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首页> 外文期刊>Medical and Biological Engineering and Computing: Journal of the International Federation for Medical and Biological Engineering >Detection of the intima and media layer thickness of ultrasound common carotid artery image using efficient active contour segmentation technique.
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Detection of the intima and media layer thickness of ultrasound common carotid artery image using efficient active contour segmentation technique.

机译:使用有效的主动轮廓分割技术检测超声颈总动脉内膜和中层厚度。

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摘要

An active contour segmentation technique for extracting the intima-media layer of the common carotid artery (CCA) ultrasound images employing semiautomatic region of interest identification and speckle reduction techniques is presented in this paper. An attempt has been made to test the ultrasound images of the carotid artery of different subjects with this contour segmentation based on improved dynamic programming method. It is found that the preprocessing of ultrasound images of the CCA with region identification and despeckleing followed by active contour segmentation algorithm can be successfully used in evaluating the intima-media thickness (IMT) of the normal and abnormal subjects. It is also estimated that the segmentation used in this paper results an intermethod error of 0.09 mm and a coefficient of variation of 18.9%, for the despeckled images. The magnitudes of the IMT values have been used to explore the rate of prediction of blockage existing in the cerebrovascular and cardiovascular pathologies and also hypertension and atherosclerosis.
机译:本文提出了一种主动轮廓分割技术,该方法利用半自动关注区域识别和斑点减少技术来提取颈总动脉内膜中层。已经尝试基于改进的动态编程方法利用这种轮廓分割来测试不同对象的颈动脉的超声图像。研究发现,采用区域识别和去斑点的CCA超声图像预处理,然后采用主动轮廓分割算法,可以成功地用于评估正常和异常受试者的内膜中膜厚度(IMT)。还估计,对于去斑点图像,本文中使用的分割导致方法间误差为0.09 mm,变异系数为18.9%。 IMT值的大小已用于探索脑血管和心血管病理以及高血压和动脉粥样硬化中存在的阻塞预测率。

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