Publication detail

Delaunay-Based Vector Segmentation of Volumetric Medical Images

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

ISBN

0302-9743

Periodical

Lecture Notes in Computer Science

Year of study

2007

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"
}