Loizou C P, Pattichis C S, Pantziaris M, Tyllis T, Nicolaides A
Intercollege, Department of Computer Science, School of Sciences and Engineering, 92 Ayias Phylaxeos Str, P.O.Box 51604, CY-3507, Limassol, Cyprus.
Med Biol Eng Comput. 2007 Jan;45(1):35-49. doi: 10.1007/s11517-006-0140-3. Epub 2007 Jan 3.
Ultrasound measurements of the human carotid artery walls are conventionally obtained by manually tracing interfaces between tissue layers. In this study we present a snakes segmentation technique for detecting the intima-media layer of the far wall of the common carotid artery (CCA) in longitudinal ultrasound images, by applying snakes, after normalization, speckle reduction, and normalization and speckle reduction. The proposed technique utilizes an improved snake initialization method, and an improved validation of the segmentation method. We have tested and clinically validated the segmentation technique on 100 longitudinal ultrasound images of the carotid artery based on manual measurements by two vascular experts, and a set of different evaluation criteria based on statistical measures and univariate statistical analysis. The results showed that there was no significant difference between all the snakes segmentation measurements and the manual measurements. For the normalized despeckled images, better snakes segmentation results with an intra-observer error of 0.08, a coefficient of variation of 12.5%, best Bland-Altman plot with smaller differences between experts (0.01, 0.09 for Expert1 and Expert 2, respectively), and a Hausdorff distance of 5.2, were obtained. Therefore, the pre-processing of ultrasound images of the carotid artery with normalization and speckle reduction, followed by the snakes segmentation algorithm can be used successfully in the measurement of IMT complementing the manual measurements. The present results are an expansion of data published earlier as an extended abstract in IFMBE Proceedings (Loizou et al. IEEE Int X Mediterr Conf Medicon Med Biol Eng POS-03 499:1-4, 2004).
传统上,对人体颈动脉壁的超声测量是通过手动描绘组织层之间的界面来获取的。在本研究中,我们提出了一种蛇形分割技术,用于在纵向超声图像中检测颈总动脉(CCA)远壁的内膜中层,该技术通过在归一化、散斑减少以及归一化和散斑减少之后应用蛇形算法。所提出的技术利用了一种改进的蛇形初始化方法以及一种改进的分割方法验证。我们基于两位血管专家的手动测量以及基于统计量和单变量统计分析的一组不同评估标准,在100幅颈动脉纵向超声图像上对该分割技术进行了测试和临床验证。结果表明,所有蛇形分割测量结果与手动测量结果之间没有显著差异。对于归一化去斑后的图像,获得了更好的蛇形分割结果,观察者内误差为0.08,变异系数为12.5%,专家之间差异较小的最佳布兰德 - 奥特曼图(专家1和专家2分别为0.01、0.09),以及豪斯多夫距离为5.2。因此,对颈动脉超声图像进行归一化和散斑减少预处理,然后采用蛇形分割算法,可成功用于内膜中层厚度(IMT)的测量,作为手动测量的补充。目前的结果是对早期作为扩展摘要发表在《IFMBE会议录》(Loizou等人,IEEE Int X Mediterr Conf Medicon Med Biol Eng POS - 03 499:1 - 4, 2004)中的数据的扩展。