Journal of the Korea Computer Graphics Society (한국컴퓨터그래픽스학회논문지)

Korea Computer Graphics Society (한국컴퓨터그래픽스학회)
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Automatic Meniscus Segmentation from Knee MR Images using Multi-atlas-based Locally-weighted Voting and Patch-based Edge Feature Classification

무릎 MR 영상에서 다중 아틀라스 기반 지역적 가중 투표 및 패치 기반 윤곽선 특징 분류를 통한 반월상 연골 자동 분할

  • Kim, SoonBeen (Department of Software Convergence, Seoul Women's University) ;
  • Kim, Hyeonjin (Department of Software Convergence, Seoul Women's University) ;
  • Hong, Helen (Department of Software Convergence, Seoul Women's University) ;
  • Wang, Joon Ho (Department of Orthopedic Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine)
  • 김순빈 (서울여자대학교 소프트웨어융합학과) ;
  • 김현진 (서울여자대학교 소프트웨어융합학과) ;
  • 홍헬렌 (서울여자대학교 소프트웨어융합학과) ;
  • 왕준호 (성균관대학교 의과대학 삼성서울병원 정형외과)
  • Received : 2018.08.13
  • Accepted : 2018.08.27
  • Published : 2018.09.01
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Abstract

In this paper, we propose an automatic segmentation method of meniscus in knee MR images by automatic meniscus localization, multi-atlas-based locally-weighted voting, and patch-based edge feature classification. First, after segmenting the bone and knee articular cartilage, the volume of interest of the meniscus is automatically localized. Second, the meniscus is segmented by multi-atlas-based locally-weighted voting taking into account the weights of shape and intensity distribution in the volume of interest of the meniscus. Finally, to remove leakage to the collateral ligaments with similar intensity, meniscus is refined using patch-based edge feature classification considering shape and distance weights. Dice similarity coefficient between proposed method and manual segmentation were 80.13% of medial meniscus and 80.81 % for lateral meniscus, and showed better results of 7.25% for medial meniscus and 1.31% for lateral meniscus compared to the multi-atlas-based locally-weighted voting.

본 논문에서는 무릎 MR 영상에서 반월상 연골의 자동 위치화, 다중 아틀라스 기반 지역적 가중 투표를 통한 반월상 연골 분할 및 패치 기반 윤곽선 특징 분류를 통한 반월상 연골 자동 분할 방법을 제안한다. 첫째, 뼈와 무릎 관절 연골을 분할한 후 이를 이용하여 반월상 연골의 관심볼륨영역을 자동 위치화한다. 둘째, 반월상 연골의 관심볼륨영역에서 형상 및 밝기값 분포 가중치를 고려한 다중 아틀라스 기반 지역적 가중 투표를 통해 반월상 연골을 분할한다. 셋째, 밝기값이 유사한 측부 인대로의 누출을 제거하기 위해 형상 및 거리 가중치를 고려한 패치 기반 윤곽선 특징 분류를 통해 반월상 연골 분함을 개선한다. 제안 방법을 통한 분할 결과와 수동 분할 결과 간 다이스 유사계수는 내측 반월상 연골은 80.13%, 외측 반월상 연골은 80.81%를 보였으며 다중 아틀라스 기반 지역적 가중투표를 통한 분할 방법과 비교하여 내 측 및 외측 반월상 연 골 각각 7.25%, 1.31% 향상되었다.

Keywords

References

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