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

악교정수술에서 광전자 포인트 마커를 이용한 상악골 위치 변화의 계측 및 계산 방법 연구

  • 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)
  • 박종웅 (서울대학교 치의학대학원 치의학과) ;
  • 김성민 (서울대학교 치의학대학원 치의학과) ;
  • 어미영 (서울대학교 치의학대학원 구강악안면외과학교실) ;
  • 박정민 (서울대학교 치의학대학원 치학연구소) ;
  • 명훈 (서울대학교 치의학대학원 치의학과) ;
  • 이종호 (서울대학교 치의학대학원 치의학과) ;
  • 김명진 (서울대학교 치의학대학원 치의학과)
  • Received : 2011.02.20
  • Accepted : 2011.04.14
  • Published : 2011.05.31

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

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