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DC poleHodnotaJazyk
dc.contributor.authorKortelainen, Juha M.
dc.contributor.authorAntila, Kari
dc.contributor.editorSkala, Václav
dc.date.accessioned2017-11-08T10:25:54Z
dc.date.available2017-11-08T10:25:54Z
dc.date.issued2014
dc.identifier.citationWSCG 2014: communication papers proceedings: 22nd International Conference in Central Europeon Computer Graphics, Visualization and Computer Visionin co-operation with EUROGRAPHICS Association, p. 285-292.en
dc.identifier.isbn978-80-86943-71-8
dc.identifier.uriwscg.zcu.cz/WSCG2014/!!_2014-WSCG-Communication.pdf
dc.identifier.urihttp://hdl.handle.net/11025/26425
dc.format8 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherVáclav Skala - UNION Agencycs
dc.relation.ispartofseriesWSCG 2014: communication papers proceedingsen
dc.rights@ Václav Skala - UNION Agencycs
dc.subjectdeformovatelný povrchcs
dc.subjectprostatacs
dc.subjectMRI segmentacecs
dc.titleSemi-automatic segmentation of prostate by directional search for edge boundariesen
dc.typekonferenční příspěvekcs
dc.typeconferenceObjecten
dc.rights.accessopenAccessen
dc.type.versionpublishedVersionen
dc.description.abstract-translatedSemi-automatic segmentation of the prostate boundary is presented for the pre-operational images of the MRIguided ultrasonic thermal therapy of the prostate cancer. The specific deformable surface method is based on firstly fitting an ellipsoid on the given manual landmark points, then modifying the shape of the initialization surface mesh by masking out the regions of the separately segmented bladder and rectum, and finally adapting the surface mesh by searching image for the edge boundaries in the direction of the surface normal. The suggested segmentation method combines information from two types of pre-operational MR-images showing different contrast for the tissue structure. Dice similarity coefficient (DSC) between the semi-automatic segmentation and the manual reference was on average 0.89 for a group of N=5 patients having the MRI guided ultrasound thermal treatment. The robustness of the surface fitting method was tested by simulating 30 randomized initialization sets of the landmark points for each patient, and the resulting standard deviation of DSC was 0.01.en
dc.subject.translateddeformable surfaceen
dc.subject.translatedprostateen
dc.subject.translatedMRI segmentationen
dc.type.statusPeer-revieweden
Vyskytuje se v kolekcích:WSCG 2014: Communication Papers Proceedings

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