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The purpose of this study is to develop an automatic algorithm for vessel segmentation in X-Ray angio-gram using Random Forest (RF). The proposed algorithm is composed of the following steps: First, the multiscalehessian-based filtering is performed in order to enhance the vessel structure. Second, eigenvalues and eigenvectorsof hessian matrix are used to learn the RF classifier as feature vectors. Finally, we can get the result through thetrained RF. We evaluated the similarity between the result of proposed algorithm and the manual segmentation using349 frames, and compared with the results of the following two methods: Frangi et al. [1] and Krissian et al. [2]. Accord-ing to the experimental results, the proposed algorithm showed high similarity compared to other two methods.Key words: Vessel segmentation, X-Ray angiogram, Random Forest I.  (catheter)   (Percutaneous coronary inter-vention, PCI)    ,     X- (angiogram)  .                 .      (projection)      .      , (stent)        .      X-

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