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Description
  • 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.
  • 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. (en)
  • Při zpracování medicínských CT/MR dat hraje klíčovou roli segmentace obrazu. Naneštěstí, rastrový charakter většiny existujících metod není příliš vhodný pro tvorbu 3D polygonálních modelů jednotlivých tkání. Tento článek popisuje metodu přímé vektorové segmentace objemových medicínských dat, která vychází z 3D Delaunay triangulace. Tetrahedrální síť je využita pro efektivní dělení prostoru na vektorové elementy (tetrahedry), které následně klasifikujeme a spojujeme ve větší regiony.<br> (cs)
Title
  • Delaunay-Based Vector Segmentation of Volumetric Medical Images
  • Delaunay-Based Vector Segmentation of Volumetric Medical Images (en)
  • Vektorová segmentace objemových medicínských dat (cs)
skos:prefLabel
  • Delaunay-Based Vector Segmentation of Volumetric Medical Images
  • Delaunay-Based Vector Segmentation of Volumetric Medical Images (en)
  • Vektorová segmentace objemových medicínských dat (cs)
skos:notation
  • RIV/00216305:26230/07:PU73388!RIV08-MSM-26230___
http://linked.open.../vavai/riv/strany
  • 261-268
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • Z(MSM0021630528)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 416108
http://linked.open...ai/riv/idVysledku
  • RIV/00216305:26230/07:PU73388
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Medical image processing, CT/MRI data, vector image segmentation, 3D Delaunay triangulation, tetraheral mesh, isotropic meshing, classification.<br> (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [5DEC2E7A7E6A]
http://linked.open...v/mistoKonaniAkce
  • Vienna
http://linked.open...i/riv/mistoVydani
  • Berlin Heidelberg
http://linked.open...i/riv/nazevZdroje
  • Proceedings of the 12th International Conference on Computer Analysis of Images and Patterns, CAIP 2007
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Španěl, Michal
  • Štancl, Vít
  • Kršek, Přemysl
  • Šiler, Ondřej
  • Švub, Miroslav
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
http://linked.open...n/vavai/riv/zamer
number of pages
http://purl.org/ne...btex#hasPublisher
  • Springer-Verlag
https://schema.org/isbn
  • 3-540-74271-9
http://localhost/t...ganizacniJednotka
  • 26230
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