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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

  • DOI - Digital Object Identifier

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

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    JD - Use of computers, robotics and its application

  • OECD FORD branch

Result continuities

  • Project

  • 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

  • e-ISSN

  • 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