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Automated detection of fetal nuchal translucency based on hierarchical structural model

机译:基于层次结构模型的胎儿颈部半透明性自动检测

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The nuchal translucency (NT) thickness is an important parameter in the diagnosis of fetuses. The previous computerized methods often require manual operations to select the NT region, which leads to the time-consuming problem and the detection variability. In the paper, a hierarchical structural model is proposed for the automated detection of the NT region. Three discriminative classifiers are first trained with Gaussian pyramids to represent the NT, head and body of fetuses respectively. Then a spatial model is proposed to denote the spatial constrains among them. Finally the dynamic programming and generalized distance transform are applied for the inference from the proposed model, which ensures the optimal solution can be obtained for the NT detection. The performance of the proposed model is verified by the experimental results of 345 clinical NT ultrasound images.
机译:颈部半透明(NT)厚度是胎儿诊断的重要参数。先前的计算机化方法通常需要手动操作来选择NT区域,这导致了耗时的问题和检测的可变性。在本文中,提出了用于NT区域自动检测的分层结构模型。首先使用高斯金字塔训练三个判别式分类器,分别代表胎儿的NT,头部和身体。然后提出一种空间模型来表示它们之间的空间约束。最后,通过动态规划和广义距离变换对所提出的模型进行推论,以确保能够为NT检测获得最优解。 345个临床NT超声图像的实验结果验证了所提出模型的性能。

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