@inproceedings{b8cd185794954bd6bdbdd94d4f350f89,
title = "Inferring vascular structures in coronary artery X-ray angiograms based on multi-feature fuzzy recognition algorithm",
abstract = "The multi-feature fuzzy recognition (MFFR) algorithm was presented to infer the vessel structures, in the context of X-Ray Angiograms (XRA) of the coronary artery. In the modeling, a multi-feature metrics (MFM) was firstly established to describe the local configuration; then the membership degree of MFM-based fuzzy subsets was defined, and the fuzzy recognition operator was constructed. The MFFR algorithm can correctly infer four kinds of vessel structures including vascular ends, segments, bifurcations and crossovers. The results are satisfying: on average 91.1% of the testing vessel lengths in medium quality images are automatically delineated as well as their structures being correctly inferred with point-wise.",
keywords = "Coronary artery X-ray angiograms, Multi-feature fuzzy recognition, Vessel structure inference",
author = "Shoujun Zhou and Wufan Chen and Jiangui Zhang and Yongtian Wang",
year = "2006",
doi = "10.1007/11812715_41",
language = "English",
isbn = "3540372202",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "325--332",
booktitle = "Medical Imaging and Augmented Reality - Third International Workshop",
address = "Germany",
note = "3rd International Workshop on Medical Imaging and Augmented Reality ; Conference date: 17-08-2006 Through 18-08-2006",
}