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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">An Automatic and Robust Algorithm of Reestablishment of Digital Dental Occlusion</title><author><name sortKey="Chang, Yu Bing" sort="Chang, Yu Bing" uniqKey="Chang Y" first="Yu-Bing" last="Chang">Yu-Bing Chang</name></author><author><name sortKey="Xia, James J" sort="Xia, James J" uniqKey="Xia J" first="James J." last="Xia">James J. Xia</name></author><author><name sortKey="Gateno, Jaime" sort="Gateno, Jaime" uniqKey="Gateno J" first="Jaime" last="Gateno">Jaime Gateno</name></author><author><name sortKey="Xiong, Zixiang" sort="Xiong, Zixiang" uniqKey="Xiong Z" first="Zixiang" last="Xiong">Zixiang Xiong</name></author><author><name sortKey="Zhou, Xiaobo" sort="Zhou, Xiaobo" uniqKey="Zhou X" first="Xiaobo" last="Zhou">Xiaobo Zhou</name></author><author><name sortKey="Wong, Stephen T C" sort="Wong, Stephen T C" uniqKey="Wong S" first="Stephen T. C." last="Wong">Stephen T. C. Wong</name></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">20529735</idno><idno type="pmc">5668907</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5668907</idno><idno type="RBID">PMC:5668907</idno><idno type="doi">10.1109/TMI.2010.2049526</idno><date when="2010">2010</date><idno type="wicri:Area/Pmc/Corpus">002730</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">002730</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">An Automatic and Robust Algorithm of Reestablishment of Digital Dental Occlusion</title><author><name sortKey="Chang, Yu Bing" sort="Chang, Yu Bing" uniqKey="Chang Y" first="Yu-Bing" last="Chang">Yu-Bing Chang</name></author><author><name sortKey="Xia, James J" sort="Xia, James J" uniqKey="Xia J" first="James J." last="Xia">James J. Xia</name></author><author><name sortKey="Gateno, Jaime" sort="Gateno, Jaime" uniqKey="Gateno J" first="Jaime" last="Gateno">Jaime Gateno</name></author><author><name sortKey="Xiong, Zixiang" sort="Xiong, Zixiang" uniqKey="Xiong Z" first="Zixiang" last="Xiong">Zixiang Xiong</name></author><author><name sortKey="Zhou, Xiaobo" sort="Zhou, Xiaobo" uniqKey="Zhou X" first="Xiaobo" last="Zhou">Xiaobo Zhou</name></author><author><name sortKey="Wong, Stephen T C" sort="Wong, Stephen T C" uniqKey="Wong S" first="Stephen T. C." last="Wong">Stephen T. C. Wong</name></author></analytic><series><title level="j">IEEE transactions on medical imaging</title><idno type="ISSN">0278-0062</idno><idno type="eISSN">1558-254X</idno><imprint><date when="2010">2010</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p id="P1">In the field of craniomaxillofacial (CMF) surgery, surgical planning can be performed on composite 3-D models that are generated by merging a computerized tomography scan with digital dental models. Digital dental models can be generated by scanning the surfaces of plaster dental models or dental impressions with a high-resolution laser scanner. During the planning process, one of the essential steps is to reestablish the dental occlusion. Unfortunately, this task is time-consuming and often inaccurate. This paper presents a new approach to automatically and efficiently reestablish dental occlusion. It includes two steps. The first step is to initially position the models based on dental curves and a point matching technique. The second step is to reposition the models to the final desired occlusion based on iterative surface-based minimum distance mapping with collision constraints. With linearization of rotation matrix, the alignment is modeled by solving quadratic programming. The simulation was completed on 12 sets of digital dental models. Two sets of dental models were partially edentulous, and another two sets have first premolar extractions for orthodontic treatment. Two validation methods were applied to the articulated models. The results show that using our method, the dental models can be successfully articulated with a small degree of deviations from the occlusion achieved with the gold-standard method.</p></div></front></TEI><pmc article-type="research-article"><pmc-comment>The publisher of this article does not allow downloading of the full text in XML form.</pmc-comment>
