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Modeling and Features Extraction of Blood Vessels based on Soft Regional Segmentation

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F18%3A10241601" target="_blank" >RIV/61989100:27240/18:10241601 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.scopus.com/record/display.uri?eid=2-s2.0-85052868511&origin=resultslist&sort=plf-f&src=s&sid=ccee54aa40814fb6d866f65604a4c9df&sot=autdocs&sdt=autdocs&sl=18&s=AU-ID%2824823900000%29&relpos=21&citeCnt=0&searchTerm=" target="_blank" >https://www.scopus.com/record/display.uri?eid=2-s2.0-85052868511&origin=resultslist&sort=plf-f&src=s&sid=ccee54aa40814fb6d866f65604a4c9df&sot=autdocs&sdt=autdocs&sl=18&s=AU-ID%2824823900000%29&relpos=21&citeCnt=0&searchTerm=</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.ifacol.2018.07.181" target="_blank" >10.1016/j.ifacol.2018.07.181</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Modeling and Features Extraction of Blood Vessels based on Soft Regional Segmentation

  • Original language description

    Analysis and visualization of the blood vessels has a crucial impact for the clinical practice. One of the most important aspects of such analysis is the blood vessels features extraction characterizing their state and manifestation. Such procedure may be done by using the mathematical modeling of the blood vessels which is not conventionally possible from the native records. We have proposed a mathematical segmentation model for extraction and modeling of the blood vessels structure from the CT angiography native records with a target of differentiation of the physiological blood vessels from calcification spots indicating areas where the blood vessel is damaged. Such model consequently allows for objective quantification of the calcification amount, as an important clinical parameter of the damage level of the blood vessel. The method is based on the histogram partitioning, and consequent classification via predefined number of the fuzzy triangular classes representing individual parts of the blood vessels. Consequent part of the segmentation model takes into account spatial relations inside of each region to make a model accurate, and robust against the noise and artefacts. As a part of our analysis we have tested the computation complexity of the proposed segmentation model. (C) 2018

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database

  • CEP classification

  • OECD FORD branch

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

Result continuities

  • 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)

Others

  • Publication year

    2018

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    IFAC-PapersOnLine. Volume 51

  • ISSN

    2405-8963

  • e-ISSN

  • Volume of the periodical

    51

  • Issue of the periodical within the volume

    6

  • Country of publishing house

    NL - THE KINGDOM OF THE NETHERLANDS

  • Number of pages

    6

  • Pages from-to

    366-371

  • UT code for WoS article

  • EID of the result in the Scopus database

    2-s2.0-85052868511