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验证口内扫描到锥形束计算机断层扫描的自动配准,以实现高效的数字化牙科工作流程。

Validation of automated registration of intraoral scan onto Cone Beam Computed Tomography for an efficient digital dental workflow.

机构信息

OMFS IMPATH Research Group, Department of Imaging & Pathology, Faculty of Medicine, KU Leuven & Oral and Maxillofacial Surgery, University Hospitals Leuven, Kapucijnenvoer 33 BE-3000 Leuven, Belgium.

OMFS IMPATH Research Group, Department of Imaging & Pathology, Faculty of Medicine, KU Leuven & Oral and Maxillofacial Surgery, University Hospitals Leuven, Kapucijnenvoer 33 BE-3000 Leuven, Belgium; Department of Oral Diagnosis, Division of Oral Radiology, Piracicaba Dental School, University of Campinas (UNICAMP), Av. Limeira 901, Piracicaba, São Paulo 13414‑903, Brazil.

出版信息

J Dent. 2024 Oct;149:105282. doi: 10.1016/j.jdent.2024.105282. Epub 2024 Jul 31.

Abstract

OBJECTIVE

This study aimed to validate a newly developed automated method (Virtual Patient Creator, Relu, Leuven, Belgium) for multimodal registration of intraoral scan (IOS) and Cone Beam Computed Tomography (CBCT).

METHODS

Time point-matched IOS and CBCT scans of forty patients with variable dental statuses (natural dentition, partial edentulism, presence of orthodontic brackets) were selected. Three operators registered IOS and CBCT scans using three state-of-the-art softwares for orthodontics and orthognathic surgery (IPS Case Designer, Proplan CMF and Dolphin Imaging). Automated registration was compared to expert-performed semi-automated registration. Time consumption, accuracy, and consistency of the proposed method were benchmarked to semi-automated registration using root mean squared error calculations. The robustness of the automated registration was evaluated in relationship to the dental status of the patients in the dataset.

RESULTS

On average, automatic registration was 7.3 times faster than semi-automatic registration performed by an expert operator. Automatic registration yielded reliable results with low deviation errors compared to the differently skilled operators and semi-automated software. Automated registration surpassed human variability as expressed in intra- and inter-operator inconsistencies. Neither orthodontic brackets nor edentulism impacted registration accuracy.

CONCLUSIONS

The presented automated method for IOS and CBCT registration is faster, equally accurate, and more consistent than semi-automatic registration performed by an expert or an occasional operator. With similar results among cases with different dental statuses, the clinical feasibility of the method is ensured.

CLINICAL SIGNIFICANCE

A validated automated registration method provides accurate and fast multimodal image integration without incorporating operator bias at the very start of the digital workflows for dentistry, periodontics, orthodontics and orthognathic surgery.

摘要

目的

本研究旨在验证一种新开发的自动方法(比利时鲁汶的虚拟患者创建者、Relu),用于口腔内扫描(IOS)和锥形束计算机断层扫描(CBCT)的多模态配准。

方法

选择了四十名具有不同牙齿状况(天然牙、部分缺牙、正畸托槽存在)的患者的时间点匹配的 IOS 和 CBCT 扫描。三名操作员使用三种正畸和正颌手术的最先进软件(IPS Case Designer、Proplan CMF 和 Dolphin Imaging)注册 IOS 和 CBCT 扫描。将自动注册与专家执行的半自动注册进行比较。使用均方根误差计算来评估所提出的方法的时间消耗、准确性和一致性,以半自动注册为基准。评估了自动化注册在数据集患者牙齿状况方面的稳健性。

结果

平均而言,自动注册比专家操作员执行的半自动注册快 7.3 倍。与不同技能水平的操作员和半自动软件相比,自动注册产生的结果可靠,偏差误差低。自动注册超过了人类变异性,表现在操作员内和操作员间的不一致性。正畸托槽或缺牙都不会影响注册准确性。

结论

与专家或偶尔操作员执行的半自动注册相比,所提出的用于 IOS 和 CBCT 注册的自动方法更快、同样准确且更一致。具有不同牙齿状况的病例之间具有相似的结果,确保了该方法的临床可行性。

临床意义

经过验证的自动注册方法在牙科、牙周病学、正畸和正颌手术的数字化工作流程开始时提供了准确、快速的多模态图像集成,而不会引入操作员偏见。

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