PhD. Theses

Španěl, M.: Delaunay-based Vector Segmentation of Volumetric Medical Images, Brno, CZ, FIT VUT, 2011, p. 138

Publication language:

english

Original title:

Delaunay-based Vector Segmentation of Volumetric Medical Images

Title (cs):

Vektorová segmentace objemových medicínských dat založená na Delaunayho triangulaci

Pages:

138

Place:

Brno, CZ

Year:

2011

Publisher:

Faculty of Information Technology BUT

Files:

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.

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.

BibTeX:

@PHDTHESIS{
   author = {Michal Španěl},
   title = {Delaunay-based Vector Segmentation of Volumetric Medical
	Images},
   pages = {138},
   year = {2011},
   location = {Brno, CZ},
   publisher = {Faculty of Information Technology BUT},
   language = {english},
   url = {http://www.fit.vutbr.cz/research/view_pub.php?id=9452}
}

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