3D analysis of facial morphology
3D analysis of facial morphology
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DOI：
10.1002/ajmg.a.20665
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发表时间：
2004-05-01
影响因子：
2
通讯作者：
Winter, RM
中科院分区：
文献类型：
--
作者：
Hammond, P;Hutton, TJ;Winter, RM
通过建立每个3D人脸图像上的数千个点的对应关系，密集表面模型可以用于分析3D人脸形态。这些模型提供了3D脸型变化的戏剧性可视化，有可能培训医生识别特定症状的关键组成部分。我们展示了它们用于可视化和识别3D人脸图像集合中的形状差异，其中包括280名对照组(2周至56岁)、90名Noonan综合征(NS)患者(7个月至56岁)和60名VCFs患者(3至17岁)。使用五种模式识别算法(最近均值、C5.0决策树、神经网络、Logistic回归和支持向量机)对未见的测试样本进行了三组之间的10倍交叉验证判别测试。在区分NS患者和对照组时，儿童的最佳平均灵敏度和特异度分别为92%和93%，成人的平均灵敏度和特异度分别为83%和94%，儿童和成人的联合灵敏度和特异度分别为88%和94%。对于VCFS患者和对照组，最好的结果分别为83%和92%。在NS患者和VCFS患者的比较中，两种综合征的正确识别率都达到了95%。本文包含补充材料，可在《美国医学遗传学杂志》网站http：hwww-interScience上查看。Wiley.com/jpages/01148-7299/suppmat/index.html.(C)2004年Wiley-Liss公司
Dense surface models can be used to analyze 3D facial morphology by establishing a correspondence of thousands of points across each 3D face image. The models provide dramatic visualizations of 3D face-shape variation with potential for training physicians to recognize the key components of particular syndromes. We demonstrate their use to visualize and recognize shape differences in a collection of 3D face images that includes 280 controls (2 weeks to 56 years of age), 90 individuals with Noonan syndrome (NS) (7 months to 56 years), and 60 individuals with velo-cardio-facial syndrome (VCFS; 3 to 17 years of age). Ten-fold cross-validation testing of discrimination between the three groups was carried out on unseen test examples using five pattern recognition algorithms (nearest mean, C5.0 decision trees, neural networks, logistic regression, and support vector machines). For discriminating between individuals with NS and controls, the best average sensitivity and specificity levels were 92 and 93% for children, 83 and 94% for adults, and 88 and 94% for the children and adults combined. For individuals with VCFS and controls, the best results were 83 and 92%. In a comparison of individuals with NS and individuals with VCFS, a correct identification rate of 95% was achieved for both syndromes. This article contains supplementary material, which may be viewed at the American Journal of Medical Genetics website at http:Hwww-interscience. wiley.com/jpages/01148-7299/suppmat/index.html. (C) 2004 Wiley-Liss, Inc.