The following operations are part of the pipeline.
Pipeline operations layout
Input ROI
This operation allows to select the region of interest (ROI). ROI defines the dataset subarea that will be processed and analyzed by the pipeline.
Denoising
Set of operations performing noise reduction. Choose the more suitable method based on your sample and define the diameter.
Blob Finder
Automatic objects detection algorithm. It uses a local threshold method.
Blob Finder results
If you have set the parameters correctly, the preview (see Previewing the results) should look like this:
Region Growing
Automatic objects detection algorithm based on region growing approach. It uses the nuclei (seeds) previously segmented by the Blob Finder operation as starting point for the growing task.
Region Growing parameters
|
Parameter |
Description |
|
|---|---|---|
|
Seeds |
Sets the input (seeds). |
|
|
Method |
Sets the seeding method. |
|
|
– |
Watershed |
Segments bright objects such as cells by growing from seeds to the border of an object. |
|
– |
Membrane-based watershed |
Segments dark objects such as membrane staining by growing from the seeds to the bright intensity outlines. |
|
Channel |
Sets the analysis target channel. |
|
|
Threshold |
Set the region growing threshold. |
|
|
Max. distance |
Set the Maximum distance on which (within) the region growing will act. |
|
Region Growing results
If you have set the parameters correctly, the preview (see Previewing the results) should look like this:
Store Objects
Store the detected segments (tag) in the active dataset.
Results (segments and measurements) will be stored in the dataset only if this operation has been correctly set. Check appropriately the option before completing the pipeline execution.