Prediction of facial deformation after complete denture prosthesis using BP neural network.
Identifieur interne : 000E14 ( Main/Exploration ); précédent : 000E13; suivant : 000E15Prediction of facial deformation after complete denture prosthesis using BP neural network.
Auteurs : Cheng Cheng [République populaire de Chine] ; Xiaosheng Cheng [République populaire de Chine] ; Ning Dai [République populaire de Chine] ; Xiaotong Jiang [République populaire de Chine] ; Yuchun Sun [République populaire de Chine] ; Weiwei Li [République populaire de Chine]Source :
- Computers in biology and medicine [ 1879-0534 ] ; 2015.
Descripteurs français
- KwdFr :
- MESH :
- anatomopathologie : Bouche édentée.
- imagerie diagnostique : Bouche édentée.
- Analyse de régression, Humains, Imagerie tridimensionnelle, Informatique médicale, Modèles théoriques, Prothèse dentaire complète, Réseaux neuronaux (ordinateur), Simulation numérique, Tomodensitométrie, Élasticité.
English descriptors
- KwdEn :
- MESH :
- diagnostic imaging : Mouth, Edentulous.
- pathology : Mouth, Edentulous.
- Computer Simulation, Denture, Complete, Elasticity, Humans, Imaging, Three-Dimensional, Medical Informatics, Models, Theoretical, Neural Networks (Computer), Regression Analysis, Tomography, X-Ray Computed.
Abstract
With the accelerated aging of world population, complete denture prosthesis plays an increasingly important role in mouth rehabilitation. In addition to recovering stomatognathic system function, restoring the appearance of a third of the area under the face has become a great challenge in complete denture prosthesis. This study analyzes the interactive relationship between the appearance of a third of the area under the face and complete denture, and proposes a new method to predict facial deformation after complete denture prosthesis. Firstly, to improve computational efficiency, the feature template is constructed to replace the deformed facial region. Secondly, a forecast model of elastic deformation is constructed using BP neural network and predicts elastic deformation amount because of the inhomogeneous, anisotropic and nonlinear material properties of soft tissue. Finally, a new feature template is calculated using deformation amount, and the deformation of preoperative model is simulated using Laplacian deformation technique. The average error rates of different hidden layer nodes in the neural network are analysed. Deformation and postoperative models are superimposed for match analysis. Experimental results show that this method can predict facial soft tissue deformation quickly and accurately.
DOI: 10.1016/j.compbiomed.2015.08.018
PubMed: 26386549
Affiliations:
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Electronic address: dai_ning@nuaa.edu.cn.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Mailbox 357, 29 Yudao Street, Qinhuai District, Nanjing 210016</wicri:regionArea><wicri:noRegion>Nanjing 210016</wicri:noRegion></affiliation></author><author><name sortKey="Jiang, Xiaotong" sort="Jiang, Xiaotong" uniqKey="Jiang X" first="Xiaotong" last="Jiang">Xiaotong Jiang</name><affiliation wicri:level="1"><nlm:affiliation>College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Mailbox 357, 29 Yudao Street, Qinhuai District, Nanjing 210016, PR China. 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Electronic address: liww@bjmu.edu.cn.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Research Centre of Engineering and Technology for Computerized Dentistry, Ministry of Health, Peking University School and Hospital of Stomatology, Beijing 100081</wicri:regionArea><placeName><settlement type="city">Pékin</settlement></placeName></affiliation></author></analytic><series><title level="j">Computers in biology and medicine</title><idno type="eISSN">1879-0534</idno><imprint><date when="2015" type="published">2015</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Computer Simulation</term><term>Denture, Complete</term><term>Elasticity</term><term>Humans</term><term>Imaging, Three-Dimensional</term><term>Medical Informatics</term><term>Models, Theoretical</term><term>Mouth, Edentulous (diagnostic imaging)</term><term>Mouth, Edentulous (pathology)</term><term>Neural Networks (Computer)</term><term>Regression Analysis</term><term>Tomography, X-Ray Computed</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Analyse de régression</term><term>Bouche édentée (anatomopathologie)</term><term>Bouche édentée (imagerie diagnostique)</term><term>Humains</term><term>Imagerie tridimensionnelle</term><term>Informatique médicale</term><term>Modèles théoriques</term><term>Prothèse dentaire complète</term><term>Réseaux neuronaux (ordinateur)</term><term>Simulation numérique</term><term>Tomodensitométrie</term><term>Élasticité</term></keywords><keywords scheme="MESH" qualifier="anatomopathologie" xml:lang="fr"><term>Bouche édentée</term></keywords><keywords scheme="MESH" qualifier="diagnostic imaging" xml:lang="en"><term>Mouth, Edentulous</term></keywords><keywords scheme="MESH" qualifier="imagerie diagnostique" xml:lang="fr"><term>Bouche édentée</term></keywords><keywords scheme="MESH" qualifier="pathology" xml:lang="en"><term>Mouth, Edentulous</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Computer Simulation</term><term>Denture, Complete</term><term>Elasticity</term><term>Humans</term><term>Imaging, Three-Dimensional</term><term>Medical Informatics</term><term>Models, Theoretical</term><term>Neural Networks (Computer)</term><term>Regression Analysis</term><term>Tomography, X-Ray Computed</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Analyse de régression</term><term>Humains</term><term>Imagerie tridimensionnelle</term><term>Informatique médicale</term><term>Modèles théoriques</term><term>Prothèse dentaire complète</term><term>Réseaux neuronaux (ordinateur)</term><term>Simulation numérique</term><term>Tomodensitométrie</term><term>Élasticité</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">With the accelerated aging of world population, complete denture prosthesis plays an increasingly important role in mouth rehabilitation. In addition to recovering stomatognathic system function, restoring the appearance of a third of the area under the face has become a great challenge in complete denture prosthesis. This study analyzes the interactive relationship between the appearance of a third of the area under the face and complete denture, and proposes a new method to predict facial deformation after complete denture prosthesis. Firstly, to improve computational efficiency, the feature template is constructed to replace the deformed facial region. Secondly, a forecast model of elastic deformation is constructed using BP neural network and predicts elastic deformation amount because of the inhomogeneous, anisotropic and nonlinear material properties of soft tissue. Finally, a new feature template is calculated using deformation amount, and the deformation of preoperative model is simulated using Laplacian deformation technique. The average error rates of different hidden layer nodes in the neural network are analysed. Deformation and postoperative models are superimposed for match analysis. Experimental results show that this method can predict facial soft tissue deformation quickly and accurately.</div></front></TEI><affiliations><list><country><li>République populaire de Chine</li></country><settlement><li>Pékin</li></settlement></list><tree><country name="République populaire de Chine"><noRegion><name sortKey="Cheng, Cheng" sort="Cheng, Cheng" uniqKey="Cheng C" first="Cheng" last="Cheng">Cheng Cheng</name></noRegion><name sortKey="Cheng, Xiaosheng" sort="Cheng, Xiaosheng" uniqKey="Cheng X" first="Xiaosheng" last="Cheng">Xiaosheng Cheng</name><name sortKey="Dai, Ning" sort="Dai, Ning" uniqKey="Dai N" first="Ning" last="Dai">Ning Dai</name><name sortKey="Jiang, Xiaotong" sort="Jiang, Xiaotong" uniqKey="Jiang X" first="Xiaotong" last="Jiang">Xiaotong Jiang</name><name sortKey="Li, Weiwei" sort="Li, Weiwei" uniqKey="Li W" first="Weiwei" last="Li">Weiwei Li</name><name sortKey="Sun, Yuchun" sort="Sun, Yuchun" uniqKey="Sun Y" first="Yuchun" last="Sun">Yuchun Sun</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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