Articular cartilage defect detection based on image segmentation with colour mapping

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F14%3A86092914" target="_blank" >RIV/61989100:27240/14:86092914 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/61989100:27740/14:86092914

Výsledek na webu

<a href="http://link.springer.com/chapter/10.1007%2F978-3-319-11289-3_22" target="_blank" >http://link.springer.com/chapter/10.1007%2F978-3-319-11289-3_22</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Articular cartilage defect detection based on image segmentation with colour mapping

Popis výsledku v původním jazyce

This article addresses a possible approach for a higher quality diagnosis and detection of the pathological defects of articular cartilage. The defects of articular cartilage are one of the most common pathologies of articular cartilage that a physicianencounters. In clinical practice, doctors can only estimate visually whether or not there is a pathological defect with the use of magnetic resonance images. Our proposed methodology is able to accurately and precisely localize ruptures of cartilaginoustissue and thus greatly contribute to improving a final diagnosis. When analysing MRI data, we work only with grey-levels, which is rather complicated for producing a quality diagnosis. Our proposed algorithm, based on fuzzy logic, brings together various shades of grey. Each set is assigned a colour that corresponds to the density of the tissue. With this procedure, it is possible to create a contrast map of individual tissue structures and very clearly identify where cartilaginous tiss

Název v anglickém jazyce

Articular cartilage defect detection based on image segmentation with colour mapping

Popis výsledku anglicky

This article addresses a possible approach for a higher quality diagnosis and detection of the pathological defects of articular cartilage. The defects of articular cartilage are one of the most common pathologies of articular cartilage that a physicianencounters. In clinical practice, doctors can only estimate visually whether or not there is a pathological defect with the use of magnetic resonance images. Our proposed methodology is able to accurately and precisely localize ruptures of cartilaginoustissue and thus greatly contribute to improving a final diagnosis. When analysing MRI data, we work only with grey-levels, which is rather complicated for producing a quality diagnosis. Our proposed algorithm, based on fuzzy logic, brings together various shades of grey. Each set is assigned a colour that corresponds to the density of the tissue. With this procedure, it is possible to create a contrast map of individual tissue structures and very clearly identify where cartilaginous tiss

Druh

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

CEP obor

JC - Počítačový hardware a software

OECD FORD obor

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Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2014

Kód důvěrnosti údajů

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

Název periodika

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Volume 6678 LNAI, Issue PART 1

ISSN

0302-9743

e-ISSN

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Svazek periodika

2014

Číslo periodika v rámci svazku

8733

Stát vydavatele periodika

DE - Spolková republika Německo

Počet stran výsledku

9

Strana od-do

214-222

Kód UT WoS článku

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EID výsledku v databázi Scopus

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