Segmentation of MRI data to extract the blood vessels based on fuzzy thresholding

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F15%3A86096607" target="_blank" >RIV/61989100:27240/15:86096607 - isvavai.cz</a>

Výsledek na webu

<a href="http://link.springer.com/chapter/10.1007%2F978-3-319-16211-9_5" target="_blank" >http://link.springer.com/chapter/10.1007%2F978-3-319-16211-9_5</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-16211-9_5" target="_blank" >10.1007/978-3-319-16211-9_5</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Segmentation of MRI data to extract the blood vessels based on fuzzy thresholding

Popis výsledku v původním jazyce

The article discusses the design of appropriate methodology of segmentation and visualization of MRI data to extract the blood vessels. The main objective of the proposed algorithm is effective separation individual vessels and adjecent structures. In clinical practice, it is necessary to assess the progress of the blood vessels in order to assess the condition of the vascular system. For physician who performs diagnosis is much more rewarding to perform analysis of an image that contains only vascularelements. The proposed method of image segmentation can effectively separate the individual blood vessels from surrounding tissue structures. The output of this analysis is the color coding of the input image data to distinguish contrasting behavior of individual vessels that are at the forefront of our concerns, the structures that we need in the picture.

Název v anglickém jazyce

Segmentation of MRI data to extract the blood vessels based on fuzzy thresholding

Popis výsledku anglicky

The article discusses the design of appropriate methodology of segmentation and visualization of MRI data to extract the blood vessels. The main objective of the proposed algorithm is effective separation individual vessels and adjecent structures. In clinical practice, it is necessary to assess the progress of the blood vessels in order to assess the condition of the vascular system. For physician who performs diagnosis is much more rewarding to perform analysis of an image that contains only vascularelements. The proposed method of image segmentation can effectively separate the individual blood vessels from surrounding tissue structures. The output of this analysis is the color coding of the input image data to distinguish contrasting behavior of individual vessels that are at the forefront of our concerns, the structures that we need in the picture.

Druh

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

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

—

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2015

Kód důvěrnosti údajů

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

Název periodika

Studies in Computational Intelligence. Volume 598

ISSN

1860-949X

e-ISSN

—

Svazek periodika

598

Číslo periodika v rámci svazku

2015

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

10

Strana od-do

43-52

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-84938274169