dc.rights.license | CC-BY-NC-ND | |
dc.contributor.advisor | Vaxman, A. | |
dc.contributor.author | Vanheste, S. | |
dc.date.accessioned | 2019-05-27T17:00:47Z | |
dc.date.available | 2019-05-27T17:00:47Z | |
dc.date.issued | 2019 | |
dc.identifier.uri | https://studenttheses.uu.nl/handle/20.500.12932/32683 | |
dc.description.abstract | In 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.sponsorship | Utrecht University | |
dc.format.extent | 18572430 | |
dc.format.mimetype | application/pdf | |
dc.language.iso | en | |
dc.title | User-Guided Semi-Automatic Segmentation of Medical 3D Images | |
dc.type.content | Master Thesis | |
dc.rights.accessrights | Open Access | |
dc.subject.keywords | user-guided segmentation;active contours;active contour;radiology e-learning;3D medical scans segmentation; | |
dc.subject.courseuu | Game and Media Technology | |