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Nuclei Classification Trainig

HCSImage segmentationClassificationPhenotypes
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May 14, 2019 9:15 AM
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This workflow reads images from a high throughput experiment acquired with an Olympus ScanR Microscope. A subset of the image data is used to train a classifier, which is then applied to the whole data setA classifier is trained on exemplary images and applied to the whole dataset.

External resources

  • SurveyMonkey
  • HD-HuB
  • de.NBI
  • HCS image dataset
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Used extensions & nodes

Created with KNIME Analytics Platform version 4.1.4 Note: Not all extensions may be displayed.
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    KNIME CoreTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.4

    knime
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    KNIME Excel SupportTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.4

    knime
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    KNIME HCS ToolsTrusted extension

    Max Planck Institute of Molecular Cell Biology and Genetics (MPI-CBG), Dresden, Germany

    Version 4.0.0

    mpicbg-tds
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    KNIME Image ProcessingTrusted extension

    University of Konstanz / KNIME

    Version 1.8.1

    bioml-konstanz
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    KNIME Image Processing - ImageJ Integration (Beta)

    KNIME / LOCI

    Version 0.11.6

    bioml-konstanz
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    KNIME Math Expression (JEP)Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.0

    knime
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    KNIME Quick FormsTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.4

    knime
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    KNIME Virtual NodesTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.0

    knime

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