• Oriented tooth detection: a CB...

Treffer: Oriented tooth detection: a CBCT image processing method integrated with RoI transformer.

Title:
Oriented tooth detection: a CBCT image processing method integrated with RoI transformer.
Authors:
Zhao Z; School of Biomedical Engineering, Capital Medical University, Beijing 100069, China.; Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, Capital Medical University, Beijing 100069, China.; Department of Stomatology, Beijing Friendship Hospital, Capital Medical University, Beijing 10050, China.; School of Stomatology, Capital Medical University, Beijing 100070, China., Wu B; School of Biomedical Engineering, Capital Medical University, Beijing 100069, China.; Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, Capital Medical University, Beijing 100069, China., Su S; Department of Stomatology, Beijing Friendship Hospital, Capital Medical University, Beijing 10050, China., Liu D; School of Biomedical Engineering, Capital Medical University, Beijing 100069, China.; Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, Capital Medical University, Beijing 100069, China., Wu Z; Department of Stomatology, Beijing Friendship Hospital, Capital Medical University, Beijing 10050, China., Gao R; Department of Stomatology, Beijing Friendship Hospital, Capital Medical University, Beijing 10050, China., Zhang N; School of Biomedical Engineering, Capital Medical University, Beijing 100069, China.; Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, Capital Medical University, Beijing 100069, China.
Source:
Dento maxillo facial radiology [Dentomaxillofac Radiol] 2025 Nov 01; Vol. 54 (8), pp. 695-705.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Oxford University Press Country of Publication: England NLM ID: 7609576 Publication Model: Print Cited Medium: Internet ISSN: 1476-542X (Electronic) Linking ISSN: 0250832X NLM ISO Abbreviation: Dentomaxillofac Radiol Subsets: MEDLINE
Imprint Name(s):
Publication: January 2024- : [Oxford] : Oxford University Press
Original Publication: Erlangen, Germany : University Press Erlangen
MeSH Terms:
Cone-Beam Computed Tomography*/methods , Tooth*/diagnostic imaging , Image Processing, Computer-Assisted*/methods, Humans ; Imaging, Three-Dimensional/methods ; Radiography, Panoramic/methods
Grant Information:
61672362 National Natural Science Foundation of China; 81771026 National Natural Science Foundation of China; 4232002 Beijing Natural Science Foundation
Contributed Indexing:
Keywords: CBCT image processing; RoI transformer; cone beam computed tomography; oriented object detection; tooth detection
Entry Date(s):
Date Created: 20250711 Date Completed: 20251126 Latest Revision: 20251126
Update Code:
20251127
DOI:
10.1093/dmfr/twaf049
PMID:
40644333
Database:
MEDLINE

Weitere Informationen

Objectives: Cone beam computed tomography (CBCT) has revolutionized dental imaging due to its high spatial resolution and ability to provide detailed 3-dimensional reconstructions of dental structures. This study introduces an innovative CBCT image processing method using an oriented object detection approach integrated with a Region of Interest (RoI) transformer.
Methods: This study addresses the challenge of accurate tooth detection and classification in PAN derived from CBCT, introducing an innovative oriented object detection approach, which has not been previously applied in dental imaging. This method better aligns with the natural growth patterns of teeth, allowing for more accurate detection and classification of molars, premolars, canines, and incisors. By integrating RoI transformer, the model demonstrates relatively acceptable performance metrics compared to conventional horizontal detection methods while also offering enhanced visualization capabilities. Furthermore, post-processing techniques, including distance and greyscale value constraints, are employed to correct classification errors and reduce false positives, especially in areas with missing teeth.
Results: The experimental results indicate that the proposed method achieves an accuracy of 98.48%, a recall of 97.21%, an F1 score of 97.21%, and an mean average precision (mAP) of 98.12% in tooth detection.
Conclusions: The proposed method enhances the accuracy of tooth detection in CBCT-derived PAN by reducing background interference and improving the visualization of tooth orientation.
(© The Author(s) 2025. Published by Oxford University Press on behalf of the British Institute of Radiology and the International Association of Dentomaxillofacial Radiology. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)