About: Automatic Human Body Segmentation Using Mean-Shift Clustering As Assistance in The Hyperthermia Treatment Planning     Goto   Sponge   NotDistinct   Permalink

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Description
  • The article deals the human body segmentation technique which supports hyperthermia oncology treatment planning. According to the inner structure of the tumor the applicator needs to be placed in the right direction. We used the automatical segmentation using mean-shift clustering algorithm in comparison with the segmented image data evaluated by the medical expert. The data was obtained with the commercial segmentation software 3D-DOCTOR. The quality of the segmentation can be essential for not only for treatment planning but can also provide the feedback in clinician decision making.
  • The article deals the human body segmentation technique which supports hyperthermia oncology treatment planning. According to the inner structure of the tumor the applicator needs to be placed in the right direction. We used the automatical segmentation using mean-shift clustering algorithm in comparison with the segmented image data evaluated by the medical expert. The data was obtained with the commercial segmentation software 3D-DOCTOR. The quality of the segmentation can be essential for not only for treatment planning but can also provide the feedback in clinician decision making. (en)
Title
  • Automatic Human Body Segmentation Using Mean-Shift Clustering As Assistance in The Hyperthermia Treatment Planning
  • Automatic Human Body Segmentation Using Mean-Shift Clustering As Assistance in The Hyperthermia Treatment Planning (en)
skos:prefLabel
  • Automatic Human Body Segmentation Using Mean-Shift Clustering As Assistance in The Hyperthermia Treatment Planning
  • Automatic Human Body Segmentation Using Mean-Shift Clustering As Assistance in The Hyperthermia Treatment Planning (en)
skos:notation
  • RIV/68407700:21230/09:00159186!RIV10-MSM-21230___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(2C06031), P(GD102/08/H008), P(GD102/08/H081), Z(MSM0021620806), Z(MSM6840770012)
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
  • 304475
http://linked.open...ai/riv/idVysledku
  • RIV/68407700:21230/09:00159186
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • MRI segmentation; mean-shift algorithm; medical expert evaluation. (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [130798DCD48A]
http://linked.open...v/mistoKonaniAkce
  • Praha
http://linked.open...i/riv/mistoVydani
  • Praha
http://linked.open...i/riv/nazevZdroje
  • Technical Computing Prague 2009
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Rusz, Jan
  • Vorlíček, Jaroslav
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
  • Humusoft
https://schema.org/isbn
  • 978-80-7080-733-0
http://localhost/t...ganizacniJednotka
  • 21230
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