Journal of KIISE:Computer Systems and Theory (한국정보과학회논문지:시스템및이론)

Korean Institute of Information Scientists and Engineers (한국정보과학회)
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Multi-modality MEdical Image Registration based on Moment Information and Surface Distance

모멘트 정보와 표면거리 기반 다중 모달리티 의료영상 정합

  • 최유주 (이화여자대학교 컴퓨터학과) ;
  • 김민정 (이화여자대학교 컴퓨터학) ;
  • 박지영 (이화여자대학교 컴퓨터학) ;
  • 윤현주 (이화여자대학교 컴퓨터그래픽스연구센) ;
  • 정명진 (삼성전자 소프트웨어센) ;
  • 홍승봉 (성균관대학교 의과대학, 삼성서울병원 신경) ;
  • 김명희 (이화여자대학교 컴퓨터학과)
  • Published : 2004.04.01
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Abstract

Multi-modality image registration is a widely used image processing technique to obtain composite information from two different kinds of image sources. This study proposes an image registration method based on moment information and surface distance, which improves the previous surface-based registration method. The proposed method ensures stable registration results with low registration error without being subject to the initial position and direction of the object. In the preprocessing step, the surface points of the object are extracted, and then moment information is computed based on the surface points. Moment information is matched prior to fine registration based on the surface distance, in order to ensure stable registration results even when the initial positions and directions of the objects are very different. Moreover, surface comer sampling algorithm has been used in extracting representative surface points of the image to overcome the limits of the existed random sampling or systematic sampling methods. The proposed method has been applied to brain MRI(Magnetic Resonance Imaging) and PET(Positron Emission Tomography), and its accuracy and stability were verified through registration error ratio and visual inspection of the 2D/3D registration result images.

다중 모달리티 영상정합은 서로 다른 성격의 두 영상의 중요정보를 결합하여 복합적 정보를 얻기 위해 널리 사용되는 영상처리 기법이다. 본 연구에서는 정합 대상 객체의 초기위치 및 방향에 종속적이지 않고, 낮은 정합오차 범위 내에서의 안정적인 정합을 지원하기 위하여 기존의 표면기반 정합 기법을 개선한 모멘트 정보 및 표면거리 기반의 정합 기법을 제시한다. 제안방법에서는 우선 정합대상객체의 표면 윤곽 점을 추출하고, 이를 기반으로 대상객체의 모멘트 정보를 추출하여, 표면거리 기반 상세 정합 이전에 모멘트 정보를 일치시키는 변환을 수행함으로써, 정합이전 대상객체의 위치 및 방향이 상이한 경우에 있어서도 정합이 안정적으로 수행되도록 한다. 또한 테스트 영상에 대한 표면 대표점 추출 시, 표면 코너추출법을 적용함으로써, 기존 표면 정보 기반 정합기법에서 일반적으로 사용하고 있는 무작위 샘플링 및 일정간격 샘플링에 의한 취약점을 보완한다. 본 논문에서 제안기법의 검증을 위하여 뇌 부위 자기공명단층영상(MRI)과 양자 방출 단층 촬영 영상(PET)을 적용하고, 정합오류율과 정합결과에 대한 2,3차원 가시화 영상의 육안평가를 통하여 정확성 및 안정성 측면을 검증한다.

Keywords

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