Journal of Biomedical Engineering Research (대한의용생체공학회:의공학회지)

The Korean Society of Medical and Biological Engineering (대한의용생체공학회)
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Automatic Registration of Images for Digital Subtraction Radiography Using Local Correlation

국소적 상관계수를 이용한 자동적 디지털 방사선 영상정합

  • 이원진 (서울대학교치과대학구강악안면방사선학교실, 치학연구소 및 BK21) ;
  • 허민석 (서울대학교치과대학구강악안면방사선학교실, 치학연구소 및 BK2) ;
  • 이삼선 (서울대학교치과대학구강악안면방사선학교실, 치학연구소 및 BK2) ;
  • 최순철 (서울대학교치과대학구강악안면방사선학교실, 치학연구소 및 BK2) ;
  • 이재성 (서울대학교 의학연구원 방사선의학연구소)
  • Published : 2004.04.01
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Abstract

Most of digital subtraction methods in dental radiography are based on registration using manual landmarks. We have developed an automatic registration method without using the manual selection of landmarks. By restricting a geometrical matching of images to a region of interest (ROl), we compare the cross-correlation coefficient only between the ROIs. The affine or perspective transform parameters satisfying maximum of cross-correlation between the local regions are searched iteratively by a fast searching strategy. The parameters are searched on the 1/4 scale image coarsely and then, the fine registration is performed on the original scale image. The developed method can match the images corrupted by Gaussian noise with the same accuracy for the images without any transform simulation. The registration accuracy of the perspective method shows a 17% improvement over the manual method. The application of the developed method to radiography of dental implants provides an automatic noise robust registration with high accuracy in almost real time.

현재 치과 방사선 영상에 적용되고 있는 대부분의 영상공제술은 기준점을 이용한 정한에 근거하고 있다. 본 연구에서는 수작업에 의한 기준점 설정 방법을 이용하지 않고 자동적으로 정참을 수행하는 방법을 개발하였다. 두 영상의 기하학적 매칭을 국소적 관심영역(ROI)에 한정시켜서 이 관심영역 간의 상관계수를 비교한다. 두 영역의 상관계수가 최대화되는 affine 또는 perspective 변환 파라미터를 고속의 탐색전략을 이용하여 반복적으로 찾는다. 우선 1/4 스케일 영상에 대하여 근사적인 파라미터를 탐색한 후 다시 원래 영상에 대하여 미세한 매칭이 이루어진다. 개발된 방법은 Gaussian 잡음에 의해 손상된 모의영상을 모의변환을 하지 않은 영상과 동일한 정도의 정확도를 가지고 정합 할 수 있다. 개발된 방법의 perspective 변환을 이용한 정합의 정확도는 수작업에 의한 것보다 17%향상된 결과를 보였다. 결론적으로, 이 방법의 치과 임플란트 영상에의 적용은 거의 실시간으로 자동적이고 잡음에 강인한 정합을 제공한다.

Keywords

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