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Human age estimation combining third molar and skeletal development

机译:结合第三磨牙和骨骼发育的人类年龄估算

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摘要

The wide prediction intervals obtained with age estimation methods based on third molar development could be reduced by combining these dental observations with age-related skeletal information. Therefore, on cephalometric radiographs, the most accurate age-estimating skeletal variable and related registration method were searched and added to a regression model, with age as response and third molar stages as explanatory variable. In a pilot set up on a dataset of 496 (283 M; 213 F) cephalometric radiographs, the techniques of Baccetti et al. (2005) (BA), Seedat et al. (2005) (SE), Caldas et al. (2007) and Rai et al. (2008) (RA) were verified. In the main study, data from 460 (208 F, 224 M) individuals in an age range between 3 and 26 years, for which at the same day an orthopantogram and a cephalogram were taken, were collected. On the orthopantomograms, the left third molar development was registered using the scoring system described by Gleiser and Hunt (1955) and modified by Köhler (1994) (GH). On the cephalograms, cervical vertebrae development was registered according to the BA and SE techniques. A regression model, with age as response and the GH scores as explanatory variable, was fitted to the data. Next, information of BA, SE and BA + SE was, respectively, added to this model. From all obtained models, the determination coefficients and the root mean squared errors were calculated. Inclusion of information from cephalograms based on the BA, as well as the SE, technique improved the amount of explained variance in age acquired from panoramic radiographs using the GH technique with 48%. Inclusion of cephalometric BA + SE information marginally improved the previous result (+1%). The RMSE decreased with 1.93, 1.85 and 2.03 years by adding, respectively, BA, SE and BA + SE information to the GH model. The SE technique allows clinically the fastest and easiest registration of the degree of development of the cervical vertebrae. Therefore, the choice of technique to classify cervical vertebrae development in addition to third molar development is preferably the SE technique.
机译:通过将这些牙科观察结果与年龄相关的骨骼信息相结合,可以减少使用基于第三磨牙发育的年龄估算方法获得的较宽的预测间隔。因此,在头颅X线照片上,搜索了最准确的估计年龄的骨骼变量和相关的配准方法,并将其添加到回归模型中,以年龄为响应,第三磨牙期为解释变量。在建立了496张(283 M; 213 F)头颅X线照片的数据集上的飞行员中,Baccetti等人的技术得到了应用。 (2005)(BA),Seedat等。 (2005)(SE),Caldas等。 (2007年)和Rai等人。 (2008)(RA)进行了验证。在主要研究中,收集了460位(208 F,224 M)年龄在3至26岁之间的数据,并在同一天拍摄了正畸图和头颅图。在正射影像图上,使用Gleiser和Hunt(1955)描述的评分系统并由Köhler(1994)(GH)修改的评分系统记录左第三磨牙的发育情况。在脑电图上,根据BA和SE技术记录了颈椎发育情况。数据以年龄为响应,GH评分为解释变量的回归模型拟合。接下来,将BA,SE和BA + SE的信息分别添加到此模型中。从所有获得的模型中,计算确定系数和均方根误差。包括基于BA和SE的头颅图的信息,使用GH技术从全景X线照片中获得的解释年龄变化量提高了48%。纳入头颅测量BA + SE信息可略微改善先前的结果(+ 1%)。通过分别向GH模型添加BA,SE和BA + SE信息,RMSE分别降低了1.93、1.85和2.03年。 SE技术可以在临床上最快,最简单地记录颈椎发育程度。因此,除第三磨牙发育之外,对颈椎发育进行分类的技术的选择优选为SE技术。

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