先进牙科的新领域：CBCT、口内扫描仪、传感器和牙科人工智能。
New Frontier in Advanced Dentistry: CBCT, Intraoral Scanner, Sensors, and Artificial Intelligence in Dentistry.
机构信息
Department of Orthodontics, Graduate School of Dentistry, Kyung Hee University, Seoul 02447, Korea.
Department of Orthodontics, Center for Advanced Dental Education, Saint Louis University, Saint Louis, MO 63104, USA.
出版信息
Sensors (Basel). 2022 Apr 12;22(8):2942. doi: 10.3390/s22082942.
Abstract
The advancement of science and technology has brought innovation in the dental field [...].
摘要
科学技术的进步给牙科领域带来了创新。
相似文献
1
New Frontier in Advanced Dentistry: CBCT, Intraoral Scanner, Sensors, and Artificial Intelligence in Dentistry.先进牙科的新领域：CBCT、口内扫描仪、传感器和牙科人工智能。
Sensors (Basel). 2022 Apr 12;22(8):2942. doi: 10.3390/s22082942.
2
Artificial intelligence models for clinical usage in dentistry with a focus on dentomaxillofacial CBCT: a systematic review.专注于牙颌面锥形束计算机断层扫描的牙科临床应用人工智能模型：一项系统评价
Oral Radiol. 2023 Jan;39(1):18-40. doi: 10.1007/s11282-022-00660-9. Epub 2022 Oct 21.
3
Accuracy and dimensional reproducibility by model scanning, intraoral scanning, and CBCT imaging for digital implant dentistry.模型扫描、口内扫描和 CBCT 成像在数字化种植牙科中的准确性和尺寸重现性。
Int J Implant Dent. 2021 Jun 30;7(1):63. doi: 10.1186/s40729-021-00343-w.
4
Cone Beam Computed Tomography (CBCT) Technology and Learning Outcomes in Dental Anatomy Education: E-Learning Approach.锥形束计算机断层扫描（CBCT）技术与牙体解剖学教育的学习成果：电子学习方法。
Anat Sci Educ. 2021 Nov;14(6):711-720. doi: 10.1002/ase.2066. Epub 2021 May 5.
5
Influence of dental fillings and tooth type on the performance of a novel artificial intelligence-driven tool for automatic tooth segmentation on CBCT images - A validation study.牙体填充和牙位对基于 CBCT 图像的新型人工智能驱动的自动牙体分割工具性能的影响 - 一项验证研究。
J Dent. 2022 Apr;119:104069. doi: 10.1016/j.jdent.2022.104069. Epub 2022 Feb 18.
6
Importance of artificial intelligence in the analysis of children's CBCT imaging by dental students.人工智能在牙科学生分析儿童锥形束计算机断层扫描（CBCT）影像中的重要性。
J Dent Educ. 2023 Jun;87 Suppl 1:914-916. doi: 10.1002/jdd.13060. Epub 2022 Jul 26.
7
A deep learning algorithm proposal to automatic pharyngeal airway detection and segmentation on CBCT images.一种用于在锥形束计算机断层扫描（CBCT）图像上自动进行咽部气道检测和分割的深度学习算法方案。
Orthod Craniofac Res. 2021 Dec;24 Suppl 2:117-123. doi: 10.1111/ocr.12480. Epub 2021 Mar 8.
8
An audit and service evaluation of the use of cone beam computed tomography (CBCT) in a paediatric dentistry department.对儿科牙科部门使用锥形束计算机断层扫描 (CBCT) 的审核和服务评估。
Dentomaxillofac Radiol. 2019 Jul;48(5):20180393. doi: 10.1259/dmfr.20180393. Epub 2019 Feb 12.
9
Development and validation of a novel artificial intelligence driven tool for accurate mandibular canal segmentation on CBCT.开发和验证一种新型人工智能驱动的工具，用于在 CBCT 上准确分割下颌管。
J Dent. 2022 Jan;116:103891. doi: 10.1016/j.jdent.2021.103891. Epub 2021 Nov 13.
10
Artificial Intelligence DENTOMO: Opportunities and Prospects for Interpretation of Cone Beam CT in Dentistry.人工智能 DENTOMO：锥形束 CT 在牙科中解释的机会和前景。
Bull Exp Biol Med. 2021 Mar;170(5):686-688. doi: 10.1007/s10517-021-05133-3. Epub 2021 Mar 31.
引用本文的文献
1
[Advances in low-dose cone-beam computed tomography image reconstruction methods based on deep learning].基于深度学习的低剂量锥束计算机断层扫描图像重建方法进展
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2025 Jun 25;42(3):635-642. doi: 10.7507/1001-5515.202409021.
2
Sivan classification system for diagnosis of jaw lesions based on visual volumetric analysis of 3-dimensional cone-beam computed tomographic images.基于三维锥形束计算机断层扫描图像视觉容积分析的颌骨病变诊断西万分类系统。
Sci Rep. 2024 Dec 30;14(1):32138. doi: 10.1038/s41598-024-83974-4.
3
New Approaches and Technologies in Orthodontics.正畸学的新方法与新技术
J Clin Med. 2024 Apr 24;13(9):2470. doi: 10.3390/jcm13092470.
4
Automated Caries Screening Using Ensemble Deep Learning on Panoramic Radiographs.基于全景X线片的集成深度学习自动龋病筛查
Entropy (Basel). 2022 Sep 24;24(10):1358. doi: 10.3390/e24101358.
