Please use this identifier to cite or link to this item: http://dx.doi.org/10.25673/98386
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dc.contributor.authorNiemann, Annika-
dc.contributor.authorVoß, Samuel-
dc.contributor.authorTulamo, Riikka-
dc.contributor.authorWeigand, Simon-
dc.contributor.authorPreim, Bernhard-
dc.contributor.authorBerg, Philipp-
dc.contributor.authorSaalfeld, Sylvia-
dc.date.accessioned2023-01-24T13:36:53Z-
dc.date.available2023-01-24T13:36:53Z-
dc.date.issued2021-
dc.date.submitted2021-
dc.identifier.urihttps://opendata.uni-halle.de//handle/1981185920/100342-
dc.identifier.urihttp://dx.doi.org/10.25673/98386-
dc.description.abstractPurpose For the evaluation and rupture risk assessment of intracranial aneurysms, clinical,morphological and hemodynamic parameters are analyzed. The reliability of intracranial hemodynamic simulations strongly depends on the underlying models. Due to the missing information about the intracranial vessel wall, the patient-specific wall thickness is often neglected as well as the specific physiological and pathological properties of the vessel wall. Methods In this work, we present a model for structural simulations with patient-specific wall thickness including different tissue types based on postmortem histologic image data. Images of histologic 2D slices from intracranial aneurysms were manually segmented in nine tissue classes. After virtual inflation, they were combined into 3D models. This approach yields multiple 3D models of the inner and outer wall and different tissue parts as a prerequisite for subsequent simulations. Result We presented a pipeline to generate 3D models of aneurysms with respect to the different tissue textures occurring in the wall. First experiments show that including the variance of the tissue in the structural simulation affect the simulation result. Especially at the interfaces between neighboring tissue classes, the larger influence of stiffer components on the stability equilibrium became obvious. Conclusion The presented approach enables the creation of a geometricmodel with differentiatedwall tissue. This information can be used for different applications, like hemodynamic simulations, to increase the modeling accuracy.eng
dc.description.sponsorshipProjekt DEAL 2021-
dc.language.isoeng-
dc.relation.ispartofhttp://link.springer.com/journal/11548-
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/-
dc.subjectIntracranial aneurysmseng
dc.subjectAneurysm walleng
dc.subjectHistologic imageseng
dc.subjectStructural simulationeng
dc.subject.ddc000-
dc.titleComplex wall modeling for hemodynamic simulations of intracranial aneurysms based on histologic imageseng
dc.typeArticle-
dc.identifier.urnurn:nbn:de:gbv:ma9:1-1981185920-1003427-
local.versionTypepublishedVersion-
local.bibliographicCitation.journaltitleInternational journal of computer assisted radiology and surgery-
local.bibliographicCitation.volume16-
local.bibliographicCitation.issue4-
local.bibliographicCitation.pagestart597-
local.bibliographicCitation.pageend607-
local.bibliographicCitation.publishernameSpringer-
local.bibliographicCitation.publisherplaceBerlin-
local.bibliographicCitation.doi10.1007/s11548-021-02334-z-
local.openaccesstrue-
dc.identifier.ppn177569612X-
local.bibliographicCitation.year2021-
cbs.sru.importDate2023-01-24T13:33:47Z-
local.bibliographicCitationEnthalten in International journal of computer assisted radiology and surgery - Berlin : Springer, 2006-
local.accessrights.dnbfree-
Appears in Collections:Fakultät für Informatik (OA)

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