I am using a nicely working KNIME + headless Ilastik workflow to segment and quantify four channel images originating from high-content screening. When taking images over several hours in multiple 384-well plates it is unfortunately unavoidable that some fields-of-view are de-focused occur as “blurry” and less intense or that some other areas are too bright due to debris or aggregates. To improve data quality and speed up the workflow (less bad data going through analysis for nothing), I would like to sort out such images at the beginning.
A number of pixel intensity-based statistical methods have been described, for example PLLS (Power log-log slope). It’s actually part of CellProfiler.
Question 1: Does such a field-of-view quality control tool/node exist already in KNIME?
In case not, I started to experiment with the FIJI plugin “Microscope Image Focus Quality”. It uses a pre-trained TensorFlow model to assess image focus in multiple tiles per image (https://imagej.net/Microscope_Focus_Quality). This works very well for my images. However, I don’t manage to run this macro in KNIME. The “ImageJ macro” node doesn’t execute this plugins macro code. I also could not get it working using the “Run Script” node. But I have to say I’m fairly new to combining ImageJ with KNIME, so I might be missing the obvious.
Question 2: What is the best way to run a non-preinstalled ImageJ macro in KNIME?
Thanks for your help!