대한전자공학회논문지SP (Journal of the Institute of Electronics Engineers of Korea SP)

대한전자공학회 (The Institute of Electronics and Information Engineers)
권호 표지

지식기반 다중 템플릿을 이용한 치과용 디지털 X-ray 영상에서의 미세변화 검출에 관한 연구

Bone Loss Detection in Dental Radiography by Domain Knowledge Based Multi-template

  • 안용학 (세종대학교 컴퓨터공학과) ;
  • 채옥삼 (경희대학교 컴퓨터공학과)
  • 투고 : 2009.06.10
  • 발행 : 2010.05.25
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초록

본 논문에서는 치과용 의료시스템(Dental PACS)에서 필요한 시계열 분석(Subtraction Radiography) 방법에 기반 하여 기존의 연구에서 갖지 못했던 영상정렬의 자동화 방안과 미세변화 검출 방안을 제안한다. 제안된 방법은 기존의 단일 템플릿 방식의 문제점을 해결하기 위해 인공치아 및 자연치아의 기하학적 형태 정보를 이용하여 각 치아에 대한 관심영역을 획득하고 획득된 관심영역을 기준으로 지식 기반(knowlege-based)의 다중 템플릿(multi-template) 방식의 정합을 통해 치아 주위에서 발생되는 미세변화를 빠르고 정확하게 검출할 수 있다. 실험결과 제안된 방법은 신속하고 정확하게 치아 주위의 미세변화에 대한 검출이 가능하였고, 보다 객관적이고 정량적인 결과를 제시할 수 있음을 보여주었다.

This study proposes the algorithm to automate image alignment and detect marginal bone destructions, based on subtraction radiography for dental radiographic images necessary for dental PACS, which hasn't been covered by related literatures. The proposed algorithm enables a quick and precise detection of marginal bone destructions around teeth including implant through the knowlege-based multi-template matching in reference to ROI(Region Of Interest) obtained from applicable teeth using information about their geometric forms to solve problems single-template matching is exposed to. Actually, the test showed that it was possible not only to quickly and precisely detect marginal bone destructions around teeth, but also to get more objective and quantitative results through the algorithm.

키워드

참고문헌

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