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Statements

Subject Item
n2:RIV%2F00216305%3A26230%2F07%3APU73388%21RIV08-MSM-26230___
rdf:type
skos:Concept n18:Vysledek
dcterms: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. 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> 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.
dcterms:title
Delaunay-Based Vector Segmentation of Volumetric Medical Images Delaunay-Based Vector Segmentation of Volumetric Medical Images Vektorová segmentace objemových medicínských dat
skos:prefLabel
Vektorová segmentace objemových medicínských dat Delaunay-Based Vector Segmentation of Volumetric Medical Images Delaunay-Based Vector Segmentation of Volumetric Medical Images
skos:notation
RIV/00216305:26230/07:PU73388!RIV08-MSM-26230___
n6:strany
261-268
n6:aktivita
n14:Z
n6:aktivity
Z(MSM0021630528)
n6:dodaniDat
n10:2008
n6:domaciTvurceVysledku
n9:8547238 n9:5755093 n9:3148041 n9:6090419 n9:7822200
n6:druhVysledku
n20:D
n6:duvernostUdaju
n17:S
n6:entitaPredkladatele
n11:predkladatel
n6:idSjednocenehoVysledku
416108
n6:idVysledku
RIV/00216305:26230/07:PU73388
n6:jazykVysledku
n19:eng
n6:klicovaSlova
Medical image processing, CT/MRI data, vector image segmentation, 3D Delaunay triangulation, tetraheral mesh, isotropic meshing, classification.<br>
n6:klicoveSlovo
n7:3D%20Delaunay%20triangulation n7:isotropic%20meshing n7:tetraheral%20mesh n7:vector%20image%20segmentation n7:classification.%3Cbr%3E n7:CT%2FMRI%20data n7:Medical%20image%20processing
n6:kontrolniKodProRIV
[5DEC2E7A7E6A]
n6:mistoKonaniAkce
Vienna
n6:mistoVydani
Berlin Heidelberg
n6:nazevZdroje
Proceedings of the 12th International Conference on Computer Analysis of Images and Patterns, CAIP 2007
n6:obor
n13:JC
n6:pocetDomacichTvurcuVysledku
5
n6:pocetTvurcuVysledku
5
n6:rokUplatneniVysledku
n10:2007
n6:tvurceVysledku
Kršek, Přemysl Švub, Miroslav Štancl, Vít Španěl, Michal Šiler, Ondřej
n6:typAkce
n8:WRD
n6:zahajeniAkce
2007-08-27+02:00
n6:zamer
n12:MSM0021630528
s:numberOfPages
8
n16:hasPublisher
Springer-Verlag
n15:isbn
3-540-74271-9
n4:organizacniJednotka
26230