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Nuclei Classification Trainig

HCS Image segmentation Classification Phenotypes

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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

Used extensions & nodes

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

    KNIME AG, Zurich, Switzerland

    Version 4.1.4

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    KNIME Excel Support Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.4

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    KNIME HCS Tools Trusted extension

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

    Version 4.0.0

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    KNIME Image Processing Trusted extension

    University of Konstanz / KNIME

    Version 1.8.1

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    KNIME Image Processing - ImageJ Integration (Beta)

    KNIME / LOCI

    Version 0.11.6

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    KNIME Math Expression (JEP) Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.0

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    KNIME Quick Forms Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.4

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    KNIME Virtual Nodes Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.0

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