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Comparison of full-size and patches-based learning approaches for aneurysm segmentation in TOF-MRI data

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F22%3APU150906" target="_blank" >RIV/00216305:26220/22:PU150906 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2022_sbornik_1_v2.pdf" target="_blank" >https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2022_sbornik_1_v2.pdf</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Comparison of full-size and patches-based learning approaches for aneurysm segmentation in TOF-MRI data

  • Original language description

    The paper is interested in segmentation of intracranial aneurysms. Intracranial aneurysms are life-threatening issue. In this paper there are proposed two methods for this segmentation problem. First one is segmentation with use of full size images, the other one uses patches of the image, which could help decrease the ration between pixels representing background and pixels representing aneurysms. Data from ADAM challenge 2020 are used to train and evaluate these approaches. Using full images show better results in dice coefficient, which is 0.16 greater, then patched image approach.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    20200 - Electrical engineering, Electronic engineering, Information engineering

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2022

  • 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 I of the 28th Conference STUDENT EEICT 2022 General papers

  • ISBN

    978-80-214-6029-4

  • ISSN

  • e-ISSN

  • Number of pages

    4

  • Pages from-to

    247-250

  • Publisher name

    Brno University of Technology, Faculty of Electronic Engineering and Communication

  • Place of publication

    Brno

  • Event location

    Brno

  • Event date

    Apr 26, 2022

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article