Detail publikace

Delaunay-Based Vector Segmentation of Volumetric Medical Images

Originální název

Delaunay-Based Vector Segmentation of Volumetric Medical Images

Anglický název

Delaunay-Based Vector Segmentation of Volumetric Medical Images

Jazyk

en

Originální abstrakt

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.

Anglický abstrakt

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.

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",
  annote="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.",
  address="Springer Verlag",
  booktitle="Proceedings of the 12th International Conference on Computer Analysis of Images and Patterns, CAIP 2007",
  chapter="26059",
  edition="LNCS 4673",
  howpublished="print",
  institution="Springer Verlag",
  journal="Lecture Notes in Computer Science (IF 0,513)",
  number="08",
  year="2007",
  month="august",
  pages="261--269",
  publisher="Springer Verlag",
  type="conference paper"
}