랜덤 포레스트를 이용한 X-선 혈관조영영상에서의 혈관 자동 영역화 알고리즘
An Automatic Algorithm for Vessel Segmentation in X-Ray Angiogram using Random Forest
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초록
The purpose of this study is to develop an automatic algorithm for vessel segmentation in X-Ray angiogram using Random Forest (RF). The proposed algorithm is composed of the following steps: First, the multiscale hessian-based filtering is performed in order to enhance the vessel structure. Second, eigenvalues and eigenvectors of hessian matrix are used to learn the RF classifier as feature vectors. Finally, we can get the result through the trained RF. We evaluated the similarity between the result of proposed algorithm and the manual segmentation using 349 frames, and compared with the results of the following two methods: Frangi et al. [1] and Krissian et al. [2]. According to the experimental results, the proposed algorithm showed high similarity compared to other two methods.
Abstract
The purpose of this study is to develop an automatic algorithm for vessel segmentation in X-Ray angiogram using Random Forest (RF). The proposed algorithm is composed of the following steps: First, the multiscale hessian-based filtering is performed in order to enhance the vessel structure. Second, eigenvalues and eigenvectors of hessian matrix are used to learn the RF classifier as feature vectors. Finally, we can get the result through the trained RF. We evaluated the similarity between the result of proposed algorithm and the manual segmentation using 349 frames, and compared with the results of the following two methods: Frangi et al. [1] and Krissian et al. [2]. According to the experimental results, the proposed algorithm showed high similarity compared to other two methods.
참고문헌 (8)
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- Gupta, V., "A robust and accurate approach to automatic blood vessel detection and segmentation from angiography x-ray images using multistage random forests", SPIE Medical Imaging 2012: Computer-Aided Diagnosis, 8315, pp.83152F~83152F-6 (2012)
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- "Open Source Computer Vision Library"[URL]