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Random Forests Pixel-wise Classification for Detection and Segmentation of Cells in the Images from Holographic Microscope

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F17%3APU124471" target="_blank" >RIV/00216305:26220/17:PU124471 - isvavai.cz</a>

  • Result on the web

    <a href="http://www.radio.feec.vutbr.cz/ieee/userfiles/downloads/archive/2017-Mikulov/Proceedings_Mikulov_2017.pdf" target="_blank" >http://www.radio.feec.vutbr.cz/ieee/userfiles/downloads/archive/2017-Mikulov/Proceedings_Mikulov_2017.pdf</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Random Forests Pixel-wise Classification for Detection and Segmentation of Cells in the Images from Holographic Microscope

  • Original language description

    Microscopic cell image analysis is widely used by biologists for cell behavior and cell morphology study. In dense cell cultures precise single-cell segmentation is challenging task and it is an important step for automatic cell analysis methods. This work introduces a novel method for robust single cell segmentation of images from holographic microscope. The method is based on pixel-wise classification with random forests for both background segmentation a cell detection, where cell detection image is refined with distance transform based detector. Final single cell segmentation combines both detection and background with seeded watershed. Proposed background segmentation part reaches results similar to other algorithms, but cell detection part of the algorithm is innovative and achieves significantly better result than commonly used detector.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    20204 - Robotics and automatic control

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

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

    Proceedings of IEEE Student Branch Conference Mikulov 2017

  • ISBN

    978-80-214-5526-9

  • ISSN

  • e-ISSN

  • Number of pages

    4

  • Pages from-to

    67-70

  • Publisher name

    Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií

  • Place of publication

    Brno

  • Event location

    Mikulov, Czech republic

  • Event date

    Aug 28, 2017

  • Type of event by nationality

    EUR - Evropská akce

  • UT code for WoS article