5
Effectiveness of creating digital twins with different digital dentition models and cone-beam computed tomography.不同数字化牙颌模型和锥形束计算机断层扫描创建数字孪生体的有效性。
Sci Rep. 2023 Jun 30;13(1):10603. doi: 10.1038/s41598-023-37774-x.
6
Artificial Intelligence in Medicine and Dentistry.医学与牙医学中的人工智能
Acta Stomatol Croat. 2023 Mar;57(1):70-84. doi: 10.15644/asc57/1/8.
7
Full-Arch Guided Restoration and Bone Regeneration: A Complete Digital Workflow Case Report.全牙弓引导式修复与骨再生：一份完整的数字化工作流程病例报告。
Healthcare (Basel). 2023 May 2;11(9):1301. doi: 10.3390/healthcare11091301.
8
Temporomandibular Joint Osteoarthritis Diagnosis Employing Artificial Intelligence: Systematic Review and Meta-Analysis.运用人工智能诊断颞下颌关节骨关节炎：系统评价与荟萃分析
J Clin Med. 2023 Jan 25;12(3):942. doi: 10.3390/jcm12030942.
9
Where Is the Artificial Intelligence Applied in Dentistry? Systematic Review and Literature Analysis.人工智能在牙科领域的应用现状：系统评价与文献分析
Healthcare (Basel). 2022 Jul 8;10(7):1269. doi: 10.3390/healthcare10071269.
10
3D Cephalometric Normality Range: Auto Contractive Maps (ACM) Analysis in Selected Caucasian Skeletal Class I Age Groups.三维头影测量正常范围：特定白种人骨骼Ⅰ类年龄组的自收缩映射（ACM）分析
Bioengineering (Basel). 2022 May 17;9(5):216. doi: 10.3390/bioengineering9050216.
本文引用的文献
1
Cone-Beam Angle Dependency of 3D Models Computed from Cone-Beam CT Images.基于锥形束 CT 图像的三维模型的锥形束角度依赖性。
Sensors (Basel). 2022 Feb 7;22(3):1253. doi: 10.3390/s22031253.
2
Sandwich Integration Technique for the Pressure Sensor Detection of Occlusal Force In Vitro.夹心式整合技术用于体外咬合压力传感器检测。
Sensors (Basel). 2021 Dec 29;22(1):220. doi: 10.3390/s22010220.
3
Pros and Cons of CAD/CAM Technology for Infection Prevention in Dental Settings during COVID-19 Outbreak.CAD/CAM 技术在 COVID-19 疫情期间预防牙科环境感染的优缺点。
Sensors (Basel). 2021 Dec 22;22(1):49. doi: 10.3390/s22010049.
4
Sagittal and Vertical Growth of the Maxillo-Mandibular Complex in Untreated Children: A Longitudinal Study on Lateral Cephalograms Derived from Cone Beam Computed Tomography.未治疗儿童的上颌-下颌复合体矢状和垂直生长：来自锥形束计算机断层扫描的侧颅面片的纵向研究。
Sensors (Basel). 2021 Dec 20;21(24):8484. doi: 10.3390/s21248484.
5
A CBCT Evaluation of Midpalatal Bone Density in Various Skeletal Patterns.不同骨骼类型的中 palate 骨密度的锥形束 CT 评估。
Sensors (Basel). 2021 Nov 24;21(23):7812. doi: 10.3390/s21237812.
6
A Multi-Center Disclusion Time Reduction (DTR) Randomized Controlled Occlusal Adjustment Study Using Occlusal Force and Timing Sensors Synchronized with Muscle Physiology Sensors.一项多中心的闭口时间减少（DTR）随机对照咬合调整研究，使用与肌肉生理学传感器同步的咬合力和时间传感器。
Sensors (Basel). 2021 Nov 24;21(23):7804. doi: 10.3390/s21237804.
7
Diagnostic Accuracy of Cystic Lesions Using a Pre-Programmed Low-Dose and Standard-Dose Dental Cone-Beam Computed Tomography Protocol: An Ex Vivo Comparison Study.使用预编程低剂量和标准剂量口腔锥形束计算机断层扫描方案评估囊性病变的诊断准确性：一项离体比较研究。
Sensors (Basel). 2021 Nov 7;21(21):7402. doi: 10.3390/s21217402.
8
Transverse Growth of the Maxillo-Mandibular Complex in Untreated Children: A Longitudinal Cone Beam Computed Tomography Study.未治疗儿童的上颌-下颌复合体横向生长：一项纵向锥形束 CT 研究。
Sensors (Basel). 2021 Sep 24;21(19):6378. doi: 10.3390/s21196378.
9
Three-Dimensional Digital Superimposition of Orthodontic Bracket Position by Using a Computer-Aided Transfer Jig System: An Accuracy Analysis.利用计算机辅助转移夹具系统实现正畸托槽位置的三维数字叠加：准确性分析。
Sensors (Basel). 2021 Sep 2;21(17):5911. doi: 10.3390/s21175911.
10
Evaluation of Periodontal Risk Factors with Quantitative Light-Induced Fluorescence Based Fluorescent Plaque Index, in Comparison to Radiographic and Oral Health Habit Scoring: A Retrospective Case Study.基于定量光激荧光的荧光菌斑指数评估牙周危险因素与放射影像及口腔卫生习惯评分的比较：一项回顾性病例研究。
Sensors (Basel). 2021 Aug 27;21(17):5774. doi: 10.3390/s21175774.
Zotero 插件