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rdf:type
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Description
| - This work deals with segmentation of magnetic resonance images. For better distinguishing between particular tissues, particular properties of tissues and their manifestation in different types of imaging are used. Specifically, T1 and T2 images are used. The segmentation is based on the approximation of more dimensional histograms. Since the noise distribution in MR images is close to Gaussian distribution for large signal-to-noise ratio, the approximation is done by Gaussian Mixture Model, where the number of components is determined using Bayesian Information Criterion and Elbow method.
- This work deals with segmentation of magnetic resonance images. For better distinguishing between particular tissues, particular properties of tissues and their manifestation in different types of imaging are used. Specifically, T1 and T2 images are used. The segmentation is based on the approximation of more dimensional histograms. Since the noise distribution in MR images is close to Gaussian distribution for large signal-to-noise ratio, the approximation is done by Gaussian Mixture Model, where the number of components is determined using Bayesian Information Criterion and Elbow method. (cs)
- Tato práce se zabývá segmentací MR obrazů. Pro lepší odlišení jednotlivých tkání jsou využity různé vlastnosti a projev tkání v různých typech zobrazení. Konkrétně jsou využity T1 a T2-vážené snímky. Segmentace je založena aproximaci vícerozměnrného histogramu. Protože rozložení šumu je v MR obrazech s velkým poměrem signál-šum přibližně Gaussovské, aproximace je provedena pomocí Gaussovského smíšeného modelu, kde počet komponent je určen pomocí Bayesovského informačního kritéria a metody lokte. (en)
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Title
| - Multi-parametric segmentation of MR images of the Brain
- Multi-parametric segmentation of MR images of the Brain (cs)
- Multi-parametrická segmentace MR snímků mozku (en)
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skos:prefLabel
| - Multi-parametric segmentation of MR images of the Brain
- Multi-parametric segmentation of MR images of the Brain (cs)
- Multi-parametrická segmentace MR snímků mozku (en)
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skos:notation
| - RIV/00216305:26220/13:PU103797!RIV15-MSM-26220___
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http://linked.open...avai/riv/aktivita
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http://linked.open...avai/riv/aktivity
| - I, P(ED0017/01/01), P(ED2.1.00/03.0072), P(GAP102/12/1104), S
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http://linked.open...vai/riv/dodaniDat
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http://linked.open...aciTvurceVysledku
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http://linked.open.../riv/druhVysledku
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http://linked.open...iv/duvernostUdaju
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http://linked.open...titaPredkladatele
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http://linked.open...dnocenehoVysledku
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http://linked.open...ai/riv/idVysledku
| - RIV/00216305:26220/13:PU103797
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http://linked.open...riv/jazykVysledku
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http://linked.open.../riv/klicovaSlova
| - GMM, segmentace obrazu, MRI, více-parametrická segmentace, klasifikace tkání (en)
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http://linked.open.../riv/klicoveSlovo
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http://linked.open...ontrolniKodProRIV
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http://linked.open...v/mistoKonaniAkce
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http://linked.open...i/riv/mistoVydani
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http://linked.open...i/riv/nazevZdroje
| - 9th International Conference on Measurement
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http://linked.open...in/vavai/riv/obor
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http://linked.open...ichTvurcuVysledku
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http://linked.open...cetTvurcuVysledku
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http://linked.open...vavai/riv/projekt
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http://linked.open...UplatneniVysledku
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http://linked.open...iv/tvurceVysledku
| - Bartušek, Karel
- Dvořák, Pavel
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http://linked.open...vavai/riv/typAkce
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http://linked.open.../riv/zahajeniAkce
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number of pages
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http://purl.org/ne...btex#hasPublisher
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https://schema.org/isbn
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http://localhost/t...ganizacniJednotka
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