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  • This paper describes a solution of CT arteriography vessel segmentation using a combination of methods for segmentation of image data. Computer tomography (CT) is one of the most useful approaches for investigating the arterial system and its pathologies. There are three ways for segmenting the vessels from the CT image - manually, fully automatically and with a user interaction. We considered the (semi)automatic approaches, because the manual way is too timeconsuming and humandependent. We used a combination of three segmentation techniques: thresholding, edge detection and region growing. Results of this method were consulted then with a medicine expert. None of these techniques can be used separately, but a combi nation of them brought very good results, which can be used in medicine.
  • This paper describes a solution of CT arteriography vessel segmentation using a combination of methods for segmentation of image data. Computer tomography (CT) is one of the most useful approaches for investigating the arterial system and its pathologies. There are three ways for segmenting the vessels from the CT image - manually, fully automatically and with a user interaction. We considered the (semi)automatic approaches, because the manual way is too timeconsuming and humandependent. We used a combination of three segmentation techniques: thresholding, edge detection and region growing. Results of this method were consulted then with a medicine expert. None of these techniques can be used separately, but a combi nation of them brought very good results, which can be used in medicine. (en)
Title
  • Segmentation of CT arteriography based on combination of segmentation methods
  • Segmentation of CT arteriography based on combination of segmentation methods (en)
skos:prefLabel
  • Segmentation of CT arteriography based on combination of segmentation methods
  • Segmentation of CT arteriography based on combination of segmentation methods (en)
skos:notation
  • RIV/49777513:23520/11:43898227!RIV12-MSM-23520___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • S
http://linked.open...iv/cisloPeriodika
  • 3
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
  • 228586
http://linked.open...ai/riv/idVysledku
  • RIV/49777513:23520/11:43898227
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • image processing, segmentation, vessel tree, thresholding, region growing, edge detection (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...odStatuVydavatele
  • RU - Ruská federace
http://linked.open...ontrolniKodProRIV
  • [D6E35571EDF5]
http://linked.open...i/riv/nazevZdroje
  • Pattern Recognition and Image Analysis
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...v/svazekPeriodika
  • 21
http://linked.open...iv/tvurceVysledku
  • Železný, Miloš
  • Jiřík, Miroslav
  • Pirner, Ivan
issn
  • 1054-6618
number of pages
http://bibframe.org/vocab/doi
  • 10.1134/S105466181102088X
http://localhost/t...ganizacniJednotka
  • 23520
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