首页> 外文会议>International Workshop on Medical Imaging and Augmented Reality; 20060817-18; Shanghai(CN) >Inferring Vascular Structures in Coronary Artery X-Ray Angiograms Based on Multi-Feature Fuzzy Recognition Algorithm
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Inferring Vascular Structures in Coronary Artery X-Ray Angiograms Based on Multi-Feature Fuzzy Recognition Algorithm

机译:基于多特征模糊识别算法的冠状动脉X线血管造影血管结构推断

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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.
机译:提出了多特征模糊识别(MFFR)算法,以在冠状动脉的X射线血管造影照片(XRA)下推断血管结构。在建模中,首先建立了一个多特征量度(MFM)来描述本地配置。然后定义了基于MFM的模糊子集的隶属度,并构造了模糊识别算子。 MFFR算法可以正确推断出四种血管结构,包括血管末端,节段,分叉和交叉。结果令人满意:自动画出中等质量图像中平均91.1%的测试容器长度,并正确地逐点推断其结构。

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