3D assessment of the nasolabial region in cleft models comparing an intraoral and a facial scanner to a validated baseline

对唇腭裂模型鼻唇沟区域进行三维评估,比较口内扫描仪和面部扫描仪与已验证的基线数据。

阅读:1

Abstract

We aimed to validate the metric accuracy of a 3-dimensional (3D) facial scanner (FS) and an intraoral scanner (IOS) in capturing the nasolabial region in ex vivo unilateral cleft lip and palate (UCLP) models. The nasolabial region of 10 UCLP models was scanned using a 3D FS as well as an IOS and a previously validated stationary 3D scanner as a reference. Intraoral scan was performed directly on the UCLP models. In order to apply the FS on the models, they were embedded in a 3D printed sample face. Both test groups were aligned to the reference by applying a section-based best-fit algorithm. Subsequent analysis of the metric deviation from the reference was performed with a 3D analysis tool. Mean distance and integrated distance served as main parameters for surface and volume comparison. Point comparison served as an additional parameter. Statistical analysis was carried out using t-test for unconnected samples. Considering mean distance and integrated distance as main parameters for 3D evaluation of the scanner's accuracy, FS and IOS differ significantly in their metric precision in scanning the cleft model compared to the reference. The IOS proved to be significantly more accurate than the FS compared to the previously described stationary 3D scanner as reference and validated baseline. Further validation of the tested IOS and FS for 3D assessment of the nasolabial region is presented by adding the previously validated ATOS III Triple Scan blue light scanner as a reference. The IOS shows, compared to a validated baseline scan, significantly higher metric precision in experimental cleft model scanning. The collected data provides a basis for clinical application of the IOS for 3D assessment of the nasolabial region.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。