Journal of the Institute of Electronics and Information Engineers (전자공학회논문지)

The Institute of Electronics and Information Engineers (대한전자공학회)
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Pulmonary Vessels Segmentation and Refinement On the Chest CT Images

흉부 CT 영상에서 폐 혈관 분할 및 정제

  • Kim, Jung-Chul (Department of Electronics Convergence Engineering, Wonkwang University) ;
  • Cho, Joon-Ho (Department of Electronics Convergence Engineering, Wonkwang University) ;
  • Hwang, Hyung-Soo (Department of Electronics Convergence Engineering, Wonkwang University)
  • 김정철 (원광대학교 전자융합공학과) ;
  • 조준호 (원광대학교 전자융합공학과) ;
  • 황형수 (원광대학교 전자융합공학과)
  • Received : 2013.06.19
  • Published : 2013.11.25
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Abstract

In this paper, we proposed a new method for pulmonary vessels image segmentation and refinement from pulmonary image. Proposed method consist of following five steps. First, threshold estimation is performed by polynomial regression analysis of histogram variation rate of the pulmonary image. Second, segmentation of pulmonary vessels object is performed by density-based segmentation method based on estimated threshold in first step. Third, 2D connected component labeling method is applied to segmented pulmonary vessels. The seed point of both side diaphragms is determined by eccentricity and size of component. Fourth step is diaphragm extraction by 3D region growing method at the determined seed point. Finally, noise cancelation of pulmonary vessels image is performed by 3D connected component labeling method. The experimental result is showed accurately pulmonary vessels image segmentation, the diaphragm extraction and the noise cancelation of the pulmonary vessels image.

본 논문에서는 폐 영상에서 폐 혈관을 분할하고 정제하는 방법을 제안하였다. 제안된 방법은 다음과 같이 다섯 단계로 구성된다. 첫 번째, 폐 영상에서 히스토그램 변화율의 다항식 회귀 분석을 사용하여 임계값을 계산한다. 두 번째, 계산된 임계값으로 밝기값 기반 분할 방법을 사용하여 폐 혈관을 분할한다. 세 번째, 분할한 폐 혈관 영상에 2차원 연결 요소 레이블링 방법을 사용하고, 레이블링 요소의 크기와 이심률을 계산하여 좌측 및 우측 횡격막의 씨앗점을 결정한다. 네 번째, 결정된 씨앗점에서 3차원 영역 성장법을 사용하여 횡격막을 추출한다. 다섯 번째, 이진 영상의 3차원 연결 요소 레이블링 방법을 사용하여 폐 혈관 영상의 노이즈를 제거한다.

Keywords

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