초록

본 논문에서는 MR 영상에서 밝기값 분포와 기울기 정보를 이용한 전립선 자동 분할 기법을 제안한다. 첫째, 적응적 밝기값 프로파일과 다해상도 기법을 이용하는 활성형상모델을 통해 전립선 표면을 추출한다. 둘째, 표면 형상의 지역적 최적화로 인한 흘을 방지하기 위하여 기하학 정보를 이용한 흘 제거 기법을 수행한다. 셋째, 해부학적으로 변이가 큰 표면 형상은 2차원 기울기 정보를 이용하여 보정한다. 이때, 보정된 표면 형상은 한정된 정점의 개수로 산정되어 매끄럽게 표현되지 않기 때문에 표면재구성 및 평활화 기법을 이용하여 부드러운 형상으로 표현한다. 제안방법의 평가를 위하여 육안평가와 정확성 평가 그리고 수행시간을 측정하였다. 정확성 평가는 두 명의 임상전문의의 수동분할 결과와 자동분할 결과 간의 평균거리차이와 중복볼륨비율을 측정하였다. 실험 결과 평균거리차이는 0.3${\pm}$0.21mm 측정되었고, 중복볼륨 비율은 96.31${\pm}$2.71% 측정되었다. 20명의 환자 데이터에 대한 전체 수행시간은 평균 16초로 측정되었다.

Abstract

In this paper, we propose an automatic segmentation of the prostate using intensity distribution and gradient information in MR images. First, active shape model using adaptive intensity profile and multi-resolution technique is used to extract the prostate surface. Second, hole elimination using geometric information is performed to prevent the hole from occurring by converging the surface shape to the local optima. Third, the surface shape with large anatomical variation is corrected by using 2D gradient information. In this case, the corrected surface shape is often represented as rugged shape which is generated by the limited number of vertices. Thus, it is reconstructed by using surface modelling and smoothing. To evaluate our method, we performed the visual inspection, accuracy measures and processing time. For accuracy evaluation, the average distance difference and the overlapping volume ratio between automatic segmentation and manual segmentation by two radiologists are calculated. Experimental results show that the average distance difference was 0.3${\pm}$0.21mm and the overlapping volume ratio was 96.31${\pm}$2.71%. The total processing time of twenty patient data was 16 seconds on average.

주제어

#자동분할   #활성형상모델   #형상 정보   #기하학 정보   #전립선   #자기공명영상  

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