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ŠPANĚL, M. KRŠEK, P. ŠVUB, M. ŠTANCL, V. ŠILER, O.
Original Title
Delaunay-Based Vector Segmentation of Volumetric Medical Images
Type
conference paper
Language
English
Original Abstract
The image segmentation plays an important role in medical image processing. Many segmentation algorithms exist. Most of them produce raster data which is not suitable for 3D geometrical modeling of human tissues. In this paper, a vector segmentation algorithm based on 3D Delaunay triangulation is proposed. Tetrahedral mesh is used to divide volumetric CT/MR data into non-overlapping regions whose characteristics are similar. Novel methods for improving quality of the mesh and its adaptation to the 3D image structure are also presented.
Keywords
Medical image processing, CT/MRI data, vector image segmentation, 3D Delaunay triangulation, tetraheral mesh, isotropic meshing, classification.
Authors
ŠPANĚL, M.; KRŠEK, P.; ŠVUB, M.; ŠTANCL, V.; ŠILER, O.
RIV year
2007
Released
27. 8. 2007
Publisher
Springer Verlag
Location
Berlin Heidelberg
ISBN
3-540-74271-9
Book
Proceedings of the 12th International Conference on Computer Analysis of Images and Patterns, CAIP 2007
Edition
LNCS 4673
0302-9743
Periodical
Lecture Notes in Computer Science
Year of study
Number
08
State
Federal Republic of Germany
Pages from
261
Pages to
269
Pages count
8
BibTex
@inproceedings{BUT26059, author="Michal {Španěl} and Přemysl {Kršek} and Miroslav {Švub} and Vít {Štancl} and Ondřej {Šiler}", title="Delaunay-Based Vector Segmentation of Volumetric Medical Images", booktitle="Proceedings of the 12th International Conference on Computer Analysis of Images and Patterns, CAIP 2007", year="2007", series="LNCS 4673", journal="Lecture Notes in Computer Science", volume="2007", number="08", pages="261--269", publisher="Springer Verlag", address="Berlin Heidelberg", isbn="3-540-74271-9", issn="0302-9743" }