<pmc-dir>properties manuscript</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-journal-id">8310780</journal-id><journal-id journal-id-type="pubmed-jr-id">20511</journal-id><journal-id journal-id-type="nlm-ta">IEEE Trans Med Imaging</journal-id><journal-id journal-id-type="iso-abbrev">IEEE Trans Med Imaging</journal-id><journal-title-group><journal-title>IEEE transactions on medical imaging</journal-title></journal-title-group><issn pub-type="ppub">0278-0062</issn><issn pub-type="epub">1558-254X</issn></journal-meta><article-meta><article-id pub-id-type="pmid">20529735</article-id><article-id pub-id-type="pmc">5668907</article-id><article-id pub-id-type="doi">10.1109/TMI.2010.2049526</article-id><article-id pub-id-type="manuscript">NIHMS915096</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title-group><article-title>An Automatic and Robust Algorithm of Reestablishment of Digital Dental Occlusion</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Chang</surname><given-names>Yu-Bing</given-names></name><aff id="A1">Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77841 USA</aff></contrib><contrib contrib-type="author"><name><surname>Xia</surname><given-names>James J.</given-names></name><aff id="A2">Department of Oral and Maxillofacial Surgery, The Methodist Hospital Research Institute, and Department of Surgery (Oral and Maxillofacial Surgery), Weil Medical College of Cornell University, Houston, TX 77030 USA and also with Departments of Pediatric Surgery and Orthodontics, University of Texas Health Science Center, Houston, TX 77030 USA</aff></contrib><contrib contrib-type="author"><name><surname>Gateno</surname><given-names>Jaime</given-names></name><aff id="A3">Department of Oral and Maxillofacial Surgery, the Methodist Hospital Research Institute, and Department of Surgery (Oral and Maxillofacial Surgery), Weil Medical College of Cornell University, Houston, TX 77030 USA</aff></contrib><contrib contrib-type="author"><name><surname>Xiong</surname><given-names>Zixiang</given-names></name><role>Fellow, IEEE</role><aff id="A4">Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77841 USA</aff></contrib><contrib contrib-type="author"><name><surname>Zhou</surname><given-names>Xiaobo</given-names></name><xref rid="FN1" ref-type="author-notes">*</xref><aff id="A5">Center for Biotechnology and Informatics, The Methodist Hospital Research Institute and Department of Radiology, The Methodist Hospital, Weill Medical College of Cornell University, Houston, TX 77030 USA</aff></contrib><contrib contrib-type="author"><name><surname>Wong</surname><given-names>Stephen T. C.</given-names></name><aff id="A6">Center for Biotechnology and Informatics, The Methodist Hospital Research Institute and Department of Radiology, The Methodist Hospital, Weill Medical College of Cornell University, Houston, TX 77030 USA</aff></contrib></contrib-group><author-notes><corresp id="FN1"><label>*</label>Corresponding author: <email>xzhou@tmhs.org</email></corresp></author-notes><pub-date pub-type="nihms-submitted"><day>25</day><month>10</month><year>2017</year></pub-date><pub-date pub-type="epub"><day>07</day><month>6</month><year>2010</year></pub-date><pub-date pub-type="ppub"><month>9</month><year>2010</year></pub-date><pub-date pub-type="pmc-release"><day>03</day><month>11</month><year>2017</year></pub-date><volume>29</volume><issue>9</issue><fpage>1652</fpage><lpage>1663</lpage><pmc-comment>elocation-id from pubmed: 10.1109/TMI.2010.2049526</pmc-comment>
<abstract><p id="P1">In the field of craniomaxillofacial (CMF) surgery, surgical planning can be performed on composite 3-D models that are generated by merging a computerized tomography scan with digital dental models. Digital dental models can be generated by scanning the surfaces of plaster dental models or dental impressions with a high-resolution laser scanner. During the planning process, one of the essential steps is to reestablish the dental occlusion. Unfortunately, this task is time-consuming and often inaccurate. This paper presents a new approach to automatically and efficiently reestablish dental occlusion. It includes two steps. The first step is to initially position the models based on dental curves and a point matching technique. The second step is to reposition the models to the final desired occlusion based on iterative surface-based minimum distance mapping with collision constraints. With linearization of rotation matrix, the alignment is modeled by solving quadratic programming. The simulation was completed on 12 sets of digital dental models. Two sets of dental models were partially edentulous, and another two sets have first premolar extractions for orthodontic treatment. Two validation methods were applied to the articulated models. The results show that using our method, the dental models can be successfully articulated with a small degree of deviations from the occlusion achieved with the gold-standard method.</p></abstract><kwd-group><title>Index Terms</title><kwd>Centric occlusion</kwd><kwd>craniomaxillofacial (CMF) surgeries</kwd><kwd>dental alignment</kwd><kwd>dental occlusion</kwd><kwd>digital dental articulation</kwd></kwd-group></article-meta></front></pmc></record>Pour manipuler ce document sous Unix (Dilib)
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