Tooth image segmentation and root canal measurement based on deep learning.

IF 4.8 3区工程技术 Q1 BIOTECHNOLOGY & APPLIED MICROBIOLOGY

Frontiers in Bioengineering and Biotechnology Pub Date : 2025-06-09 eCollection Date: 2025-01-01 DOI:10.3389/fbioe.2025.1565403

Ziqing Chen, Qi Liu, Jialei Wang, Nuo Ji, Yuhang Gong, Bo Gao

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引用次数: 0

Abstract

Indroduction: This study aims to develop a 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.

Methods: We 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.

Results: Quantitative evaluation demonstrated a segmentation Dice coefficient of 96.33%, Jaccard coefficient of 92.94%, Hausdorff distance of 2.04 mm, and Average surface distance of 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.

Discussion: The proposed segmentation method demonstrates favorable performance, with a relatively low relative error between automated and manual measurements, providing valuable reference for clinical applications.

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基于深度学习的牙齿图像分割与根管测量。

摘要：本研究旨在建立一种基于锥形束ct （cone beam computed tomography， CBCT）图像的牙齿分割与根管测量自动化方法，提供客观、高效、准确的测量结果，指导和协助临床医生进行根管诊断分级、器械选择和术前规划。方法：利用注意力U-Net识别牙齿描述符，基于这些描述符的质心提取感兴趣区域（roi），并应用集成深度学习方法进行分割。分割结果被映射回原始坐标并进行位置校正，然后自动测量根管长度和角度并可视化。结果：定量评价表明，该分割方法的Dice系数为96.33%，Jaccard系数为92.94%，Hausdorff距离为2.04 mm，平均表面距离为0.24 mm，均优于现有方法。根管长度测量的相对误差为3.42%（小于5%），自动矫正效果得到临床医生的认可。讨论：本文提出的分割方法具有良好的性能，自动测量和人工测量之间的相对误差较低，为临床应用提供了有价值的参考。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Frontiers in Bioengineering and Biotechnology Chemical Engineering-Bioengineering

CiteScore

8.30

自引率

5.30%

发文量

2270

审稿时长

12 weeks

期刊介绍： The translation of new discoveries in medicine to clinical routine has never been easy. During the second half of the last century, thanks to the progress in chemistry, biochemistry and pharmacology, we have seen the development and the application of a large number of drugs and devices aimed at the treatment of symptoms, blocking unwanted pathways and, in the case of infectious diseases, fighting the micro-organisms responsible. However, we are facing, today, a dramatic change in the therapeutic approach to pathologies and diseases. Indeed, the challenge of the present and the next decade is to fully restore the physiological status of the diseased organism and to completely regenerate tissue and organs when they are so seriously affected that treatments cannot be limited to the repression of symptoms or to the repair of damage. This is being made possible thanks to the major developments made in basic cell and molecular biology, including stem cell science, growth factor delivery, gene isolation and transfection, the advances in bioengineering and nanotechnology, including development of new biomaterials, biofabrication technologies and use of bioreactors, and the big improvements in diagnostic tools and imaging of cells, tissues and organs. In today`s world, an enhancement of communication between multidisciplinary experts, together with the promotion of joint projects and close collaborations among scientists, engineers, industry people, regulatory agencies and physicians are absolute requirements for the success of any attempt to develop and clinically apply a new biological therapy or an innovative device involving the collective use of biomaterials, cells and/or bioactive molecules. “Frontiers in Bioengineering and Biotechnology” aspires to be a forum for all people involved in the process by bridging the gap too often existing between a discovery in the basic sciences and its clinical application.