New approach to the automatic segmentation of coronary artery in X-ray angiograms  

作　　者：ZHOU ShouJun YANG Jun CHEN WuFan WANG YongTian 

机构地区：[1]School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China [2]458 Hospital of PLA, Guangzhou 510000, China [3]Department of Opto-electronic Engineering, Beijing Institute of Technology, Beijing 100081, China

出　　处：《Science in China(Series F)》2008年第1期25-39,共15页中国科学（F辑英文版）

基　　金：Supported by the National Basic Research Program of China (Grant No. 2003CB716101);the National Natural Science Foundation of China (Grant No. 60772120);the Key National Science Foundation of China (Grant No. 30730026)

摘　　要：For the segmentation of X-ray angiograms （XRA）, the essential feature and the prior knowledge of angiographic image were analyzed, and a multi-feature based fuzzy recognition （MFFR） algorithm was proposed to infer the local vessel structure in this paper. Guided by the prior knowledge of artery vessel, a probability tracking operator （PTO） can rapidly track along the artery tree, and walk across the weak region or gaps because of disturbance or preprocessing to angiographic image. Another, the accurate measurement of the vascular axis-lines and diameters can be synchronously implemented in the tracking process. To correctly evaluate the proposed method, a simulated image of CAT and some clinical XRA images were used in the experimentations. The algorithms performed better than the conventional one： given one start-point, on average 92.7% of the visible segments or branches was automatically delineated; the correctness ratio of vessel structure inference reached to 90.0% on the average.For the segmentation of X-ray angiograms （XRA）, the essential feature and the prior knowledge of angiographic image were analyzed, and a multi-feature based fuzzy recognition （MFFR） algorithm was proposed to infer the local vessel structure in this paper. Guided by the prior knowledge of artery vessel, a probability tracking operator （PTO） can rapidly track along the artery tree, and walk across the weak region or gaps because of disturbance or preprocessing to angiographic image. Another, the accurate measurement of the vascular axis-lines and diameters can be synchronously implemented in the tracking process. To correctly evaluate the proposed method, a simulated image of CAT and some clinical XRA images were used in the experimentations. The algorithms performed better than the conventional one： given one start-point, on average 92.7% of the visible segments or branches was automatically delineated; the correctness ratio of vessel structure inference reached to 90.0% on the average.

关 键 词：coronary artery angiogram vessel tracking vessel structure identification probability tracking model 

分 类 号：R3[医药卫生—基础医学]