Segmentation of MRI data by means of nonlinear diffusion

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F13%3A00210905" target="_blank" >RIV/68407700:21340/13:00210905 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00023001:_____/13:00058781

Výsledek na webu

<a href="http://www.kybernetika.cz/content/2013/2/301/paper.pdf" target="_blank" >http://www.kybernetika.cz/content/2013/2/301/paper.pdf</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Segmentation of MRI data by means of nonlinear diffusion

Popis výsledku v původním jazyce

The article focuses on the application of the segmentation algorithm based on the numerical solution of the Allen-Cahn non-linear diffusion partial differential equation. This equation is related to the motion of curves by mean curvature. It exhibits several suitable mathematical properties including stable solution profile. This allows the user to follow accurately the position of the segmentation curve by bringing it quickly to the vicinity of the segmented object and by approaching the details of thesegmentation curve. The purpose of the article is to indicate how the algorithm parameters are set up and to show how the algorithm behaves when applied to the particular class of medical data. In detail we describe the algorithm parameters influencingthe segmentation procedure. The left ventricle volume estimated by the segmentation of scanned slices is evaluated through the cardiac cycle. Consequently, the ejection fraction is evaluated. The described approach allows the user to proc

Název v anglickém jazyce

Segmentation of MRI data by means of nonlinear diffusion

Popis výsledku anglicky

The article focuses on the application of the segmentation algorithm based on the numerical solution of the Allen-Cahn non-linear diffusion partial differential equation. This equation is related to the motion of curves by mean curvature. It exhibits several suitable mathematical properties including stable solution profile. This allows the user to follow accurately the position of the segmentation curve by bringing it quickly to the vicinity of the segmented object and by approaching the details of thesegmentation curve. The purpose of the article is to indicate how the algorithm parameters are set up and to show how the algorithm behaves when applied to the particular class of medical data. In detail we describe the algorithm parameters influencingthe segmentation procedure. The left ventricle volume estimated by the segmentation of scanned slices is evaluated through the cardiac cycle. Consequently, the ejection fraction is evaluated. The described approach allows the user to proc

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

BA - Obecná matematika

OECD FORD obor

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Projekt

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Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2013

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Kybernetika

ISSN

0023-5954

e-ISSN

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Svazek periodika

49

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

18

Strana od-do

301-318

Kód UT WoS článku

000329259300007

EID výsledku v databázi Scopus

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