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Statements

Subject Item
n2:RIV%2F00216305%3A26220%2F14%3APU110573%21RIV15-MSM-26220___
rdf:type
n12:Vysledek skos:Concept
dcterms:description
Using magnetic resonance tomography to scan biological tissues is currently a very dynamic approach Based on various image parameters, the method enables us to analyze tissue properties, recognize healthy and pathological tissues, and diagnose the disease or indicate its progression. However, the acquired data must be correctly interpreted and visualized by means of a suitable software tool, such as 3DSlicer (http://www.slicer.org). This well-designed platform provides an interface between the user and the data available in the popular DICOM format, and it facilitates very simple 3D visualization of the MR-based data. One of the main advantages of the open-source software package is undoubtedly its ability to be extended with supplementary modules, for example the Matlab script. The paper describes the open-source environment with a focus on Slicer3D and introduces possible extension of this platform with a module for MR data processing via the three-dimensional, mutiparametric, SVM trainable segmenta Using magnetic resonance tomography to scan biological tissues is currently a very dynamic approach Based on various image parameters, the method enables us to analyze tissue properties, recognize healthy and pathological tissues, and diagnose the disease or indicate its progression. However, the acquired data must be correctly interpreted and visualized by means of a suitable software tool, such as 3DSlicer (http://www.slicer.org). This well-designed platform provides an interface between the user and the data available in the popular DICOM format, and it facilitates very simple 3D visualization of the MR-based data. One of the main advantages of the open-source software package is undoubtedly its ability to be extended with supplementary modules, for example the Matlab script. The paper describes the open-source environment with a focus on Slicer3D and introduces possible extension of this platform with a module for MR data processing via the three-dimensional, mutiparametric, SVM trainable segmenta
dcterms:title
Matlab Extension for 3DSlicer: A Robust MR Image Processing Tool Matlab Extension for 3DSlicer: A Robust MR Image Processing Tool
skos:prefLabel
Matlab Extension for 3DSlicer: A Robust MR Image Processing Tool Matlab Extension for 3DSlicer: A Robust MR Image Processing Tool
skos:notation
RIV/00216305:26220/14:PU110573!RIV15-MSM-26220___
n3:aktivita
n6:P
n3:aktivity
P(EE2.3.30.0039), P(GAP102/12/1104)
n3:dodaniDat
n11:2015
n3:domaciTvurceVysledku
n13:1157000
n3:druhVysledku
n15:D
n3:duvernostUdaju
n19:S
n3:entitaPredkladatele
n18:predkladatel
n3:idSjednocenehoVysledku
27673
n3:idVysledku
RIV/00216305:26220/14:PU110573
n3:jazykVysledku
n8:eng
n3:klicovaSlova
SVM, Matlab, 3D Slicer, MRI
n3:klicoveSlovo
n4:Matlab n4:3D%20Slicer n4:MRI n4:SVM
n3:kontrolniKodProRIV
[CD1585AA34EE]
n3:mistoKonaniAkce
Guangzhou
n3:mistoVydani
Guangzhou, Čína
n3:nazevZdroje
Proceedings of PIERS 2014 in Guangzhou
n3:obor
n14:JA
n3:pocetDomacichTvurcuVysledku
1
n3:pocetTvurcuVysledku
1
n3:projekt
n10:GAP102%2F12%2F1104 n10:EE2.3.30.0039
n3:rokUplatneniVysledku
n11:2014
n3:tvurceVysledku
Mikulka, Jan
n3:typAkce
n7:WRD
n3:zahajeniAkce
2014-08-25+02:00
s:numberOfPages
4
n16:hasPublisher
Neuveden
n20:isbn
978-1-934142-28-8
n21:organizacniJednotka
26220