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http://dx.doi.org/10.9718/JBER.2015.36.4.79

An Automatic Algorithm for Vessel Segmentation in X-Ray Angiogram using Random Forest  

Jung, Sunghee (Brain Korea 21 Project for Medical Science, Yonsei University)
Lee, Soochahn (Department of Electronic Engineering, Soonchunhyang University)
Shim, Hackjoon (Cardiovascular Research Institute, Yonsei University College of Medicine)
Jung, Ho Yub (Division of Computer & Electronic Systems Engineering, Hankuk University of Foreign Studies)
Heo, Yong Seok (Department of Electrical and Computer Engineering, Ajou University)
Chang, Hyuk-Jae (Division of Cardiology, Department of Internal Medicine, Yonsei University College of Medicine)
Publication Information
Journal of Biomedical Engineering Research / v.36, no.4, 2015 , pp. 79-85 More about this Journal
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. and Krissian et al. According to the experimental results, the proposed algorithm showed high similarity compared to other two methods.
Keywords
Vessel segmentation; X-Ray angiogram; Random Forest;
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