Hub
  • Software
  • Blog
  • Forum
  • Events
  • Documentation
  • About KNIME
  • KNIME Hub
  • knime
  • Spaces
  • Life Sciences
  • Image_Processing
  • KNIME Executors on HPC
  • cell segmentation usecase
  • cell-segmentation-worker
WorkflowWorkflow

Cell Segmentation (Worker)

Cell segmentation Image processing Microscopy

Last edited: 

Drag & drop
Like
Download workflow
Copy short link
Workflow preview
The workflow aims to segment cell nuclei from cytoplasm. As a first step the images need to be preprocessed by splitting the channels into separate columns, nuclei and cytoplasm. To correct for background staining and reduce noise, we are performing a background subtraction of the nuclei channel and also apply Gaussian smoothing. For segmentation, we first use the Otsu threshold method to distinguish between foreground and background. Afterwards we identify and label connected components (=nuclei) using the Connected Component Analysis node. Subsequently, we remove cell clumps and too small nuclei. As a last step, we perform a Voronoi based segmentation that identifies and labels the corresponding cytoplasm to the already labeled nuclei.

Used extensions & nodes

Created with KNIME Analytics Platform version 4.5.2
  • Go to item
    KNIME Base nodes Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.5.2

  • Go to item
    KNIME Basic File System Connectors Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.5.2

  • Go to item
    KNIME Expressions Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.5.1

  • Go to item
    KNIME Image Processing Trusted extension

    University of Konstanz / KNIME

    Version 1.8.3

  • Go to item
    KNIME Workflow Services Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.5.0

  1. Go to item
  2. Go to item
  3. Go to item
  4. Go to item
  5. Go to item
  6. Go to item

Legal

By using or downloading the workflow, you agree to our terms and conditions.

Discussion
Discussions are currently not available, please try again later.

KNIME
Open for Innovation

KNIME AG
Hardturmstrasse 66
8005 Zurich, Switzerland
  • Software
  • Getting started
  • Documentation
  • E-Learning course
  • Solutions
  • KNIME Hub
  • KNIME Forum
  • Blog
  • Events
  • Partner
  • Developers
  • KNIME Home
  • KNIME Open Source Story
  • Careers
  • Contact us
Download KNIME Analytics Platform Read more on KNIME Server
© 2022 KNIME AG. All rights reserved.
  • Trademarks
  • Imprint
  • Privacy
  • Terms & Conditions
  • Credits