research-article

CBCT image segmentation of tooth-root canal based on improved level set algorithm

Authors:

Xia WenjunAuthors Info & Claims

CIPAE 2020: Proceedings of the 2020 International Conference on Computers, Information Processing and Advanced Education

Pages 42 - 51

https://doi.org/10.1145/3419635.3419654

Published: 16 October 2020 Publication History

Abstract

Image segmentation of the root canal is important basis for the establishment of a three-dimensional model for application value clinical diagnosis and education. A total of 1554 CBCT images of polymorphic roots of 10 in vivo and 8 in vitro teeth were preprocessed by the adaptive enhancement algorithm of CLAHS and Laplace-γ, respectively. An improved level set algorithm was then used to segment the tooth-root canal image. In the process of curve evolution and convergence of the improved level set algorithm, the evolution of tooth-root canal contour was constrained by adding a new regularization function. Based on the similarity of root canal contours between adjacent sections of a tooth, a self-qualifying method was established to determine the initial contour of the root canal. In addition, a process was set up to analyze the data of a neighboring tooth to improve the segmentation process. Using the stated improvements, a set of root canal image segmentation methods was established for a single tooth based on the improved level set algorithm. Experimental results show that the average accuracy of the improved level set algorithm for root canal image segmentation is 84.7%, while in clinical trials, the average qualified rate is 90.4%.

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Cited By

Tan MCui ZZhong TFang YZhang YShen D(2024)A progressive framework for tooth and substructure segmentation from cone-beam CT imagesComputers in Biology and Medicine10.1016/j.compbiomed.2023.107839169:COnline publication date: 17-Apr-2024
https://dl.acm.org/doi/10.1016/j.compbiomed.2023.107839
Chen ZChen SHu F(2023)CTA-UNet: CNN-transformer architecture UNet for dental CBCT images segmentationPhysics in Medicine & Biology10.1088/1361-6560/acf02668:17(175042)Online publication date: 31-Aug-2023
https://doi.org/10.1088/1361-6560/acf026
Wang YXia WYan ZZhao LBian XLiu CQi ZZhang STang Z(2023)Root canal treatment planning by automatic tooth and root canal segmentation in dental CBCT with deep multi-task feature learningMedical Image Analysis10.1016/j.media.2023.10275085(102750)Online publication date: Apr-2023
https://doi.org/10.1016/j.media.2023.102750
Show More Cited By

Index Terms

CBCT image segmentation of tooth-root canal based on improved level set algorithm
1. Information systems
  1. Information systems applications
    1. Process control systems

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CIPAE 2020: Proceedings of the 2020 International Conference on Computers, Information Processing and Advanced Education

October 2020

527 pages

ISBN:9781450387729

DOI:10.1145/3419635

Copyright © 2020 ACM.

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Association for Computing Machinery

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Publication History

Published: 16 October 2020

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CIPAE 2020

CIPAE 2020: 2020 International Conference on Computers, Information Processing and Advanced Education

October 16 - 18, 2020

ON, Ottawa, Canada

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CIPAE 2020 Paper Acceptance Rate 101 of 216 submissions, 47%;

Overall Acceptance Rate 101 of 216 submissions, 47%

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Cited By

Tan MCui ZZhong TFang YZhang YShen D(2024)A progressive framework for tooth and substructure segmentation from cone-beam CT imagesComputers in Biology and Medicine10.1016/j.compbiomed.2023.107839169:COnline publication date: 17-Apr-2024
https://dl.acm.org/doi/10.1016/j.compbiomed.2023.107839
Chen ZChen SHu F(2023)CTA-UNet: CNN-transformer architecture UNet for dental CBCT images segmentationPhysics in Medicine & Biology10.1088/1361-6560/acf02668:17(175042)Online publication date: 31-Aug-2023
https://doi.org/10.1088/1361-6560/acf026
Wang YXia WYan ZZhao LBian XLiu CQi ZZhang STang Z(2023)Root canal treatment planning by automatic tooth and root canal segmentation in dental CBCT with deep multi-task feature learningMedical Image Analysis10.1016/j.media.2023.10275085(102750)Online publication date: Apr-2023
https://doi.org/10.1016/j.media.2023.102750
Kakehbaraei SArvanaghi RSeyedarabi HEsmaeili FZenouz A(2023)3D tooth segmentation in cone-beam computed tomography images using distance transformBiomedical Signal Processing and Control10.1016/j.bspc.2022.10412279(104122)Online publication date: Jan-2023
https://doi.org/10.1016/j.bspc.2022.104122
Ma LHou XGong Z(2022)Image Segmentation Technology Based on Attention Mechanism and ENetComputational Intelligence and Neuroscience10.1155/2022/98737772022(1-8)Online publication date: 4-Aug-2022
https://doi.org/10.1155/2022/9873777
Deleat-Besson RLe CZhang WTurkestani NCevidanes LBianchi JRuellas AGurgel MMassaro CDel Castillo AIoshida MYatabe MBenavides ERios HSoki FNeiva GNajarian KGryak JStyner MAristizabal JRey DAlvarez MBert LSoroushmehr RPrieto J(2021)Merging and Annotating Teeth and Roots from Automated Segmentation of Multimodal ImagesMultimodal Learning for Clinical Decision Support10.1007/978-3-030-89847-2_8(81-92)Online publication date: 20-Oct-2021
https://doi.org/10.1007/978-3-030-89847-2_8

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