Segmentation of CT arteriography based on combination of segmentation methods

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F11%3A43898227" target="_blank" >RIV/49777513:23520/11:43898227 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1134/S105466181102088X" target="_blank" >http://dx.doi.org/10.1134/S105466181102088X</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1134/S105466181102088X" target="_blank" >10.1134/S105466181102088X</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Segmentation of CT arteriography based on combination of segmentation methods

Popis výsledku v původním jazyce

This paper describes a solution of CT arteriography vessel segmentation using a combination of methods for segmentation of image data. Computer tomography (CT) is one of the most useful approaches for investigating the arterial system and its pathologies. There are three ways for segmenting the vessels from the CT image - manually, fully automatically and with a user interaction. We considered the (semi)automatic approaches, because the manual way is too timeconsuming and humandependent. We used a combination of three segmentation techniques: thresholding, edge detection and region growing. Results of this method were consulted then with a medicine expert. None of these techniques can be used separately, but a combi nation of them brought very good results, which can be used in medicine.

Název v anglickém jazyce

Segmentation of CT arteriography based on combination of segmentation methods

Popis výsledku anglicky

This paper describes a solution of CT arteriography vessel segmentation using a combination of methods for segmentation of image data. Computer tomography (CT) is one of the most useful approaches for investigating the arterial system and its pathologies. There are three ways for segmenting the vessels from the CT image - manually, fully automatically and with a user interaction. We considered the (semi)automatic approaches, because the manual way is too timeconsuming and humandependent. We used a combination of three segmentation techniques: thresholding, edge detection and region growing. Results of this method were consulted then with a medicine expert. None of these techniques can be used separately, but a combi nation of them brought very good results, which can be used in medicine.

Druh

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

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

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Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2011

Kód důvěrnosti údajů

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

Název periodika

Pattern Recognition and Image Analysis

ISSN

1054-6618

e-ISSN

—

Svazek periodika

21

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

RU - Ruská federace

Počet stran výsledku

3

Strana od-do

553-555

Kód UT WoS článku

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EID výsledku v databázi Scopus

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