About: Articular cartilage defect detection based on image segmentation with colour mapping     Goto   Sponge   Distinct   Permalink

An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

AttributesValues
rdf:type
rdfs:seeAlso
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 physician encounters. 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 cartilaginous tissue 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 tissues have been interrupted. The suggested methodology has been tested using real data from magnetic resonance images of 60 patients from Podlesí Hospital in Třinec and currently this method is being put into clinical practice.
  • 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 physician encounters. 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 cartilaginous tissue 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 tissues have been interrupted. The suggested methodology has been tested using real data from magnetic resonance images of 60 patients from Podlesí Hospital in Třinec and currently this method is being put into clinical practice. (en)
Title
  • Articular cartilage defect detection based on image segmentation with colour mapping
  • Articular cartilage defect detection based on image segmentation with colour mapping (en)
skos:prefLabel
  • Articular cartilage defect detection based on image segmentation with colour mapping
  • Articular cartilage defect detection based on image segmentation with colour mapping (en)
skos:notation
  • RIV/61989100:27740/14:86092914!RIV15-MSM-27740___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • S
http://linked.open...iv/cisloPeriodika
  • 8733
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 4147
http://linked.open...ai/riv/idVysledku
  • RIV/61989100:27740/14:86092914
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Soft thresholding; MRI; Membership function; MATLAB; Image segmentation; Fuzzy modelling (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...odStatuVydavatele
  • DE - Spolková republika Německo
http://linked.open...ontrolniKodProRIV
  • [0AB6A1F2ED13]
http://linked.open...i/riv/nazevZdroje
  • Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Volume 6678 LNAI, Issue PART 1
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...v/svazekPeriodika
  • 2014
http://linked.open...iv/tvurceVysledku
  • Penhaker, Marek
  • Kubíček, Jan
  • Bryjová, Iveta
  • Kodaj, Michal
issn
  • 0302-9743
number of pages
http://localhost/t...ganizacniJednotka
  • 27740
Faceted Search & Find service v1.16.118 as of Jun 21 2024


Alternative Linked Data Documents: ODE     Content Formats:   [cxml] [csv]     RDF   [text] [turtle] [ld+json] [rdf+json] [rdf+xml]     ODATA   [atom+xml] [odata+json]     Microdata   [microdata+json] [html]    About   
This material is Open Knowledge   W3C Semantic Web Technology [RDF Data] Valid XHTML + RDFa
OpenLink Virtuoso version 07.20.3240 as of Jun 21 2024, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (126 GB total memory, 112 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software