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dc.contributor.authorMastmeyer, Andre
dc.contributor.authorWilms, Matthias
dc.contributor.authorHandels, Heinz
dc.contributor.editorSkala, Václav
dc.date.accessioned2017-08-31T07:53:00Z
dc.date.available2017-08-31T07:53:00Z
dc.date.issued2017
dc.identifier.citationJournal of WSCG. 2017, vol. 25, no. 1, p. 1-9.en
dc.identifier.issn1213-6972 (print)
dc.identifier.issn1213-6980 (CD-ROM)
dc.identifier.issn1213-6964 (on-line)
dc.identifier.uriwscg.zcu.cz/WSCG2017/!_2017_Journal_WSCG-No-1.pdf
dc.identifier.urihttp://hdl.handle.net/11025/26275
dc.format9 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherVáclav Skala - UNION Agencycs
dc.relation.ispartofseriesJournal of WSCGen
dc.rights© Václav Skala - UNION Agencycs
dc.subjectvirtuální realitacs
dc.subjectinstruktáž punkce jatercs
dc.subject4D model pohybucs
dc.subjectregistrace mezi pacientycs
dc.titleInterpatient respiratory motion model transfer for virtual reality simulations of liver puncturesen
dc.typečlánekcs
dc.typearticleen
dc.rights.accessopenAccessen
dc.type.versionpublishedVersionen
dc.description.abstract-translatedCurrent virtual reality (VR) training simulators of liver punctures often rely on static 3D patient data and use an unrealistic (sinusoidal) periodic animation of the respiratory movement. Existing methods for the animation of breathing motion support simple mathematical or patient-specific, estimated breathing models. However with personalized breathing models for each new patient, a heavily dose relevant or expensive 4D data acquisition is mandatory for keyframe-based motion modeling. Given the reference 4D data, first a model building stage using linear regression motion field modeling takes place. Then the methodology shown here allows the transfer of existing reference respiratory motion models of a 4D reference patient to a new static 3D patient. This goal is achieved by using non-linear inter-patient registration to warp one personalized 4D motion field model to new 3D patient data. This cost- and dose-saving new method is shown here visually in a qualitative proof-of-concept study.en
dc.subject.translatedvirtual realityen
dc.subject.translatedliver puncture trainingen
dc.subject.translated4D motion modelsen
dc.subject.translatedinter-patient registrationen
dc.type.statusPeer-revieweden
Appears in Collections:Volume 25, Number 1 (2017)

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