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结合口腔内扫描、锥形束计算机断层扫描和面部扫描:虚拟患者。

Combining Intraoral Scans, Cone Beam Computed Tomography and Face Scans: The Virtual Patient.

作者信息

Mangano Carlo, Luongo Fabrizia, Migliario Mario, Mortellaro Carmen, Mangano Francesco Guido

机构信息

Department of Dental Sciences, Dental School, San Raffaele University, Milan.

Private Practice, Rome.

出版信息

J Craniofac Surg. 2018 Nov;29(8):2241-2246. doi: 10.1097/SCS.0000000000004485.

DOI:10.1097/SCS.0000000000004485
PMID:29698362
Abstract

PURPOSE

The aim of this literature review was to provide an update on the current scientific knowledge in the field of 3D virtual patient science and to identify a possible easy, smart, and affordable method to combine different file formats obtained from different digital devices.

METHODS

Electronic searches of the Medline database was performed, up to May 2017, for articles dealing with the construction of a 3D virtual patient; the matching of data acquired with different digital devices (cone beam computed tomography, CBCT; face scanner, FS; intraoral scanner, IOS; and desktop scanner, DS) was considered. The inclusion of studies was based on the superimposition of at least 2 different digital sources.

RESULTS

Twenty-five studies were selected for subsequent examination. Only 3 studies analyzed the feasibility of superimposition of 3 different types of 3D data (CBCT + FS + IOS/DS). The most frequently used matching procedure was between CBCT and FS and CBCT and IOS/DS.

CONCLUSION

The procedure of superimposition of data from CBCT, IOS, and FS is currently feasible and it is now possible to create a 3D "virtual patient" to better diagnose, plan the treatment, and communicate with patients.

摘要

目的

本综述的目的是更新3D虚拟患者科学领域的当前科学知识,并确定一种可能简单、智能且经济实惠的方法,以整合从不同数字设备获得的不同文件格式。

方法

截至2017年5月,对Medline数据库进行电子检索,查找有关3D虚拟患者构建的文章;考虑了用不同数字设备(锥形束计算机断层扫描,CBCT;面部扫描仪,FS;口腔内扫描仪,IOS;台式扫描仪,DS)获取的数据匹配情况。纳入研究基于至少2种不同数字来源的叠加。

结果

选择了25项研究进行后续审查。只有3项研究分析了叠加3种不同类型3D数据(CBCT + FS + IOS/DS)的可行性。最常用的匹配程序是CBCT与FS以及CBCT与IOS/DS之间的匹配。

结论

目前,来自CBCT、IOS和FS的数据叠加程序是可行的,现在有可能创建一个3D“虚拟患者 ”,以更好地进行诊断、规划治疗并与患者沟通。

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