Current Automatic Methods for Knee Cartilage Segmentation: A Review
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F19%3A10243838" target="_blank" >RIV/61989100:27240/19:10243838 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/8946132/algorithms#algorithms" target="_blank" >https://ieeexplore.ieee.org/document/8946132/algorithms#algorithms</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/EUVIP47703.2019.8946132" target="_blank" >10.1109/EUVIP47703.2019.8946132</a>
Alternative languages
Result language
angličtina
Original language name
Current Automatic Methods for Knee Cartilage Segmentation: A Review
Original language description
Knee cartilage segmentation has been challenging task for many years. This task is usually connected with two major issues. First object of interest is automatic detection and extraction of knee cartilage shape. Second important issue is detection of osteoarthritis, especially, in early stages. This early deterioration is badly recognizable from native images segmentation significantly contributes to precise localization, detection and extraction of early osteoarthritis. Generally, the knee cartilage automatic segmentation and extraction can be performed by various approaches including edge tracking, intensity-based methods, supervised learning, energy minimization, statistical methods and multiregional segmentation methods. Using of particular segmentation method depends on a compromise which user is willing to accept with respect to robustness, segmentation purpose, computational time, accuracy and level of user interaction. This review is mainly focused on fully automatic segmentation methods bringing the recent informations about modeling of cartilage structure via segmentation approaches. (C) 2019 IEEE.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings - European Workshop on Visual Information Processing, EUVIP 2019
ISBN
978-1-72814-496-2
ISSN
2471-8963
e-ISSN
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Number of pages
6
Pages from-to
117-122
Publisher name
IEEE
Place of publication
Piscataway
Event location
Řím
Event date
Oct 28, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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