Sonka M, Winniford M D, Zhang X, Collins S M
Department of Electrical and Computer Engineering, University of Iowa, Iowa City 52242.
IEEE Trans Biomed Eng. 1994 Jun;41(6):520-8. doi: 10.1109/10.293239.
We have developed a method for lumen centerline detection in individual coronary segments that is based on simultaneous detection of the approximate positions of the left and right coronary borders. This approach emulates that of a clinician who visually identifies the lumen centerline as the midline between the simultaneously-determined left and right borders of the vessel segment of interest. Our lumen centerline detection algorithm and two conventional centerline detection methods were compared to carefully-defined observer-identified centerlines in 89 complex coronary images. Computer-detected and observer-defined centerlines were objectively compared using five indices of centerline position and orientation. The quality of centerlines obtained with the new simultaneous border identification approach and the two conventional centerline detection methods was also subjectively assessed by an experienced cardiologist who was unaware of the analysis method. Our centerline detection method yielded accurate centerlines in the 89 complex images. Moreover, our method outperformed the two conventional methods as judged by all five objective parameters (p < 0.001 for each parameter) and by the subjective assessment of centerline quality (p < 0.001). Automated detection of lumen centerlines based on simultaneous detection of both coronary borders provides improved accuracy in complex coronary arteriograms.
我们已经开发出一种用于检测单个冠状动脉节段管腔中心线的方法，该方法基于同时检测左、右冠状动脉边界的大致位置。这种方法模仿了临床医生的做法，临床医生通过视觉将管腔中心线确定为感兴趣血管节段同时确定的左、右边界之间的中线。我们将管腔中心线检测算法与两种传统中心线检测方法，与89幅复杂冠状动脉图像中经过仔细定义的观察者确定的中心线进行了比较。使用中心线位置和方向的五个指标对计算机检测到的中心线和观察者定义的中心线进行了客观比较。一位不了解分析方法的经验丰富的心脏病专家还对通过新的同时边界识别方法和两种传统中心线检测方法获得的中心线质量进行了主观评估。我们的中心线检测方法在89幅复杂图像中产生了准确的中心线。此外，根据所有五个客观参数（每个参数p < 0.001）以及中心线质量的主观评估（p < 0.001）判断，我们的方法优于两种传统方法。基于同时检测冠状动脉边界的管腔中心线自动检测在复杂冠状动脉造影中提高了准确性。
