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Learning to segment cell nuclei in phase-contrast microscopy from fluorescence images for drug discovery

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F22%3A00362696" target="_blank" >RIV/68407700:21230/22:00362696 - isvavai.cz</a>

  • Alternative codes found

    RIV/61989592:15110/22:73618881

  • Result on the web

    <a href="https://doi.org/10.1117/12.2607500" target="_blank" >https://doi.org/10.1117/12.2607500</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1117/12.2607500" target="_blank" >10.1117/12.2607500</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Learning to segment cell nuclei in phase-contrast microscopy from fluorescence images for drug discovery

  • Original language description

    We describe a method for analyzing geometrical properties of cell nuclei from phase contrast microscopy images. This is useful in drug discovery for quantifying the effect of candidate chemical compounds, bypassing the need for fluorescence imaging. Fluorescence images are then only used for training our nuclei segmentation, avoiding the need for the time consuming expert annotations. Geometry based descriptors are calculated and aggregated and fed into a classifier to distinguish the different types of chemical treatments. The drug treatment can be distinguished from no treatment with accuracy better than 95% from fluorescence images and better than 77% from phase contrast images.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • 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/EF16_019%2F0000765" target="_blank" >EF16_019/0000765: Research Center for Informatics</a><br>

  • Continuities

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

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

    Proc. SPIE 12032: Medical Imaging 2022: Image Processing

  • ISBN

    978-1-5106-4939-2

  • ISSN

    1605-7422

  • e-ISSN

  • Number of pages

    7

  • Pages from-to

  • Publisher name

    SPIE

  • Place of publication

    Bellingham

  • Event location

    San Diego

  • Event date

    Feb 20, 2022

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000836295600086