Batch processing
Learning Objectives
After completing this lesson, learners should be able to:
Automatically process a number of images
Motivation
Scientific discovery is based on reproducibility. Thus, it is very common to apply the same analysis workflow to a number of images, possibly comprising different biological conditions. To achieve this, it is very important to know how to efficiently “batch process” many images.
Concept map
graph TD
I1("Image 1") --> S("Analysis workflow")
I2("Image 2") --> S
IN("Image ...") --> S
S --> R1("Result 1")
S --> R2("Result 2")
S --> RN("Result ...")
Figure
Activities
- Batch process several images containing nuclei.
- Download the images in image_data/batch_process.
- For each image
- Segment the nuclei and save the label mask.
- Measure the nuclei area and save the results in a table.
- For each image
Show activity for:
ImageJ Macro Scijava
Exercises
Show exercise/solution for:ImageJ Macro Scijava
- Download the unfinished.ijm ImageJ macro script.
- Open the script in Fiji.
- The script will not run like this.
- Add code to the lines where it says
TODO
to enable batch processing.
- Tip: you can copy and paste code from the script in this modules activity.
- Tip: to make it work you may also have to add code to some lines where it does not say
TODO
.Solution
- Download solution.ijm.
Assessment
Fill in the blanks
- If you have thousands of images to process you should consider using a ___ .
- Batch processing refers to __ processing many data sets.
Solution
- computer cluster (HPC)
- automatically
Explanations
Follow-up material
Recommended follow-up modules:
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