Delaunay-based Vector Segmentation of Volumetric Medical Images
Vektorová segmentace objemových medicínských dat založená na Delaunay triangulaci
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Image segmentation plays an important role in medical image analysis. Many segmentation algorithms exist. Most of them produce data which are more or less not suitable for further surface extraction and anatomical modeling of human tissues. In this thesis, a novel segmentation technique based on the 3D Delaunay triangulation is proposed. A modified variational tetrahedral meshing approach is used to adapt a tetrahedral mesh to the underlying CT volumetric data, so that image edges are well approximated in the mesh. In order to classify tetrahedra into regions/tissues whose characteristics are similar, three different clustering schemes are presented. Finally, several methods for improving quality of the mesh and its adaptation to the image structure are also discussed.
KeywordsMedical imaging, computed tomography, volumetric data, image segmentation, surface reconstruction, surgery planning, custom-made implant, Delaunay triangulation, variational tetrahedral meshing, sliver elimination, feature extraction, clustering.
Study brunchInformační technologie
Composition of Committee
Date of defence2011-01-05
Process of defence
Result of the defencepráce byla úspěšně obhájena
SourceŠPANĚL, M. Delaunay-based Vector Segmentation of Volumetric Medical Images [online]. Brno: Vysoké učení technické v Brně. Fakulta informačních technologií. 2011.
- 2011