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Statements

Subject Item
n2:RIV%2F00216305%3A26220%2F09%3APU79623%21RIV10-MSM-26220___
rdf:type
n6:Vysledek skos:Concept
dcterms:description
The paper describes the segmentation of NMR image of the human head in the region of temporomandibular joint. Images obtained by the tomograph used are of very low resolution and contrast, and processing them can prove to be difficult. There were found many methods for segmentation of small and noised parts of NMR images such as active contours, region-based or edge-based level set segmentation methods and very known the region growing method. An appropriate algorithm has been found, which consists of pre-processing the image by a smoothing filter, sharpening, and four-phase level set segmentation. This method segments the image on the basis of the intensity of regions and is thus suitable to be applied to the above NMR images, in which no sharp edges occur. The method also has some filtering capability. The paper describes the most popular segmentation methods in MRI processing and it is shown the result of the mentioned four-phase level set segmentation method. The future work will be aimed at testi The paper describes the segmentation of NMR image of the human head in the region of temporomandibular joint. Images obtained by the tomograph used are of very low resolution and contrast, and processing them can prove to be difficult. There were found many methods for segmentation of small and noised parts of NMR images such as active contours, region-based or edge-based level set segmentation methods and very known the region growing method. An appropriate algorithm has been found, which consists of pre-processing the image by a smoothing filter, sharpening, and four-phase level set segmentation. This method segments the image on the basis of the intensity of regions and is thus suitable to be applied to the above NMR images, in which no sharp edges occur. The method also has some filtering capability. The paper describes the most popular segmentation methods in MRI processing and it is shown the result of the mentioned four-phase level set segmentation method. The future work will be aimed at testi
dcterms:title
Segmentation methods for MRI processing Segmentation methods for MRI processing
skos:prefLabel
Segmentation methods for MRI processing Segmentation methods for MRI processing
skos:notation
RIV/00216305:26220/09:PU79623!RIV10-MSM-26220___
n3:aktivita
n7:Z n7:P
n3:aktivity
P(GA102/07/1086), Z(MSM0021630513)
n3:dodaniDat
n4:2010
n3:domaciTvurceVysledku
n22:5918367 n22:4095499 n22:1157000
n3:druhVysledku
n15:D
n3:duvernostUdaju
n20:S
n3:entitaPredkladatele
n10:predkladatel
n3:idSjednocenehoVysledku
340551
n3:idVysledku
RIV/00216305:26220/09:PU79623
n3:jazykVysledku
n12:eng
n3:klicovaSlova
level set segmentation, mandibular joint
n3:klicoveSlovo
n14:level%20set%20segmentation n14:mandibular%20joint
n3:kontrolniKodProRIV
[E3E55AE429B8]
n3:mistoKonaniAkce
Polsko
n3:mistoVydani
Polsko
n3:nazevZdroje
Recent Advances in Numerical Modelling
n3:obor
n11:JA
n3:pocetDomacichTvurcuVysledku
3
n3:pocetTvurcuVysledku
3
n3:projekt
n5:GA102%2F07%2F1086
n3:rokUplatneniVysledku
n4:2009
n3:tvurceVysledku
Gescheidtová, Eva Mikulka, Jan Bartušek, Karel
n3:typAkce
n19:WRD
n3:zahajeniAkce
2009-05-10+02:00
n3:zamer
n13:MSM0021630513
s:numberOfPages
4
n18:hasPublisher
Neuveden
n21:isbn
978-83-922095-8-4
n16:organizacniJednotka
26220