Extraction of blood vessels using multilevel thresholding with color coding

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F16%3A86099583" target="_blank" >RIV/61989100:27240/16:86099583 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-3-319-24584-3_33" target="_blank" >http://dx.doi.org/10.1007/978-3-319-24584-3_33</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-24584-3_33" target="_blank" >10.1007/978-3-319-24584-3_33</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Extraction of blood vessels using multilevel thresholding with color coding

Popis výsledku v původním jazyce

The proposed work deals with the design of algorithm for segmentation of blood vessels in order to extract the geometrical features of analyzed vessels. The algorithm was tested on a sample of 25 clinical data to identify blood vessels direction and suppress surrounding tissues. The proposed methodology is effective for practical purposes, because identifies minor visual differences on the surface of blood vessels. These changes often represent pathological lesions that cannot be identified from the native data. The algorithm is based on the identification of several significant levels to make ideal thresholding, according to object features. For even better diagnostic results image background is subsequently filtered out from the segmented image, background may have a disturbing effect in the diagnosis and the final segmented image contains only analyzed blood vessels.

Název v anglickém jazyce

Extraction of blood vessels using multilevel thresholding with color coding

Popis výsledku anglicky

The proposed work deals with the design of algorithm for segmentation of blood vessels in order to extract the geometrical features of analyzed vessels. The algorithm was tested on a sample of 25 clinical data to identify blood vessels direction and suppress surrounding tissues. The proposed methodology is effective for practical purposes, because identifies minor visual differences on the surface of blood vessels. These changes often represent pathological lesions that cannot be identified from the native data. The algorithm is based on the identification of several significant levels to make ideal thresholding, according to object features. For even better diagnostic results image background is subsequently filtered out from the segmented image, background may have a disturbing effect in the diagnosis and the final segmented image contains only analyzed blood vessels.

Druh

D - Stať ve sborníku

CEP obor

JC - Počítačový hardware a software

OECD FORD obor

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Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2016

Kód důvěrnosti údajů

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

Název statě ve sborníku

Lecture Notes in Electrical Engineering. Volume 362

ISBN

978-3-319-24582-9

ISSN

1876-1100

e-ISSN

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Počet stran výsledku

10

Strana od-do

397-406

Název nakladatele

Springer Verlag

Místo vydání

London

Místo konání akce

Phuket

Datum konání akce

9. 6. 2015

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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