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Bioimaging ? Autothresholding and segmentation via neural networks

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60076658%3A12520%2F17%3A43895368" target="_blank" >RIV/60076658:12520/17:43895368 - isvavai.cz</a>

  • Alternative codes found

    RIV/49777513:23520/17:43932945

  • Result on the web

    <a href="https://link.springer.com/chapter/10.1007/978-3-319-56148-6_31#enumeration" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-319-56148-6_31#enumeration</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-319-56148-6_31" target="_blank" >10.1007/978-3-319-56148-6_31</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Bioimaging ? Autothresholding and segmentation via neural networks

  • Original language description

    Bioimaging, image segmentation, thresholding, and multivariate processing are helpful tools in analysis of series of images from many time lapse experiments. The different methods of mathematic, algorithmization and artificial intelligence could by modified, parametrized or adopted for single purpose case of completely different biological background (namely microorganisms, tissue cultures, aquaculture). However, most of the task is based on initial image segmentation, before features axtraction and comparison tasks are evaluated. In this article, we compare several of classical approaches in bioinformatical and biophysical cases with the neural network approach. The concept of neural network was adopted from the biological neural networks. Th networks need to be trained, however after the learning phase, they should be able to find one solution for various objects. The comparison of the methods is evaluated via error in segmentation according to the human supervisor.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    20204 - Robotics and automatic control

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

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

Others

  • Publication year

    2017

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Lecture Notes in Computer Science

  • ISBN

    978-3-319-56147-9

  • ISSN

    0302-9743

  • e-ISSN

    neuvedeno

  • Number of pages

    11

  • Pages from-to

    358-368

  • Publisher name

    Springer Verlag

  • Place of publication

    Cham

  • Event location

    Granada, Španělsko

  • Event date

    Apr 26, 2017

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article