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Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-25387
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dc.contributor.authorDupuy, Nicolas-
dc.contributor.authorJuchler, Norman-
dc.contributor.authorMorel, Sandrine-
dc.contributor.authorKwak, Brenda R.-
dc.contributor.authorHirsch, Sven-
dc.contributor.authorBijlenga, Philippe-
dc.date.accessioned2022-08-05T09:58:14Z-
dc.date.available2022-08-05T09:58:14Z-
dc.date.issued2022-
dc.identifier.isbn978-0-9562914-6-2de_CH
dc.identifier.issn2227-3085de_CH
dc.identifier.issn2227-9385de_CH
dc.identifier.urihttps://www.compbiomed.net/getfile.php?type=16/site_documents&id=CMBE%202022%20Proceedings%20volume1.pdfde_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/25387-
dc.description.abstractIntracranial aneurysm (IA) shape is proposed to be a predicting factor of rupture. In this study, using 3D-angiographies, surgical and histological images, we ranked 11 IAs according to different characteristics (homogeneity, aspect and thickness), and correlations between the different ranking systems were investigated. We showed positive correlations between IA morphology (normalized total Gaussian curvature, GLN) and wall aspect ranking, and between GLN and histology ranking. Correlations between increased GLN, inhomogeneity of IA wall aspect and thickness were shown. This exploratory study supports the GLN in its ability to quantify IA shape and to be used as an IA wall feature predictor.de_CH
dc.language.isoende_CH
dc.publisherComputational & Mathematical Biomedical Engineeringde_CH
dc.rightsLicence according to publishing contractde_CH
dc.subjectIntracranial aneurysmde_CH
dc.subjectMorphologyde_CH
dc.subjectWall aspectde_CH
dc.subjectWall thicknessde_CH
dc.subject.ddc005: Computerprogrammierung, Programme und Datende_CH
dc.subject.ddc616: Innere Medizin und Krankheitende_CH
dc.titleExploring intracranial aneurysm instability markers to improve disease modelingde_CH
dc.typeKonferenz: Paperde_CH
dcterms.typeTextde_CH
zhaw.departementLife Sciences und Facility Managementde_CH
zhaw.organisationalunitInstitut für Computational Life Sciences (ICLS)de_CH
dc.identifier.doi10.21256/zhaw-25387-
zhaw.conference.details7th International Conference on Computational and Mathematical Biomedical Engineering (CMBE22), Milan, Italy, 27-29 June 2022de_CH
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.pages.end17de_CH
zhaw.pages.start14de_CH
zhaw.parentwork.editorNithiarasu, Perumal-
zhaw.parentwork.editorVergara, Christian-
zhaw.publication.statuspublishedVersionde_CH
zhaw.volume1de_CH
zhaw.publication.reviewPeer review (Abstract)de_CH
zhaw.title.proceedingsCMBE 2022 : 7th International Conference on Computational & Mathematical Biomedical Engineeringde_CH
zhaw.webfeedBiomedical Simulationde_CH
zhaw.webfeedMedical Image Analysis & Data Modelingde_CH
zhaw.funding.zhawAneuXde_CH
zhaw.author.additionalNode_CH
zhaw.display.portraitYesde_CH
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