Department for Orthodontics and Pediatric Dentistry, University of Michigan, Ann Arbor, Michigan.
University of North Carolina, Chapel Hill, North Carolina.
Orthod Craniofac Res. 2019 May;22 Suppl 1(Suppl 1):213-220. doi: 10.1111/ocr.12281.
Clinical applications of 3D image registration and superimposition have contributed to better understanding growth changes and clinical outcomes. The use of 3D dental and craniofacial imaging in dentistry requires validate image analysis methods for improved diagnosis, treatment planning, navigation and assessment of treatment response. Volumetric 3D images, such as cone-beam computed tomography, can now be superimposed by voxels, surfaces or landmarks. Regardless of the image modality or the software tools, the concepts of regions or points of reference affect all quantitative of qualitative assessments. This study reviews current state of the art in 3D image analysis including 3D superimpositions relative to the cranial base and different regional superimpositions, the development of open source and commercial tools for 3D analysis, how this technology has increased clinical research collaborations from centres all around the globe, some insight on how to incorporate artificial intelligence for big data analysis and progress towards personalized orthodontics.
3D 图像配准和叠加的临床应用有助于更好地了解生长变化和临床结果。在牙科中使用 3D 口腔和颅面成像需要验证的图像分析方法,以提高诊断、治疗计划、导航和治疗反应评估的准确性。现在可以通过体素、表面或标志对容积 3D 图像(如锥形束计算机断层扫描)进行叠加。无论图像模态或软件工具如何,区域或参考点的概念都会影响所有定量和定性评估。本研究综述了 3D 图像分析的最新技术,包括相对于颅底的 3D 叠加和不同的区域叠加、用于 3D 分析的开源和商业工具的开发、这项技术如何增加来自全球各地中心的临床研究合作、如何将人工智能用于大数据分析的一些见解以及朝着个性化正畸的进展。