Extraction of Coronary Vessels in Fluoroscopic X-Ray Sequences Using Vessel Correspondence Optimization

Authors

Seung Yeon Shin
Soochahn Lee
Kyoung Jin Noh
Il Dong Yun
Kyoung Mu Lee

Abstract

We present a method to extract coronary vessels from fluoroscopic x-ray sequences. Given the vessel structure for the source frame, vessel correspondence candidates in the subsequent frame are generated by a novel hierarchical search scheme to overcome the aperture problem. Optimal correspondences are determined within a Markov random field optimization framework. Post-processing is performed to extract vessel branches newly visible due to the inflow of contrast agent. Quantitative and qualitative evaluation conducted on a dataset of 18 sequences demonstrate the effectiveness of the proposed method.

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Seung Yeon Shin, Soochahn Lee, Kyoung Jin Noh, Il Dong Yun, and Kyoung Mu Lee, "Extraction of Coronary Vessels in Fluoroscopic X-Ray Sequences Using Vessel Correspondence Optimization," Proc. MICCAI:International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2016. Bibtex

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