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저대조 혈관 조영상에서 좌심실 기능의 정량화를 위한 지식 기반의 경계선 자동검출
전춘기,권용무 대한의용생체공학회 1996 의공학회지 Vol.17 No.1
Cardiac function is evaluated quantitatively using angiographic images via the analysis of the shape change or the heart wall boundaries. To kin with, boundary defection or ESLV(End Systolic Lert Ventricular) and EDLV(End Diastolic Left Ventricular) is essential for the quantitative analysis of cardiac function. The boundary detection methods proposed in the past were almost semi-automatic. Intervention by a knowledgeable human operator was still required Of con, manual tracing of the boundaries is currently used for subsequent analysis and diagnosis. This method would not cut excessive time, labor, and subjectivity associated with manual intervention by a human operator. EDLV images have noncontiguous and ambiguous edge signal on some boundary regions. In this paper, we propose a new method for automated detection of boundaries in noncontiguous and ambiguous EDLV images. The boundary detection scheme which based on a priori knowledge information is divided into two steps. The first step is to detect the candidate edge points of EDLV using ESLV boundaries. The second step is to correct detected boundaries of EDLV using the LV shape. We developed the algorithm of modifying EDLV boundaries defined adaptive modifier. We experimented the method proposed in this paper and compared our proposed method with the manual method in detecting boundaries of EDLV. In the areas within estimated boundaries of EDLV, the percentage of error was about 1.4%. We verified the useflilness and obtained the satisfying results througll the experiments of the proposed method.
전춘기,강광남,이태원,Jeon, Chun-Gi,Gang, Gwang-Nam,Lee, Tae-Won 대한의용생체공학회 1995 의공학회지 Vol.16 No.3
지금까지는 혈관의 중심선을 구해서 혈관의 직경을 측정해 왔다. 혈관의 중심선을 구하는 방법은 2가지가 보고되어 있는데 그중 하나는 maunal로 중심선을 찾는 observer-defined 방법이다. 이 방법을 사용자에 따라 변화할 가능성이 잠재한다, 또 다른 방법은 자동으로 혈관의 중심을 찾아내는 것인데 대단히 복잡하다. 이 논문에서, 중심선을 찾지 않고 방향코드와 위치정보를 이용하여 직경을 구하는 새로운 방법을 제안한다. 이 방법은 경계선과 방향코드를 동시에 검출하기 때문에 절차가 간단해지고 처리속도도 빨라진다. 중앙선을 이용하여 자동으로 혈관직경을 구하는 방법과 비교해보면, 가지가 있거나 장애가 있는 혈관 이미지에 있어서 정확도가 개선된다. 또한 방향 코드는 3비트로 코드화되기 때문에 혈관정보를 압축 저장하는데 용이하다. 이 방법은 실험을 통하여 유용성이 있음을 확인하였다. The conventionally used method requires centerline of vessels to estimate the vessel diameter. Two methods of estimating the centerline of vessels are reported : One is manually observer-defined method. This potentially contributes to inter-and intra-observer variability. And the other is to auto- matically detect the centerline of vessels. But this is very complicated method. In this paper, we propose a new method of estimating vessel diameter using direction codes and position informs:ion without detecting centerline. Since this method detects the vessel boundary and direction code at d same time, it simplifies the procedure and reduces execution time in estimating the vessel diameter. Compared to a method that automatically estimates the vessel diAmeter uslng centerline, our method provides improved accuracy in image with poor contrast, branching or obstructed vessels. Also, this provides a good compression of boundary description, because each direction code element can be coded with 3 bits only, instead of the 4 bytes required for the storage of the coordinates of each border pixel. Our experiments demonstrate the usefulness of the technique using direction code for quantitative analysis of coronary angiography Experimental results Justify the validity of the proposed method.