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.
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Zhou, S., Chen, W., Zhang, J., Wang, Y. (2006). Inferring Vascular Structures in Coronary Artery X-Ray Angiograms Based on Multi-Feature Fuzzy Recognition Algorithm. In: Yang, GZ., Jiang, T., Shen, D., Gu, L., Yang, J. (eds) Medical Imaging and Augmented Reality. MIAR 2006. Lecture Notes in Computer Science, vol 4091. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11812715_41
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DOI: https://doi.org/10.1007/11812715_41
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