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A non-supervised approach to locate and to measure the nuchal translucency by means of wavelet analysis and neural networks

机译:通过小波分析和神经网络来定位和测量颈部半透明性的非监督方法

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摘要

Ultrasound imaging is a well known noninvasive way to evaluate various diseases during the prenatal age. In particular, the thickness measure of the nuchal transucency is strictly correlated with pathologies like trisomy 13, 18 and 21. For a correct investigation, the methodology needs mid-sagittal sections and the proposed approach is based on wavelet analysis and neural network classifiers to locate components useful to identify mid-sagittal planes. To evaluate the performance and the robustness of the methodology, real clinical ultrasound images were considered, obtaining an average error of at most 0.3 millimeters in 97.4% of the cases.
机译:超声成像是一种众所周知的评估产前各种疾病的非侵入性方法。尤其是,颈部透明性的厚度测量值与三体性13、18和21等病理学密切相关。为了进行正确的研究,该方法需要矢状矢状切面,并且所提出的方法基于小波分析和神经网络分类器进行定位有助于识别矢状中平面的组件。为了评估该方法的性能和鲁棒性,考虑了真实的临床超声图像,在97.4%的病例中获得的平均误差最大为0.3毫米。

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