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EMBC44109.2020.9176729.pdf3.43 MBAdobe PDF見る/開く
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dc.contributor.authorMaekawa, Hinakoen
dc.contributor.authorNakao, Megumien
dc.contributor.authorMineura, Katsutakaen
dc.contributor.authorChen-Yoshikawa, Toyofumi F.en
dc.contributor.authorMatsuda, Tetsuyaen
dc.contributor.alternative前川, 日南子ja
dc.contributor.alternative中尾, 恵ja
dc.contributor.alternative峯浦, 一貴ja
dc.contributor.alternative松田, 哲也ja
dc.date.accessioned2021-10-11T02:27:39Z-
dc.date.available2021-10-11T02:27:39Z-
dc.date.issued2020-
dc.identifier.isbn9781728119908-
dc.identifier.urihttp://hdl.handle.net/2433/265388-
dc.description[2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 20-24 July 2020, Montreal, QC, Canada]en
dc.description.abstractBecause the lung deforms during surgery because of pneumothorax, it is important to be able to track the location of a tumor. Deformation of the whole lung can be estimated using intraoperative cone-beam CT (CBCT) images. In this study, we used deformable mesh registration methods for paired CBCT images in the inflated and deflated states, and analyzed their deformation. We proposed a deformable mesh registration framework for deformations of partial organ shapes involving large deformation and rotation. Experimental results showed that the proposed methods reduced errors in point-to-point correspondence. As a result of registration using surgical clips placed on the lung surface during imaging, it was confirmed that an average error of 3.9 mm occurred in eight cases. The result of analysis showed that both tissue rotation and contraction had large effects on displacement.en
dc.language.isoeng-
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en
dc.rights© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en
dc.rightsThis is not the published version. Please cite only the published version. この論文は出版社版でありません。引用の際には出版社版をご確認ご利用ください。en
dc.subjectLungen
dc.subjectStrainen
dc.subjectShapeen
dc.subjectSurgeryen
dc.subjectComputed tomographyen
dc.subjectTumorsen
dc.titleModel-based registration for pneumothorax deformation analysis using intraoperative cone-beam CT imagesen
dc.typeconference paper-
dc.type.niitypeConference Paper-
dc.identifier.jtitle2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)en
dc.identifier.spage5818-
dc.identifier.epage5821-
dc.relation.doi10.1109/EMBC44109.2020.9176729-
dc.textversionauthor-
dc.identifier.artnum9176729-
dc.identifier.pmid33019297-
dcterms.accessRightsopen access-
datacite.awardNumber18K19918-
datacite.awardNumber.urihttps://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-18K19918/-
jpcoar.funderName日本学術振興会ja
jpcoar.awardTitle圧縮センシングを応用した治療時生体臓器の高次状態復元ja
出現コレクション:学術雑誌掲載論文等

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