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The Segmentation and 3D Reconstruction of Teeth, Root Canals, and Alveolar Bones in CBCT Images Based on AVIZO
Yan Liu1, Chunshen Li1, Pengyu Chen1
1Department of Stomatology, The First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta West Road, Xi'an, 710061, Shaanxi, China, xjtu.edu.cn.
Background:
This study utilized AVIZO software and manual segmentation techniques to extract individual teeth, root canals, and alveolar bone structures from cone beam computed tomography (CBCT) images. A three-dimensional model suitable for personalized treatment planning was constructed, which holds significant implications for clinical diagnosis and treatment.
Methods:
We collected 576 CBCT dental images. Based on AVIZO software, the tooth, root canal, and alveolar bone were segmented and 3D reconstructed by image calibration, image noise reduction and edge enhancement, manual labeling, and other methods.
Results:
Our approach enables segmentation and reconstruction, allowing for quantitative analysis of 3D reconstructed teeth and root canals, including tooth 3D volume size, dip angle, azimuth angle, and shape factors. Three-dimensional volume range: 0.31-1.11 cm3, tooth dip angle range: 2.02-49.39, tooth azimuth range: -158.38-176.36, tooth shape factor range: 3.74-9.59, and root canal shape factor range: 4.93-17.64.
Conclusions:
We successfully achieved segmentation and three-dimensional reconstruction of teeth, root canals, and alveolar bone. Based on the reconstruction results, we obtained corresponding quantitative data, providing objective and quantitative evidence for developing personalized treatment plans.
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