3D LUNG SEGMENTATION SEGMENTATION USING MARKOV RANDOM FIELDS
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F14%3APU109130" target="_blank" >RIV/00216305:26220/14:PU109130 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
3D LUNG SEGMENTATION SEGMENTATION USING MARKOV RANDOM FIELDS
Original language description
In this paper, Bayesian classification with Markov random fields is used for 3D Computed Tomography (3D CT) lung image segmentation and modified metropolis dynamic is employed as optimization algorithm. Lung tissue is well separated from the other tissues like a bones, muscles, surrounding soft tissue and fat. Segmentation is necessary for subsequent lung analysis (size, shape, lung contour, etc.), and lung blood-vessels, airways (bronchi, bronchioles) segmentation and tumour studies.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
JD - Use of computers, robotics and its application
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
Article name in the collection
Proceedings of the 20th Conference STUDENT EEICT 2014 Volume 3
ISBN
978-80-214-4924-4
ISSN
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e-ISSN
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Number of pages
5
Pages from-to
217-221
Publisher name
LITERA
Place of publication
Brno
Event location
Brno
Event date
Apr 24, 2014
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
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