ORIGINAL RESEARCH article
Front. Bioeng. Biotechnol.
Sec. Biosensors and Biomolecular Electronics
Volume 13 - 2025 | doi: 10.3389/fbioe.2025.1565403
Tooth Image Segmentation and Root Canal Measurement Based on Deep Learning
Provisionally accepted
- Sichuan University, Chengdu, China
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This study aims to develop a fully automated method for tooth segmentation and root canal measurement based on cone beam computed tomography (CBCT) images, providing objective, efficient, and accurate measurement results to guide and assist clinicians in root canal diagnosis grading, instrument selection, and preoperative planning. The method utilizes Attention U-Net to recognize tooth descriptors, crops regions of interest (ROIs) based on the center of mass of these descriptors, and applies an integrated deep learning method for segmentation. The segmentation results are mapped back to the original coordinates and position-corrected, followed by automatic measurement and visualization of root canal lengths and angles. The results indicated that the Dice coefficient for segmentation was 96.33%, the Jaccard coefficient was 92.94%, the Hausdorff distance was 2.04 mm, and the mean surface distance was 0.24 mm, all surpassing existing methods. The relative error of root canal length measurement was 3.42% (less than 5%), and the effect of auto-correction was recognized by clinicians.
Keywords: Tooth instance segmentation, CBCT, Root canal measurement, deep learning, Attention U-net, V-Net
Received: 23 Jan 2025; Accepted: 28 May 2025.
Copyright: © 2025 Chen, Liu, Wang, Ji, Gong and Gao. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Qi Liu, Sichuan University, Chengdu, China
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