruction of the facial skeleton. Arch Facial Plast Surg 2003;5:437.   DOI
4 Schramm A, Gellrich NC, Schmelzeisen R. Registration process. In: Navigational surgery of the facial skeleton. Navigation; Springer: 2007. p.1-24.
5 Goldberg JL, editor. Matrix Theory with Applicaions. McGraw-Hill; 1992.
6 Wagner A, Rasse M, Millesi W, Ewers R. Virtual reality for orthognathic surgery: the augmented reality environment concept. J Oral Maxillofac Surg 1997;55:456-62; discussion 462-3.   DOI   ScienceOn
7 Schramm A, Gellrich NC, Gutwald R, et al. Indications for computer-assisted treatment of cranio-maxillofacial tumors. Comput Aided Surg 2000;5:343-52.   DOI   ScienceOn
8 Watzinger F, Wanschitz F, Rasse M, et al. Computer-aided surgery in distraction osteogenesis of the maxilla and mandible. Int J Oral Maxillofac Surg 1999;28:171-5.
9 Lee IH, editor. Linear algebra. JayuAcademy; 1996.
10 Metaxas D, Venkataraman S, Vogler C. Image-based stress recognition using a model-based dynamic face tracking system. In: Computational Science - ICCS 2004; 2004. p. 813-21.