Segmentation of Knee Cartilage: A Comprehensive Review

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F18%3A10244452" target="_blank" >RIV/61989100:27240/18:10244452 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.ingentaconnect.com/content/asp/jmihi/2018/00000008/00000003/art00001" target="_blank" >https://www.ingentaconnect.com/content/asp/jmihi/2018/00000008/00000003/art00001</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1166/jmihi.2018.2376" target="_blank" >10.1166/jmihi.2018.2376</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Segmentation of Knee Cartilage: A Comprehensive Review

Popis výsledku v původním jazyce

The main aim of this study is a complex critical review of the methods applicable for the knee cartilage segmentation. Segmentation of the knee cartilage is intended for a quantitative and qualitative analysis of cartilage morphological structure. This task is important in a field of the clinical practice in the context of an early diagnosis of the pathological changes, such as the osteoarthritis. The cartilage segmentation methods are divided into manual, semiautomatic and automatic approaches, each of this group is associated with a certain level of the user interaction. Generally, the knee cartilage segmentation and extraction can be performed by various approaches including the edge tracking, intensity based methods, supervised learning, energy minimization, statistical methods and multiregional segmentation methods. Using of particular segmentation method is depended on a compromise which user is willing to accept with a respect to the robustness, segmentation purpose, computational time, accuracy and level of user interaction. Some of the presented methods are intended for a detection of cartilage shape, moreover other methods are able to identify the pathological changes badly recognizable from the native image records.

Název v anglickém jazyce

Segmentation of Knee Cartilage: A Comprehensive Review

Popis výsledku anglicky

The main aim of this study is a complex critical review of the methods applicable for the knee cartilage segmentation. Segmentation of the knee cartilage is intended for a quantitative and qualitative analysis of cartilage morphological structure. This task is important in a field of the clinical practice in the context of an early diagnosis of the pathological changes, such as the osteoarthritis. The cartilage segmentation methods are divided into manual, semiautomatic and automatic approaches, each of this group is associated with a certain level of the user interaction. Generally, the knee cartilage segmentation and extraction can be performed by various approaches including the edge tracking, intensity based methods, supervised learning, energy minimization, statistical methods and multiregional segmentation methods. Using of particular segmentation method is depended on a compromise which user is willing to accept with a respect to the robustness, segmentation purpose, computational time, accuracy and level of user interaction. Some of the presented methods are intended for a detection of cartilage shape, moreover other methods are able to identify the pathological changes badly recognizable from the native image records.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/GA17-03037S" target="_blank" >GA17-03037S: Hodnocení investic do vývoje zdravotních prostředků</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2018

Kód důvěrnosti údajů

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

Název periodika

Journal of medical imaging and health informatics

ISSN

2156-7018

e-ISSN

—

Svazek periodika

8

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

18

Strana od-do

401-418

Kód UT WoS článku

000428166200001

EID výsledku v databázi Scopus

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