Automated Spheriod Detection

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This workflow demonstrates how to retrieve raw images taken with CytoSMART Lux2 and Lux3 BR microscopes via a (custom) SiLA 2 server. The images are processed and a pretrained neural network is applied to detect spheroids. The results are send back to the SiLA 2 server. Additionally a report is created and send via email to the user.

**IMPORTANT**
This workflow requires a Java library that we have not bundled to keep the file size minimal. Please import the entire SiLA Prototype workflow group (see link below) to run this workflow.

**IMPORTANT**
In order to successfully run this workflow, you have to setup a custom SiLA2 server. Please follow these instructions to start it:

1. Make sure that you have at least Java 8 installed on your computer and that the according environment variables are correctly set. (You can check this in a terminal by executing “java -version”)

2. Open a terminal or commandline and execute the following command: “java -jar server -p 50052 -data ”. (You can figure out the paths by right clicking on the respective item in the KNIME Explorer and selecting Copy Location > Local path)

3. Make sure that you see some output like "2021-01-08 12:37:31 INFO s.l.s.SiLAServer:97 - Server started on port=50052" in the terminal.

Components and (custom) SiLa Server were developed by Mike Groezinger (mike.groezinger@siobra.de) and Stefan Helfrich (stefan.helfrich@knime.com).

Nodes

• Component Input4 ×
• Component Output4 ×
• Column Appender2 ×
• Column Filter2 ×
• Column Selection Configuration2 ×
• Show all 33 nodes

Extensions

• FeatureKNIME Base nodes
• FeatureKNIME Basic File System Connectors
• FeatureKNIME Column Expressions (legacy)
• FeatureKNIME Deep Learning - Keras Integration
• FeatureKNIME Image Processing
• Show all 9 modules

Links

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