Department of Orthodontics, School of Dentistry, University of North Carolina, Chapel Hill, NC 27599, USA.
Am J Orthod Dentofacial Orthop. 2010 Apr;137(4 Suppl):S120-9. doi: 10.1016/j.ajodo.2009.04.021.
The recent emphases on soft tissues as the limiting factor in treatment and on soft-tissue relationships in establishing the goals of treatment has made 3-dimensional (3D) analysis of soft tissues more important in diagnosis and treatment planning. It is equally important to be able to detect changes in the facial soft tissues produced by growth or treatment. This requires structures of reference for superimposition and a way to display the changes with quantitative information.
In this study, we outlined a technique for quantifying facial soft-tissue changes viewed in cone-beam computed tomography data, using fully automated voxel-wise registrations of the cranial base surface. The assessment of soft-tissue changes is done by calculation of the Euclidean surface distances between the 3D models. Color maps are used for visual assessment of the location and the quantification of changes.
This methodology allows a detailed examination of soft-tissue changes with growth or treatment.
Because of the lack of stable references with 3D photogrammetry, 3D photography, and laser scanning, soft-tissue changes cannot be accurately quantified by these methods.
最近,人们强调软组织是治疗的限制因素,并强调软组织关系在确定治疗目标方面的重要性,这使得 3 维(3D)软组织分析在诊断和治疗计划中变得更加重要。能够检测到由生长或治疗引起的面部软组织的变化同样重要。这需要参考结构进行叠加,并需要一种方法用定量信息显示变化。
在这项研究中,我们概述了一种使用颅底表面的全自动体素配准技术来量化锥形束 CT 数据中观察到的面部软组织变化的技术。通过计算 3D 模型之间的欧几里得表面距离来评估软组织变化。颜色图用于视觉评估位置和量化变化。
该方法允许详细检查生长或治疗引起的软组织变化。
由于缺乏 3D 摄影测量、3D 摄影和激光扫描的稳定参考,这些方法无法准确量化软组织变化。