Automatic Tooth Segmentation of Dental Mesh Based on Harmonic Fields
An important preprocess in computer-aided orthodontics is to segment teeth from the dental models accurately, which should involve manual interactions as few as possible. But fully automatic partition of all teeth is not a trivial task, since teeth occur in different shapes and their arrangements va...
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Series: | BioMed Research International |
Online Access: | http://dx.doi.org/10.1155/2015/187173 |
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doaj-0fea90e2399b49b79e1d277bc3b3e4c32020-11-24T23:26:31ZengHindawi LimitedBioMed Research International2314-61332314-61412015-01-01201510.1155/2015/187173187173Automatic Tooth Segmentation of Dental Mesh Based on Harmonic FieldsSheng-hui Liao0Shi-jian Liu1Bei-ji Zou2Xi Ding3Ye Liang4Jun-hui Huang5School of Information Science and Engineering, Central South University, Changsha 410083, ChinaSchool of Information Science and Engineering, Central South University, Changsha 410083, ChinaSchool of Information Science and Engineering, Central South University, Changsha 410083, ChinaDepartment of Stomatology, First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, ChinaDepartment of Stomatology, Xiangya Hospital of Central South University, Changsha 410008, ChinaXiangya Stomatological Hospital of Central South University, Changsha 410008, ChinaAn important preprocess in computer-aided orthodontics is to segment teeth from the dental models accurately, which should involve manual interactions as few as possible. But fully automatic partition of all teeth is not a trivial task, since teeth occur in different shapes and their arrangements vary substantially from one individual to another. The difficulty is exacerbated when severe teeth malocclusion and crowding problems occur, which is a common occurrence in clinical cases. Most published methods in this area either are inaccurate or require lots of manual interactions. Motivated by the state-of-the-art general mesh segmentation methods that adopted the theory of harmonic field to detect partition boundaries, this paper proposes a novel, dental-targeted segmentation framework for dental meshes. With a specially designed weighting scheme and a strategy of a priori knowledge to guide the assignment of harmonic constraints, this method can identify teeth partition boundaries effectively. Extensive experiments and quantitative analysis demonstrate that the proposed method is able to partition high-quality teeth automatically with robustness and efficiency.http://dx.doi.org/10.1155/2015/187173 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Sheng-hui Liao Shi-jian Liu Bei-ji Zou Xi Ding Ye Liang Jun-hui Huang |
spellingShingle |
Sheng-hui Liao Shi-jian Liu Bei-ji Zou Xi Ding Ye Liang Jun-hui Huang Automatic Tooth Segmentation of Dental Mesh Based on Harmonic Fields BioMed Research International |
author_facet |
Sheng-hui Liao Shi-jian Liu Bei-ji Zou Xi Ding Ye Liang Jun-hui Huang |
author_sort |
Sheng-hui Liao |
title |
Automatic Tooth Segmentation of Dental Mesh Based on Harmonic Fields |
title_short |
Automatic Tooth Segmentation of Dental Mesh Based on Harmonic Fields |
title_full |
Automatic Tooth Segmentation of Dental Mesh Based on Harmonic Fields |
title_fullStr |
Automatic Tooth Segmentation of Dental Mesh Based on Harmonic Fields |
title_full_unstemmed |
Automatic Tooth Segmentation of Dental Mesh Based on Harmonic Fields |
title_sort |
automatic tooth segmentation of dental mesh based on harmonic fields |
publisher |
Hindawi Limited |
series |
BioMed Research International |
issn |
2314-6133 2314-6141 |
publishDate |
2015-01-01 |
description |
An important preprocess in computer-aided orthodontics is to segment teeth from the dental models accurately, which should involve manual interactions as few as possible. But fully automatic partition of all teeth is not a trivial task, since teeth occur in different shapes and their arrangements vary substantially from one individual to another. The difficulty is exacerbated when severe teeth malocclusion and crowding problems occur, which is a common occurrence in clinical cases. Most published methods in this area either are inaccurate or require lots of manual interactions. Motivated by the state-of-the-art general mesh segmentation methods that adopted the theory of harmonic field to detect partition boundaries, this paper proposes a novel, dental-targeted segmentation framework for dental meshes. With a specially designed weighting scheme and a strategy of a priori knowledge to guide the assignment of harmonic constraints, this method can identify teeth partition boundaries effectively. Extensive experiments and quantitative analysis demonstrate that the proposed method is able to partition high-quality teeth automatically with robustness and efficiency. |
url |
http://dx.doi.org/10.1155/2015/187173 |
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