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22q11.2缺失综合征(22q11.2DS)受累个体局部鼻部特征的自动分析。

Automatic analysis of local nasal features in 22q11.2DS affected individuals.

作者信息

Wu Jia, Wilamowska Katarzyna, Shapiro Linda, Heike Carrie

机构信息

Department of Computer Science and Engineering, University of Washington, Seattle, WA 98195, USA.

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:3597-600. doi: 10.1109/IEMBS.2009.5333755.

Abstract

The 22q11.2 deletion syndrome is a common genetic condition with an estimated prevalence between 1:2000 and 1:6000 live births in the US. The syndrome is manifested in multiple different craniofacial features. The nasal area is known to play a role in assessing the extent of dysmorphology of an individual patient. In this paper, we present a method for detecting and assessing the severity of a common nasal feature: the bulbous nasal tip. Our method locates the nose and computes four descriptors, each of which leads to a severity score. Experiments with the four severity scores and a combinations of the best two show that using all five scores gives the best prediction of bulbous nasal tip. Furthermore, the bulbous nasal tip measures outperformed the median of human experts and attains similar results to our own prior work on global descriptors [12] for prediction of 22q11.2DS.

摘要

22q11.2缺失综合征是一种常见的遗传疾病,在美国活产婴儿中的估计患病率为1/2000至1/6000。该综合征表现为多种不同的颅面特征。已知鼻部区域在评估个体患者的畸形程度方面发挥作用。在本文中,我们提出了一种检测和评估一种常见鼻部特征——球根状鼻尖严重程度的方法。我们的方法定位鼻子并计算四个描述符,每个描述符都会得出一个严重程度分数。对这四个严重程度分数以及最佳两个分数的组合进行的实验表明,使用所有五个分数可以对球根状鼻尖进行最佳预测。此外,球根状鼻尖测量结果优于人类专家的中位数,并且在预测22q11.2缺失综合征方面获得了与我们之前关于全局描述符的工作[12]相似的结果。

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