Academic Journal
Image-based automated measurement of orthodontic tooth displacement using bracket detection.
| Τίτλος: | Image-based automated measurement of orthodontic tooth displacement using bracket detection. |
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| Συγγραφείς: | Wang Y; School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, People's Republic of China., Mesghena DR; Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, People's Republic of China.; University of Chinese Academy of Sciences, Beijing 101408, People's Republic of China., He Z; School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, People's Republic of China., Xiong J; Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, People's Republic of China., Zhao N; Department of Orthodontics, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200011, People's Republic of China., Xia Z; School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, People's Republic of China. |
| Πηγή: | Medical engineering & physics [Med Eng Phys] 2026 Sep 11; Vol. 147 (9). Date of Electronic Publication: 2026 Sep 11. |
| Τύπος έκδοσης: | Journal Article |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: Butterworth-Heinemann Country of Publication: England NLM ID: 9422753 Publication Model: Electronic Cited Medium: Internet ISSN: 1873-4030 (Electronic) Linking ISSN: 13504533 NLM ISO Abbreviation: Med Eng Phys Subsets: MEDLINE |
| Imprint Name(s): | Publication: London : Butterworth-Heinemann Original Publication: Oxford, UK : Butterworth-Heinemann, c1994- |
| Ιατρικοί όροι (MeSH): | Image Processing, Computer-Assisted*/methods , Orthodontic Brackets* , Tooth*, Humans ; Automation |
| Περίληψη: | Accurate measurement of tooth displacement is essential for orthodontic treatment planning and outcome evaluation. In routine practice, however, commonly used methods such as manual caliper measurement are constrained by limited resolution, marked operator dependence, and low efficiency when repeated measurements are required. This study proposes a fully automated image-based measurement framework in which orthodontic brackets are detected as anatomical reference markers using a YOLOv11-based detection model. The detected brackets are then automatically sorted, classified into maxillary and mandibular groups, and used for scale-normalized distance calculation, enabling high-precision displacement measurement. The method can support real-time longitudinal monitoring during orthodontic treatment and retrospective quantitative analysis of archived clinical images. Evaluation on an intraoral clinical dataset from six orthodontic patients showed that the model achieved an average mAP@0.5 of 95.4% and a precision of 97.9% in patient-level cross-validation, with an average processing time of 40 ms per image. The system measurement resolution reached 0.01 mm. In 140 clinical gauge-block validation measurements, the mean absolute error was 0.028 mm, and all errors were within 0.05 mm. These results indicate that the proposed system provides a rapid, accurate, and repeatable solution for clinical assessment of orthodontic tooth displacement. (© 2026 Institute of Physics and Engineering in Medicine. All rights, including for text and data mining, AI training, and similar technologies, are reserved.) |
| Contributed Indexing: | Keywords: dental measurement; medical image processing; orthodontics; precision dentistry; tooth displacement |
| Entry Date(s): | Date Created: 20260902 Date Completed: 20260911 Latest Revision: 20260911 |
| Update Code: | 20260911 |
| DOI: | 10.1088/1873-4030/aea162 |
| PMID: | 42685755 |
| Βάση Δεδομένων: | MEDLINE |
| ISSN: | 1873-4030 |
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| DOI: | 10.1088/1873-4030/aea162 |