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dc.rights.licenseCC-BY-NC-ND
dc.contributor.advisorVaxman, A.
dc.contributor.authorVanheste, S.
dc.date.accessioned2019-05-27T17:00:47Z
dc.date.available2019-05-27T17:00:47Z
dc.date.issued2019
dc.identifier.urihttps://studenttheses.uu.nl/handle/20.500.12932/32683
dc.description.abstractIn cooperation with the Utrecht Medical Center (UMC), I built a 3D browserbased MRI/CT e-learning system. I propose an improved way of defining correct target volumes in 3D MRI and CT scans: instead of user-defined, handcrafted target volumes in which the target contour of a specific anatomical structure has to be traced by hand for each 2D image slice, this method introduces automatic interpolation between user-provided contours. This is achieved with a new variant of the active contour method. As a result, only a subset of the slices have to be segmented manually. This improves on similar contour-based user-guided segmentation methods.
dc.description.sponsorshipUtrecht University
dc.format.extent18572430
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.titleUser-Guided Semi-Automatic Segmentation of Medical 3D Images
dc.type.contentMaster Thesis
dc.rights.accessrightsOpen Access
dc.subject.keywordsuser-guided segmentation;active contours;active contour;radiology e-learning;3D medical scans segmentation;
dc.subject.courseuuGame and Media Technology


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