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

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 demonstrat

SUBMITTER: Chen Z 

PROVIDER: S-EPMC12183224 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature