b超自动后壁厚度测量

Pavan Annangi, N. Subramanian, S. Govind, G. Swamy, B. Young
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引用次数: 3

摘要

在本文中,我们提出了一种鲁棒算法来分割后壁区域,并从胸骨旁长轴(PLAX)视图心脏b型图像估计壁厚。采用后壁厚度(PWd)、室间隔壁厚度(SWTd)和左心室内径(LVId)检测和测量左心室肥厚(LVH)的程度。由于心内膜边界较弱,与斑点交织,对比度较差,脊索、乳头肌和二尖瓣后小叶等纤维结构的运动,人工测量PWd存在较大的观察者间和观察者内变动性。提出的算法试图通过自动化测量算法来解决其中的一些问题。该算法首先通过心包检测检测心外膜边界,然后通过一维活动轮廓进化分割心内膜边界。我们已经在42张图像的试点数据集上设计了算法,并在88个患者数据集上进行了验证。测量值与专家测量值吻合良好,误差为2.06mm±1.5mm。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automated posteriorwall thickness measurement from B-mode ultrasound
In this paper, we present a robust algorithm to segment the posterior wall region and estimate wall thickness from parasternal long axis(PLAX) view cardiac US B-mode images. Posterior wall thickness (PWd), Septal wall thickness (SWTd) and Left ventricular Internal diameter(LVId) are used to detect and measure the extent of Left Ventricular Hypertrophy (LVH). Manual measurements of PWd suffers from large inter and intra observer variability due to weak endocardial boundary intertangled with speckle and poor contrast, movement of the fibrous structures like the chordae,papillary muscles and posterior mitral leaflet. The proposed algorithm seeks to address some of these issues by automating the measurement algorithm. The algorithm initially detects epicardial boundary by pericardium detection and later segments the endocardial boundary by a 1D active contour evolution. We have designed the algorithm on a pilot data set of 42 images and validated on 88 patient data sets.The measurement values are in excellent agreement with expert measurements with error = 2.06mm ± 1.5mm.
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