Delaunay-based Vector Segmentation of Volumetric Medical Images

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Referee
Mark
P
Journal Title
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Vysoké učení technické v Brně. Fakulta informačních technologií
Abstract
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.
Description
Keywords
Medical imaging, computed tomography, volumetric data, image segmentation, surface reconstruction, surgery planning, custom-made implant, Delaunay triangulation, variational tetrahedral meshing, sliver elimination, feature extraction, clustering.
Citation
ŠPANĚL, M. Delaunay-based Vector Segmentation of Volumetric Medical Images [online]. Brno: Vysoké učení technické v Brně. Fakulta informačních technologií. 2011.
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Date of access to the full text
Language of document
en
Study field
Informační technologie
Comittee
Date of acceptance
2011-01-05
Defence
Result of defence
práce byla úspěšně obhájena
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Standardní licenční smlouva - přístup k plnému textu bez omezení
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URI
http://hdl.handle.net/11012/63258
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2011
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