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dc.contributor.authorTeatini, Andrea
dc.contributor.authorPelanis, Egidijus
dc.contributor.authorAghayan, Davit
dc.contributor.authorKumar, Rahul Prasanna
dc.contributor.authorPalomar, Rafael
dc.contributor.authorFretland, Åsmund Avdem
dc.contributor.authorEdwin, Bjørn
dc.contributor.authorElle, Ole Jacob
dc.date.accessioned2020-01-23T07:54:48Z
dc.date.available2020-01-23T07:54:48Z
dc.date.created2020-01-09T10:36:09Z
dc.date.issued2019
dc.identifier.citationScientific Reports. 2019, 9nb_NO
dc.identifier.issn2045-2322
dc.identifier.urihttp://hdl.handle.net/11250/2637556
dc.description.abstractConventional surgical navigation systems rely on preoperative imaging to provide guidance. In laparoscopic liver surgery, insufflation of the abdomen (pneumoperitoneum) can cause deformations on the liver, introducing inaccuracies in the correspondence between the preoperative images and the intraoperative reality. This study evaluates the improvements provided by intraoperative imaging for laparoscopic liver surgical navigation, when displayed as augmented reality (AR). Significant differences were found in terms of accuracy of the AR, in favor of intraoperative imaging. In addition, results showed an effect of user-induced error: image-to-patient registration based on annotations performed by clinicians caused 33% more inaccuracy as compared to image-to-patient registration algorithms that do not depend on user annotations. Hence, to achieve accurate surgical navigation for laparoscopic liver surgery, intraoperative imaging is recommendable to compensate for deformation. Moreover, user annotation errors may lead to inaccuracies in registration processes.nb_NO
dc.language.isoengnb_NO
dc.publisherNature Researchnb_NO
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleThe effect of intraoperative imaging on surgical navigation for laparoscopic liver resection surgerynb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionpublishedVersionnb_NO
dc.source.volume9nb_NO
dc.source.journalScientific Reportsnb_NO
dc.identifier.doi10.1038/s41598-019-54915-3
dc.identifier.cristin1769078
dc.description.localcodeOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.nb_NO
cristin.unitcode194,63,10,0
cristin.unitnameInstitutt for datateknologi og informatikk
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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