Purpose: This study investigated the accuracy of full-arch intraoral scans obtained by various scan strategies with the segmental scan and merge methods.
Materials And Methods: Seventy intraoral scans (seven scans per group) were performed using 10 scan strategies that differed in the segmental scan (1, 2, or 3 segments) and the scanning motion (straight, zigzag, or combined). The three-dimensional (3D) geometric accuracy of scan images was evaluated by comparison with a reference image in an image analysis software program, in terms of the arch shape discrepancies. Measurement parameters were the intermolar distance, interpremolar distance, anteroposterior distance, and global surface deviation. One-way analysis of variance and Tukey honestly significance difference post hoc tests were carried out to compare differences among the scan strategy groups (α = .05).
Results: The linear discrepancy values of intraoral scans were not different among scan strategies performed with the single scan and segmental scan methods. In general, differences in the scan motion did not show different accuracies, except for the intermolar distance measured under the scan conditions of a 3-segmental scan and zigzag motion. The global surface deviations were not different among all scan strategies.
Conclusion: The segmental scan and merge methods using two scan parts appear to be reliable as an alternative to the single scan method for full-arch intraoral scans. When three segmental scans are involved, the accuracy of complete arch scan can be negatively affected.
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http://dx.doi.org/10.4047/jap.2022.14.2.88 | DOI Listing |
Medicine (Baltimore)
January 2025
Department of Oral and Maxillofacial Surgery.
Rationale: When gland-preserving treatments are unsuccessful, sialoadenectomy is typically conducted for patients afflicted with submandibular gland diseases. The definitive treatment modality for these individuals is the removal of both the gland and the associated ducts. During surgery, the gland and the majority of the ducts can be excised utilizing the lateral transcervical approach, with residual ducts unlikely to develop pathology.
View Article and Find Full Text PDFClin Oral Investig
January 2025
Department of Dentistry Section Orthodontics and Craniofacial Biology, Radboud University Medical Center, P.O. Box 9101, Nijmegen, 6500 HB, The Netherlands.
Objectives: For this research two different ways for integrating intra-oral scans into three-dimensional (3D) stereophotogrammetric images are analyzed and compared to the gold standard method.
Materials And Methods: A cross-sectional study was performed. For each patient a complete dataset was collected, which was used to generate 3D fusion models by three different methods: method A using cheek retractors, method B using a tracer and method C using full-skull CBCT.
J Esthet Restor Dent
January 2025
Center of Advanced Dental Education, Department of Periodontics, Saint Louis University, Saint Louis, Missouri, USA.
Objectives: To investigate the correlation between gingival thickness (GT) and buccal bone thickness (BBT), as well as the effects of GT, BBT, bone crest level (BC), and tooth position on the buccal gingival margin location of maxillary teeth in the esthetic zone.
Materials And Methods: Periodontally healthy subjects with prior cone beam computed tomography and intraoral scans for dental implant planning were included. The hard and soft tissue measurements were retrospectively analyzed digitally.
BMC Oral Health
January 2025
Department of Stomatology, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde, Foshan), Foshan, 528308, Guangdong, China.
Background: A comprehensive analysis of the occlusal plane (OP) inclination in predicting anteroposterior mandibular position (APMP) changes is still lacking. This study aimed to analyse the relationships between inclinations of different OPs and APMP metrics and explore the feasibility of OP inclination in predicting changes in APMP.
Methods: Overall, 115 three-dimensional (3D) models were reconstructed using deep learning-based cone-beam computed tomography (CBCT) segmentation, and their accuracy in supporting cusps was compared with that of intraoral scanning models.
Med Image Anal
December 2024
Stomatology Hospital Affliated to Zhejiang University of Medicine, Zhejiang University, Hangzhou, 310016, China; ZJU-Angelalign R&D Center for Intelligence Healthcare, ZJU-UIUC Institute, Zhejiang University, Haining, 314400, China; Zhejiang Key Laboratory of Medical Imaging Artificial Intelligence, Zhejiang University, Hangzhou, 310058, China. Electronic address:
Automatic 3-dimensional tooth segmentation on intraoral scans (IOS) plays a pivotal role in computer-aided orthodontic treatments. In practice, deploying existing well-trained models to different medical centers suffers from two main problems: (1) the data distribution shifts between existing and new centers, which causes significant performance degradation. (2) The data in the existing center(s) is usually not permitted to be shared, and annotating additional data in the new center(s) is time-consuming and expensive, thus making re-training or fine-tuning unfeasible.
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