Evaluation of the potential of automatic segmentation of the mandibular canal using cone-beam computed tomography.
Identifieur interne : 000798 ( Main/Exploration ); précédent : 000797; suivant : 000799Evaluation of the potential of automatic segmentation of the mandibular canal using cone-beam computed tomography.
Auteurs : Nicolaas Lucius Gerlach [Pays-Bas] ; Gerrit Jacobus Meijer [Pays-Bas] ; Dirk-Jan Kroon [Pays-Bas] ; Ewald Maria Bronkhorst [Pays-Bas] ; Stefaan Jozef Bergé [Pays-Bas] ; Thomas Jan Jaap Maal [Pays-Bas]Source :
- The British journal of oral & maxillofacial surgery [ 1532-1940 ] ; 2014.
Descripteurs français
- KwdFr :
- Agents colorants, Anatomie en coupes transversales, Arcade dentaire (anatomie et histologie), Arcade dentaire (imagerie diagnostique), Bleu de méthylène, Cadavre, Denture, Humains, Magenta I, Mandibule (anatomie et histologie), Mandibule (imagerie diagnostique), Molaire (anatomie et histologie), Molaire (imagerie diagnostique), Mâchoire édentée (anatomopathologie), Mâchoire édentée (imagerie diagnostique), Prémolaire (anatomie et histologie), Prémolaire (imagerie diagnostique), Systèmes experts, Tomodensitométrie à faisceau conique (normes), Traitement d'image par ordinateur (normes), Valeurs de référence, Validation de logiciel.
- MESH :
- anatomie et histologie : Arcade dentaire, Mandibule, Molaire, Prémolaire.
- anatomopathologie : Mâchoire édentée.
- imagerie diagnostique : Arcade dentaire, Mandibule, Molaire, Mâchoire édentée, Prémolaire.
- normes : Tomodensitométrie à faisceau conique, Traitement d'image par ordinateur.
- Agents colorants, Anatomie en coupes transversales, Bleu de méthylène, Cadavre, Denture, Humains, Magenta I, Systèmes experts, Valeurs de référence, Validation de logiciel.
English descriptors
- KwdEn :
- Anatomy, Cross-Sectional, Bicuspid (anatomy & histology), Bicuspid (diagnostic imaging), Cadaver, Coloring Agents, Cone-Beam Computed Tomography (standards), Dental Arch (anatomy & histology), Dental Arch (diagnostic imaging), Dentition, Expert Systems, Humans, Image Processing, Computer-Assisted (standards), Jaw, Edentulous (diagnostic imaging), Jaw, Edentulous (pathology), Mandible (anatomy & histology), Mandible (diagnostic imaging), Methylene Blue, Molar (anatomy & histology), Molar (diagnostic imaging), Reference Values, Rosaniline Dyes, Software Validation.
- MESH :
- chemical : Coloring Agents, Methylene Blue, Rosaniline Dyes.
- anatomy & histology : Bicuspid, Dental Arch, Mandible, Molar.
- diagnostic imaging : Bicuspid, Dental Arch, Jaw, Edentulous, Mandible, Molar.
- pathology : Jaw, Edentulous.
- standards : Cone-Beam Computed Tomography, Image Processing, Computer-Assisted.
- Anatomy, Cross-Sectional, Cadaver, Dentition, Expert Systems, Humans, Reference Values, Software Validation.
Abstract
We aimed to investigate the effectiveness of software for automatically tracing the mandibular canal on data from cone-beam computed tomography (CT). After the data had been collected from one dentate and one edentate fresh cadaver head, both a trained Active Shape Model (ASM) and an Active Appearance Model (AAM) were used to automatically segment the canals from the mandibular to the mental foramen. Semiautomatic segmentation was also evaluated by providing the models with manual annotations of the foramina. To find out if the tracings were in accordance with the actual anatomy, we compared the position of the automatic mandibular canal segmentations, as displayed on cross-sectional cone-beam CT views, with histological sections of exactly the same region. The significance of differences between results were analysed with the help of Fisher's exact test and Pearson's correlation coefficient. When tracings based on AAM and ASM were used, differences between cone-beam CT and histological measurements varied up to 3.45mm and 4.44mm, respectively. Manual marking of the mandibular and mental foramina did not improve the results, and there were no significant differences (p=0.097) among the methods. The accuracy of automatic segmentation of the mandibular canal by the AAM and ASM methods is inadequate for use in clinical practice.
DOI: 10.1016/j.bjoms.2014.07.253
PubMed: 25156043
Affiliations:
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Le document en format XML
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<term>Bicuspid (diagnostic imaging)</term>
<term>Cadaver</term>
<term>Coloring Agents</term>
<term>Cone-Beam Computed Tomography (standards)</term>
<term>Dental Arch (anatomy & histology)</term>
<term>Dental Arch (diagnostic imaging)</term>
<term>Dentition</term>
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<term>Jaw, Edentulous (pathology)</term>
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<term>Mandible (diagnostic imaging)</term>
<term>Methylene Blue</term>
<term>Molar (anatomy & histology)</term>
<term>Molar (diagnostic imaging)</term>
<term>Reference Values</term>
<term>Rosaniline Dyes</term>
<term>Software Validation</term>
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<keywords scheme="KwdFr" xml:lang="fr"><term>Agents colorants</term>
<term>Anatomie en coupes transversales</term>
<term>Arcade dentaire (anatomie et histologie)</term>
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<term>Bleu de méthylène</term>
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<front><div type="abstract" xml:lang="en">We aimed to investigate the effectiveness of software for automatically tracing the mandibular canal on data from cone-beam computed tomography (CT). After the data had been collected from one dentate and one edentate fresh cadaver head, both a trained Active Shape Model (ASM) and an Active Appearance Model (AAM) were used to automatically segment the canals from the mandibular to the mental foramen. Semiautomatic segmentation was also evaluated by providing the models with manual annotations of the foramina. To find out if the tracings were in accordance with the actual anatomy, we compared the position of the automatic mandibular canal segmentations, as displayed on cross-sectional cone-beam CT views, with histological sections of exactly the same region. The significance of differences between results were analysed with the help of Fisher's exact test and Pearson's correlation coefficient. When tracings based on AAM and ASM were used, differences between cone-beam CT and histological measurements varied up to 3.45mm and 4.44mm, respectively. Manual marking of the mandibular and mental foramina did not improve the results, and there were no significant differences (p=0.097) among the methods. The accuracy of automatic segmentation of the mandibular canal by the AAM and ASM methods is inadequate for use in clinical practice.</div>
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