견고한 3차원 하악골 통계 형상 모델 생성

Building a Robust 3D Statistical Shape Model of the Mandible

  • 유지현 (서울여자대학교 미디어학부) ;
  • 홍헬렌 (서울여자대학교 미디어학부)
  • 발행 : 2008.02.15

초록

본 논문에서는 하악골 데이타에서 견고한 통계 형상 모델을 생성하기 위한 방법을 제안한다. 본 제안 방법은 다음과 같은 네 단계로 구성된다. 첫째, 3차원 입력 형상에 대해 패치 분할을 수행한다. 둘째, 부동 형상에 대한 대응 형상 생성을 위하여 훈련 집합의 모든 형상들을 패치의 형태와 비슷한 도형인 원에 매개화 과정을 수행한다. 셋째, 기준 형상과 각 부동 형상 간 일대일 매핑을 통해 대응 형상을 생성한다. 이때, 패치 경계 부분에서 대응 정점 생성이 불가능한 문제를 해결한다. 마지막으로 대응 형상들을 기준 형상으로 정렬하고, 주성분 분석 기법을 사용하여 통계 형상 모델을 생성한다. 제안 방법을 적용하여 생성한 3차원 하악골 통계 형상 모델의 정확성을 평가하기 위해 육안 평가와 부동 형상과 대응 형상 간 평균 거리 차이를 이용한 유사성 측정을 수행한다. 또한 형상 변화를 표현하는 모드를 이용하여 통계 형상 모델의 밀집도를 측정한다. 실험 결과 다양한 특성을 갖는 하악골 데이타로 생성된 3차원 통계 형상 모델은 부동 형상과 대응 형상 간 높은 유사성을 가지며 적은 수의 모드로 통계 형상 모델 표현됨을 보여 준다.

In this paper, we propose a method for construction of robust 3D statistical shape model in the mandible CT datasets. Our method consists of following four steps. First, we decompose a 3D input shape Into patches. Second, to generate a corresponding shape of a floating shape, all shapes in the training set are parameterized onto a disk similar to the patch topology. Third, we generate the corresponding shape by one-to-one mapping between the reference and the floating shapes. We solve the problem failed to generate the corresponding points near the patch boundary Finally, the corresponding shapes are aligned with the reference shape. Then statistical shape model is generated by principle component analysis. To evaluate the accuracy of our 3D statistical shape model of the mandible, we perform visual inspection and similarity measure using average distance difference between the floating and the corresponding shapes. In addition, we measure the compactness of statistical shape model using the modes of variation. Experimental results show that our 3D statistical shape model generated by the mandible CT datasets with various characteristics has a high similarity between the floating and corresponding shapes and is represented by the small number of modes.

키워드

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