Extraction of Coronary Vessels in Fluoroscopic X-Ray Sequences Using Vessel Correspondence Optimization
Seung Yeon Shin
Kyoung Jin Noh
Il Dong Yun
Kyoung Mu Lee
AbstractWe 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.
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