Articular cartilage defect detection based on image segmentation with colour mapping
The result's identifiers
Result code in 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>
Alternative codes found
RIV/61989100:27740/14:86092914
Result on the web
<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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Alternative languages
Result language
angličtina
Original language name
Articular cartilage defect detection based on image segmentation with colour mapping
Original language description
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
Czech name
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Czech description
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Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
JC - Computer hardware and software
OECD FORD branch
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Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
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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Volume of the periodical
2014
Issue of the periodical within the volume
8733
Country of publishing house
DE - GERMANY
Number of pages
9
Pages from-to
214-222
UT code for WoS article
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EID of the result in the Scopus database
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