Soft-tissues Image Processing: Comparison of Traditional Segmentation Methods with 2D active Contour Methods

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68081731%3A_____%2F12%3A00385188" target="_blank" >RIV/68081731:_____/12:00385188 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216305:26220/12:PU99076

Výsledek na webu

<a href="http://dx.doi.org/10.2478/v10048-012-0023-8" target="_blank" >http://dx.doi.org/10.2478/v10048-012-0023-8</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.2478/v10048-012-0023-8" target="_blank" >10.2478/v10048-012-0023-8</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Soft-tissues Image Processing: Comparison of Traditional Segmentation Methods with 2D active Contour Methods

Popis výsledku v původním jazyce

The paper deals with modern methods of image processing, especially image segmentation, classification and evaluation of parameters. It focuses primarily on processing medical images of soft tissues obtained by magnetic resonance tomography (MR). It is easy to describe edges of the sought objects using segmented images. The edges found can be useful for further processing of monitored object such as calculating the perimeter, surface and volume evaluation or even three-dimensional shape reconstruction.The proposed solutions can be used for the classification of healthy/unhealthy tissues in MR or other imaging. Application examples of the proposed segmentation methods are shown. Research in the area of image segmentation focuses on methods based on solving partial differential equations. This is a modern method for image processing, often called the active contour method. It is of great advantage in the segmentation of real images degraded by noise with fuzzy edges and transitions betw

Název v anglickém jazyce

Soft-tissues Image Processing: Comparison of Traditional Segmentation Methods with 2D active Contour Methods

Popis výsledku anglicky

The paper deals with modern methods of image processing, especially image segmentation, classification and evaluation of parameters. It focuses primarily on processing medical images of soft tissues obtained by magnetic resonance tomography (MR). It is easy to describe edges of the sought objects using segmented images. The edges found can be useful for further processing of monitored object such as calculating the perimeter, surface and volume evaluation or even three-dimensional shape reconstruction.The proposed solutions can be used for the classification of healthy/unhealthy tissues in MR or other imaging. Application examples of the proposed segmentation methods are shown. Research in the area of image segmentation focuses on methods based on solving partial differential equations. This is a modern method for image processing, often called the active contour method. It is of great advantage in the segmentation of real images degraded by noise with fuzzy edges and transitions betw

Druh

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

CEP obor

JA - Elektronika a optoelektronika, elektrotechnika

OECD FORD obor

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Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2012

Kód důvěrnosti údajů

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

Název periodika

Measurement Science Review

ISSN

1335-8871

e-ISSN

—

Svazek periodika

12

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

SK - Slovenská republika

Počet stran výsledku

9

Strana od-do

153-161

Kód UT WoS článku

000307943000006

EID výsledku v databázi Scopus

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