Analyzing the Structures of Coronary Artery Trees in Angiogram Images Based on Fuzzy Recognition Algorithm

Abstract

The qualitative and quantitative description of coronary artery depends largely on inferring the artery tree structure in the angiograms.In this paper,an algorithm of Multi-feature based fuzzy recognition is proposed to infer vessel structure in the angiograms.In the implementation,the initial vessel features are attained by preprocessing the original image,and then a circle-detector is used to scan and calculate multi-feature metrics along the vessel path.After defining the membership degree of the multi-feature metrics,a fuzzy operator is constructed to infer the vessel structures,i.e.,the distal ends,segments,bifurcations and crossovers of the artery tree.The algorithms perform well in a simulated phantom,and the ratios of structure identification reach on average to 92.60% in the clinical angiograms.