대한의용생체공학회:의공학회지 (Journal of Biomedical Engineering Research)

  • 제25권5호
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  • Pages.323-328
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  • 2004
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  • 1229-0807(pISSN)
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  • 2288-9396(eISSN)
대한의용생체공학회 (The Korean Society of Medical and Biological Engineering)
권호 표지

3차원 MR 영상으로부터의 한국인 뇌조직확률지도 개발

Development of Korean Tissue Probability Map from 3D Magnetic Resonance Images

  • Jung Hyun, Kim (Department of Biomedical Engineering, Hanyang University) ;
  • Jong-Min, Lee (Department of Biomedical Engineering, Hanyang University) ;
  • Uicheul, Yoon (Department of Biomedical Engineering, Hanyang University) ;
  • Hyun-Pil, Kim (Department of Biomedical Engineering, Hanyang University) ;
  • Bang Bon, Koo (Department of Biomedical Engineering, Hanyang University) ;
  • In Young, Kim (Department of Biomedical Engineering, Hanyang University) ;
  • Dong Soo, Lee (Department of Nuclear Medicine, Seoul National University College of Medicine) ;
  • Jun Soo, Kwon (Department of Psychiatry, Seoul National University College of Medicine) ;
  • Sun I., Kim (Department of Biomedical Engineering, Hanyang University)
  • 발행 : 2004.10.01
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초록

대뇌조직 구분을 위한 실험적인 정보를 제공하기 위한 뇌조직 확률 지도를 개발하는 경우 개인마다 구조적으로 다양한 형태를 가진 뇌의 특성과 특히 인종간의 두드러진 차이론 반드시 고려해야 한다 본 연구에서는 특정 그룹에 대한 뇌조직 확률 지도를 제작하는데 필요한 절차를 알아보고 나이에 따른 그룹간의 뇌조직 확률 지도의 구조적인 차이를 살펴보고자 한다 피험자 그룹은 100명의 건강한 한국인이며 나이에 따라 두 그룹으로 분류하였다. 뇌 확률 지도의 기준 좌표계를 설정하기 위해 전체 그룹 내의 모든 피험자의 뇌 영상에 대한 평균 영상을 구하고, 각 뇌 영상을 기준 좌표계로 정규화 시킨다. 정규화 과정에서 얻어진 변환 매개 변수를 미리 각 뇌조직(회질, 백질, 뇌척수액)으로 분할된 피험자의 영상에 적용하고 각 그룹 내에서 변환된 뇌 조직 영상을 평균함으로써 뇌 조직 확률 지도를 완성하였다. 나이에 따른 구조적인 차이를 살펴보기 위해 그룹간 확률 값의 차이 영상을 구하였다. 이전 연구결과에서와 마찬가지로 나이가 증가함에 따라 뇌실이 확대되고 회질의 위축이 전체적인 뇌 영역에서 일어났다. 그러므로 우리는 대뇌 조직 분할을 위해 설험적인 정보들을 사용하고자 할 때는 특정 그룹에 대한 뇌 확률 지도를 사용할 것을 제안한다.

The development of group-specific tissue probability maps (TPM) provides a priori knowledge for better result of cerebral tissue classification with regard to the inter-ethnic differences of inter-subject variability. We present sequential procedures of group-specific TPM and evaluate the age effects in the structural differences of TPM. We investigated 100 healthy volunteers with high resolution MRI scalming. The subjects were classified into young (60, 25.92+4.58) and old groups (40, 58.83${\pm}$8.10) according to the age. To avoid any bias from random selected single subject and improve registration robustness, average atlas as target for TPM was constructed from skull-stripped whole data using linear and nonlinear registration of AIR. Each subject was segmented into binary images of gray matter, white matter, and cerebrospinal fluid using fuzzy clustering and normalized into the space of average atlas. The probability images were the means of these binary images, and contained values in the range of zero to one. A TPM of a given tissue is a spatial probability distribution representing a certain subject population. In the spatial distribution of tissue probability according to the threshold of probability, the old group exhibited enlarged ventricles and overall GM atrophy as age-specific changes, compared to the young group. Our results are generally consistent with the few published studies on age differences in the brain morphology. The more similar the morphology of the subject is to the average of the population represented by the TPM, the better the entire classification procedure should work. Therefore, we suggest that group-specific TPM should be used as a priori information for the cerebral tissue classification.

키워드

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