Time deformable segmentation model based on the active contour driven by Gaussian energy distribution: Extraction and modeling of early articular cartilage pathological interuptions

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F17%3A10237653" target="_blank" >RIV/61989100:27240/17:10237653 - isvavai.cz</a>

Result on the web

<a href="http://ebooks.iospress.nl/publication/47569" target="_blank" >http://ebooks.iospress.nl/publication/47569</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3233/978-1-61499-800-6-242" target="_blank" >10.3233/978-1-61499-800-6-242</a>

Result language

angličtina

Original language name

Time deformable segmentation model based on the active contour driven by Gaussian energy distribution: Extraction and modeling of early articular cartilage pathological interuptions

Original language description

In the clinical orthopaedics, the articular cartilage monitoring is an important task having especially preventive effect. The magnetic resonance (MR) is commonly used clinical standard allowing for the effective differentiation of articular cartilage from surrounding tissues (bones, soft tissues). Nevertheless, the early pathological interruptions are often badly recognizable from the native MR records. This fact significantly influences clinical diagnosis. We have carried out the analysis of the segmentation method based on the active contour with the aim of autonomous modelling articular cartilage and indication of the early cartilage interruptions. The active contour model represents time deformable model adopting the articular cartilage geometrical features with respect to cartilage interruptions. Model of the articular cartilage reflects area of the physiological cartilage in the form of binary segmentation while the active contour model is terminated in the spot of the early pathological sign. Therefore, this time deformable model has ambitions to be used as a feedback to subjective physician&apos;s opinion because the model clearly differentiates the physiological cartilage structure from the early cartilage loss. © 2017 The authors and IOS Press. All rights reserved.

Czech name

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Czech description

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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)

Project

<a href="/en/project/GA17-03037S" target="_blank" >GA17-03037S: Investment evaluation of medical device development</a><br>

Continuities

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

Publication year

2017

Confidentiality

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

Article name in the collection

Frontiers in Artificial Intelligence and Applications. Volume 297

ISBN

978-1-61499-799-3

ISSN

0922-6389

e-ISSN

1535-6698

Number of pages

14

Pages from-to

242-255

Publisher name

IOS Press

Place of publication

Amsterodam

Event location

Kitakjúšú

Event date

Sep 26, 2017

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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