Rapid Prototyping으로 제작한 3D Medical Model의 오차 측정에 관한 연구 (임상 적용 가능성 및 사례)

ACCURACY TESTS OF 3D RAPID PROTOTYPING (RP) MEDICAL MODELS: ITS POTENTIAL AND CLINICAL APPLICATIONS

  • 최진영 (서울대학교 치과대학 구강악안면외과) ;
  • 최정호 (남양주시 보건소) ;
  • 김남국 (서울대학교 산업공학과) ;
  • 이종기 (서울대학교 치과대학 구강병리과) ;
  • 김명기 (서울대학교 치과대학 치과의료관리학 연구실) ;
  • 김명진 (서울대학교 치과대학 구강악안면외과) ;
  • 김영호 (서울대학교 산업공학과)
  • Choi, Jin-Young (Department of OMFS, College of Dentistry, Seoul National university) ;
  • Choi, Jung-Ho (Namyangju Public Health Center) ;
  • Kim, Nam-Kuk (Department of Industrial Engineering, College of Engineering, Seoul National University) ;
  • Lee, Jong-Ki (Department of oral Pathology, College of Dentistry, Seoul National university) ;
  • Kim, Myeng-Ki (Dental Services Management and Policy, College of Dentistry, Seoul National university) ;
  • Kim, Myung-Jin (Department of OMFS, College of Dentistry, Seoul National university) ;
  • Kim, Yeong-Ho (Department of Industrial Engineering, College of Engineering, Seoul National University)
  • 발행 : 1999.12.31

초록

Presented in this paper are the experimental results that measure rapid prototyping (RP) errors in 3D medical models. We identified various factors that can cause dimensional errors when producing RP models, specifically in maxillofacial areas. For the experiment, we used a human dry skull. A number of linear measurements based on landmarks were first obtained on the skull. This was followed by CT scanning, 3D model reconstruction, and RP model fabrication. The landmarks were measured again on both the reconstructed models and the physical RP models, and these were compared with those on dry skull. We focused on major sources of errors, such as CT scanning, conversion from CT data to STL models, and RP model fabrication. The results show that the overall error from skull to RP is $0.64{\times}0.36mm(0.71{\times}0.66%)$ in absolute value. This indicates that the RP technology can be acceptable in the real clinical applications. A clinical case that has applied RP models successfully for treatment planning and surgical rehearsal is presented. Although the use of RP models is rare in the medical area yet, we believe RP is promising in that it has a great potential in developing new tools which can aid diagnosis, treatment planning, surgical rehearsal, education, and so on.

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